Parameter Types#

IParameter#

class IParameter#

Subclassed by visionflow::param::BinaryPacks, visionflow::param::CameraCalibrationEvaluation, visionflow::param::CameraCalibrationTrainingParameters, visionflow::param::GaugeParameters, visionflow::param::GeometrySearchFeatureModelList, visionflow::param::IAveragePrecisionList, visionflow::param::IPrecisionEvaluation, visionflow::param::ITableList, visionflow::param::LabelClasses, visionflow::param::ModelHealth, visionflow::param::SchemableParameter, visionflow::param::ViewTransformParameterList

ISchemable#

struct ISchemable#

Json Schemable Class API.

A Json Schemable Class is a class that can be serialized to/deserialized from Json and can be validated by Json Schema.

Subclassed by visionflow::param::AnnularSectionParameters, visionflow::param::AssemblyVerificationLayOutArea, visionflow::param::AssemblyVerificationMaxInputSize, visionflow::param::AssemblyVerificationModelParameters, visionflow::param::AssemblyVerificationTargetParameters, visionflow::param::AxialSideLengthRange, visionflow::param::CaliperDualEdgeFuncParameters, visionflow::param::CaliperSingleEdgeFuncParameters, visionflow::param::CategoryAreaAugment, visionflow::param::ChooseIDReader1DTypes, visionflow::param::ChooseIDReader2DTypes, visionflow::param::ClassificationInputShape, visionflow::param::Code128Parameters, visionflow::param::Code39Parameters, visionflow::param::Code93Parameters, visionflow::param::DMECC200Parameters, visionflow::param::DataAugmentation, visionflow::param::DefectSimulation, visionflow::param::DetectionInputShape, visionflow::param::DetectionTrainingStrategy, visionflow::param::Ean13Parameters, visionflow::param::Ean8Parameters, visionflow::param::EdgeFilterPropertyParameters, visionflow::param::ExampleAugRotate, visionflow::param::ExampleAugShift, visionflow::param::FilterScript, visionflow::param::GeoAugDistortion, visionflow::param::GeoAugScale, visionflow::param::GeoAugShift, visionflow::param::GeoAugSlightRotation, visionflow::param::GeometryAugmentation, visionflow::param::GeometrySearchDuplicate, visionflow::param::IDReader1DParameters, visionflow::param::IDReader2DParameters, visionflow::param::ImageAugBrightness, visionflow::param::ImageAugColorFilter, visionflow::param::ImageAugContrast, visionflow::param::ImageAugIlluminationGradient, visionflow::param::ImageAugNoise, visionflow::param::ImageAugSmoothingOrSharpening, visionflow::param::ImageAugmentation, visionflow::param::ImagePreprocessArithmParameters, visionflow::param::ImagePreprocessCirclePolarParameters, visionflow::param::ImagePreprocessCvtColorParameters, visionflow::param::ImagePreprocessFilter2DParameters, visionflow::param::ImagePreprocessFlipParameters, visionflow::param::ImagePreprocessGammaTransParameters, visionflow::param::ImagePreprocessHighPassFilterParameters, visionflow::param::ImagePreprocessLowPassFilterParameters, visionflow::param::ImagePreprocessLutParameters, visionflow::param::ImagePreprocessMorphParameters, visionflow::param::ImagePreprocessParameters, visionflow::param::ImagePreprocessParametersList, visionflow::param::ImagePreprocessResizeParameters, visionflow::param::ImagePreprocessSharpenParameters, visionflow::param::KeyPointNode, visionflow::param::LabeledGeometryAugmentation, visionflow::param::LocationMaxInputSize, visionflow::param::LocationModelParameters, visionflow::param::LocationTargetParameters, visionflow::param::LossCurve, visionflow::param::MicroQRCParameters, visionflow::param::MultiNameKeyPointNode, visionflow::param::NodeMatchTemplate, visionflow::param::OCRAnnulusParameters, visionflow::param::OCRArea, visionflow::param::OCRNodeTemplate, visionflow::param::OCRNodeTemplateArea, visionflow::param::OCRStringTemplate, visionflow::param::OCRStringTemplateArea, visionflow::param::PropertyObjectId, visionflow::param::QRCM1Parameters, visionflow::param::QRCM2Parameters, visionflow::param::QRCParameters, visionflow::param::RegularExpression, visionflow::param::RotateRectParameters, visionflow::param::SchemableParameter, visionflow::param::ScoreFuncParameters, visionflow::param::SegmentationImageSplit, visionflow::param::SegmentationInputShape, visionflow::param::SegmentationModelParameters, visionflow::param::SegmentationTrainingSampleStrategy, visionflow::param::SetGeometrySearchDownSampleRatioManually, visionflow::param::SetGeometrySearchFeatChainMagRelativeThreshManually, visionflow::param::SetGeometrySearchGranularityManually, visionflow::param::SetGeometrySearchNoiseThreshManually, visionflow::param::SideLengthRange, visionflow::param::SingleClassPolygonsFilterParameters, visionflow::param::TypeValuePair, visionflow::param::UnsuperClassificationInputShape, visionflow::param::UnsuperDefectRadius, visionflow::param::UnsuperSegmentationInputShape, visionflow::param::UnsuperSegmentationModelParameters, visionflow::param::UnsuperSegmentationSamplingParameters, visionflow::param::UpcaParameters, visionflow::param::UpceParameters, visionflow::param::WidthDiffNormFuncParameters

Public Functions

virtual const std::string &schema_str() const = 0#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const = 0#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

const void* The nlohmann::json object pointer

virtual visionflow::Buffer to_json() const = 0#

Serialize the parameter group to schema-validatable json string.

Returns:

visionflow::Buffer the schema-validatable json string.

virtual ISchemable &from_json(const visionflow::Buffer &json_str) = 0#

Deserialize the parameter group from schema-validatable json string.

See also

validate(const std::string &json_str, std::string *error_message = nullptr)

Parameters:

json_str[in] the schema-validatable json string.

Throws:
Returns:

ISchemable& the reference of the parameter.

bool validate(const visionflow::Buffer &json_str, std::string *error_message = nullptr) const#

Validate the parameter json string with json schema.

Parameters:
  • json_str[in] the json string.

  • error_message[out] the error message if the json string is invalid, otherwise empty.

Throws:

visionflow::excepts::InvalidJson – if the json string is invalid.

Returns:

bool true if the json string is valid, otherwise false.

SchemableParameter#

struct SchemableParameter : public virtual visionflow::param::ISchemable, public virtual visionflow::param::IParameter#

SchemableParameter feature interface for IParameter classes.

Subclassed by visionflow::param::AssemblyVerificationFilterParameters, visionflow::param::AssemblyVerificationTemplates, visionflow::param::AssemblyVerificationTrainingParameters, visionflow::param::BaseColor, visionflow::param::CaliperAnnularEdgeParameters, visionflow::param::CaliperDualEdgeParameters, visionflow::param::CaliperSingleEdgeParameters, visionflow::param::CameraCalibrationInferParameters, visionflow::param::CameraCalibrationPixelScale, visionflow::param::ClassificationTrainingParameters, visionflow::param::DetectionInferParameters, visionflow::param::DetectionTrainingParameters, visionflow::param::ELClassificationTrainingParameters, visionflow::param::ELOCRInferParameters, visionflow::param::ELOCRTrainingParameters, visionflow::param::ELUnsuperClassificationInferenceParameters, visionflow::param::ELUnsuperClassificationTrainingParameters, visionflow::param::ELUnsuperSegmentationInferParameters, visionflow::param::ELUnsuperSegmentationTrainingParameters, visionflow::param::ExampleAugments, visionflow::param::FeatureMapFilterParameters, visionflow::param::GeometrySearchInferParameters, visionflow::param::GeometrySearchTrainingParameters, visionflow::param::IDReaderDecoderParameters, visionflow::param::IDReaderLocationModelParameters, visionflow::param::ImageMean, visionflow::param::ImagePreprocessParametersListSet, visionflow::param::InferenceBatchSize, visionflow::param::InputImageParam, visionflow::param::IntegrationClassifyParameter, visionflow::param::LocationFilterParameters, visionflow::param::LocationTemplates, visionflow::param::LocationTrainingParameters, visionflow::param::OCRInferParameters, visionflow::param::OCRTemplates, visionflow::param::OCRTrainingParameters, visionflow::param::OCRUniversalModelParameters, visionflow::param::PolygonsFilterParameters, visionflow::param::PropertyObjectIdSet, visionflow::param::RegionCalculationParameter, visionflow::param::SampleRecommendationParameter, visionflow::param::SegmentationInferenceParameters, visionflow::param::SegmentationTrainingParameters, visionflow::param::TRTCalibParameters, visionflow::param::TrainingLog, visionflow::param::TrainingSetRecommendParameter, visionflow::param::UnsuperClassificationInferenceParameters, visionflow::param::UnsuperClassificationTrainingParameters, visionflow::param::UnsuperSegmentationInferenceParameters, visionflow::param::UnsuperSegmentationTrainingParameters, visionflow::param::ViewFilterParameters

Customize Parameters#

class BinaryPacks : public visionflow::param::IParameter#

Parameter to store list of binary data with name.

Public Functions

void insert(const std::string &key, const visionflow::Buffer &buffer)#

Insert a new binary data into the BinaryPacks. Old data with the same key will be replaced.

See also

get(const std::string &key)

Note

The data in the buffer will not be copied, Which means that if you modify the data content in the Buffer later, the data in the inserted Buffer will also be modified. If this is not the behavior you expect, you can call visionflow::Buffer::clone_data() explicitly like below:

binary_packs.insert("my-data", buffer.clone_data());

Parameters:
  • key – The key of the binary data.

  • buffer – The binary data.

void remove(const std::string &key)#

Remove binary data specified by the key. Do nothing if the key not found.

Parameters:

key – The key of the binary data to be removed.

bool contains(const std::string &key) const#

Check if the binary data exists in the container.

Parameters:

key – The key of the binary data

Returns:

True if exists. Else false.

const visionflow::Buffer &get(const std::string &key) const#

Get the binary data specified by the key.

Note

Do not modify the data in the buffer with out clone,

Parameters:

key

Returns:

const visionflow::Buffer & The reference of the binary data.

std::vector<std::string> keys() const#

Get all keys in the BinaryPacks.

Returns:

std::vector<std::string> The keys list.

void clear()#

Clear the container.

class TypeValuePair : public visionflow::param::ISchemable#

TypeValuePair Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

const std::string &get_type() const#

Get The python type.

A string representing the type of the python object.

See also

set_type()

Returns:

const std::string & The python type

TypeValuePair &set_type(std::string type)#

Set The python type with std::string value.

A string representing the type of the python object.

See also

get_type()

Parameters:

type – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

TypeValuePair the reference of this object.

const std::string &get_value() const#

Get The python value.

A string representing the value of the python object.

See also

set_value()

Returns:

const std::string & The python value

TypeValuePair &set_value(std::string value)#

Set The python value with std::string value.

A string representing the value of the python object.

See also

get_value()

Parameters:

value – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

TypeValuePair the reference of this object.

class ObjectTypeValue#

Public Functions

ObjectTypeValue()#

Default constructor. Set type to “string” and value to “”.

const std::string &get_type() const#

Get The python type.

A string representing the type of the python object.

See also

set_type()

Returns:

const std::string & The python type

ObjectTypeValue &set_type(const std::string &type)#

Set The python type with std::string value.

A string representing the type of the python object.

See also

get_type()

Parameters:

type – the value to set. Should be one of “bool”, “number”, “string”

Throws:

visionflow::excepts::InvalidArgument – if type is not one of “bool”, “number”, “string”.

Returns:

ObjectTypeValue& the reference of this object.

const std::string &get_value() const#

Get The python value.

A string representing the value of the python object.

See also

set_value()

Returns:

const std::string & The python value

ObjectTypeValue &set_value(const std::string &value)#

Set The python value with std::string value.

A string representing the value of the python object.

See also

get_value()

Parameters:

value – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ObjectTypeValue& the reference of this object.

InputImage Parameters#

enum visionflow::param::ColorType#

Values:

enumerator kGray = 1#
enumerator kBGR = 3#
class BaseColor : public visionflow::param::SchemableParameter#

BaseColor Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

const ColorType &get_color() const#

Get Color Space.

Convert all images into Gray or BGR color space

See also

set_color()

Returns:

const ColorType & Color Space

BaseColor &set_color(ColorType color)#

Set Color Space with ColorType value.

Convert all images into Gray or BGR color space

See also

get_color()

Parameters:

color – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

BaseColor the reference of this object.

class ImageMean : public visionflow::param::SchemableParameter#

ImageMean Parameter class generated by jinja2 automatically.

Image mean parameters

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

const std::vector<double> &get_values() const#

Get image mean.

image mean values ordered same as image channels

See also

set_values()

Returns:

const std::vector<double> & image mean

ImageMean &set_values(std::vector<double> values)#

Set image mean with std::vector<double> value.

image mean values ordered same as image channels

See also

get_values()

Parameters:

values – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImageMean the reference of this object.

double get_values(size_t index) const#

Get value in image mean with index.

Warning

The index must be less than get_values_size(). otherwise, the behavior is undefined and will cause segmentation fault.

Returns:

double value in image mean at index.

size_t get_values_size() const#

Get the size of image mean.

Returns:

size_t the size of image mean

class InputImageParam : public visionflow::param::SchemableParameter#

InputImageParam Parameter class generated by jinja2 automatically.

输入图像相关参数,用于控制工程的输入图像格式规范.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

int get_visual_size() const#

Get Visual Image Size.

一个visionflow.Image允许包含的可视图象数量, 多数情况下, 使用默认值1即可。若需要将多张图像当作一张图像处理, 可以设置为大于1的值。

Returns:

int Visual Image Size

InputImageParam &set_visual_size(int visual_size)#

Set Visual Image Size with int value.

一个visionflow.Image允许包含的可视图象数量, 多数情况下, 使用默认值1即可。若需要将多张图像当作一张图像处理, 可以设置为大于1的值。

Parameters:

visual_size – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

InputImageParam the reference of this object.

int get_thumbnail_image_size() const#

Get Thumbnail Size.

The maximum size of the long side of the thumbnail, the longest side is 512 by default, the maximum can not exceed 512.

Returns:

int Thumbnail Size

InputImageParam &set_thumbnail_image_size(int thumbnail_image_size)#

Set Thumbnail Size with int value.

The maximum size of the long side of the thumbnail, the longest side is 512 by default, the maximum can not exceed 512.

Parameters:

thumbnail_image_size – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

InputImageParam the reference of this object.

class LabelClasses : public visionflow::param::IParameter#

LabelClasses is a parameter to manage label classes.

Public Functions

void add(const std::string &label_name)#

Add a label name into the label classes container.

Parameters:

label_name – The label name to be added.

void remove(const std::string &label_name)#

Remove a label name from the label classes container.

Parameters:

label_name – The label name to be removed.

size_t size() const#

Get the number of label classes.

Returns:

The number of label classes.

inline bool empty() const#

Check if the container is empty.

Returns:

bool True if the container is empty.

bool contains(const std::string &label_name) const#

Check if the label classes container contains the label name.

Parameters:

label_name – The label name to be checked.

Returns:

True if the label classes container contains the label name.

std::vector<std::string> get() const#

Get all label names in the label classes container as a vector.

Returns:

std::vector<std::string> The label names in the label classes

void clear()#

Clear the label classes container.

EvaluationMetrics Parameters#

enum visionflow::param::MetricsEvaluationType#

Values:

enumerator kImage = 0#

evaluation metrics of all images.

enumerator kAllView = 1#

evaluation metrics of all views.

enumerator kTestView = 2#

evaluation metrics of all test set views.

enumerator kTrainView = 3#

evaluation metrics of all train set views.

enumerator kAllRegion = 4#

evaluation metrics of all regions.

enumerator kTestRegion = 5#

evaluation metrics of all test set regions.

enumerator kTrainRegion = 6#

evaluation metrics of all train set regions.

enumerator kAllPixel = 7#

evaluation metrics of all pixels.

enumerator kTestPixel = 8#

evaluation metrics of all test set pixels.

enumerator kTrainPixel = 9#

evaluation metrics of all train set pixels.

enum visionflow::param::PrecisionEvaluationType#

Values:

enumerator kAngle = 0#

Precision evaluation of angle.

enumerator kPosition = 1#

Precision evaluationfor of position.

class Table#

Public Functions

size_t rows() const#

The number of rows.

Returns:

size_t

size_t cols() const#

The number of columns.

Returns:

size_t

const std::vector<std::string> &row_header() const#

Get the row header.

Returns:

std::vector<std::string> The row header.

const std::vector<std::string> &col_header() const#

Get the column header.

Returns:

std::vector<std::string> The column header.

std::vector<int> row_data(size_t row) const#

Get the data of one row.

Parameters:

row – The index of rows.

Throws:

excepts::DataNotFound – If no such the row.

Returns:

std::vector<int> The data of one row.

std::vector<int> col_data(size_t col) const#

Get the data of one column.

Parameters:

col – The index of columns.

Throws:

excepts::DataNotFound – If no such the column.

Returns:

std::vector<int> The data of one column.

int data(size_t row, size_t col) const#

Get the data of the specific position in the table.

Parameters:
  • row – The index of rows.

  • col – The index of columns.

Throws:

excepts::DataNotFound – If no such the row or column.

Returns:

int

int &data(size_t row, size_t col)#

Get the reference of the data of the specific position in the table.

Parameters:
  • row – The index of rows.

  • col – The index of columns.

Throws:

excepts::DataNotFound – If no such the row or column.

Returns:

NO_DISCARD&

Table &reset_header(const std::vector<std::string> &row_header, const std::vector<std::string> &col_header)#

Reset the header of the table.

Note

If no header is set at construction time,then the first task is to reset header. The number of rows and columns of this matrix will be initialized by the length of the row and column header. If the header has been set before, the reset header will clear the previous data, please be careful.

Parameters:
  • row_header – The header of row.

  • col_header – The header of column.

Returns:

Table&

Table &set_row_data(size_t row, const std::vector<int> &data)#

Set the data of one row.

Parameters:
  • row – The index of rows.

  • data

Throws:
Returns:

Table&

Table &set_col_data(size_t col, const std::vector<int> &data)#

Set the data of one column.

Parameters:
  • col – The index of columns.

  • data

Throws:
Returns:

Table&

Table &set_data(size_t row, size_t col, int data)#

Set the data of the specific position in the table.

Parameters:
  • row – The index of rows.

  • col – The index of columns.

  • data

Throws:

excepts::DataNotFound – If no such the row or column.

Returns:

Table&

class DataMetrics#

Public Functions

float maximum() const#

Get the maximum.

Returns:

NO_DISCARD

float minimum() const#

Get the minimum.

Returns:

NO_DISCARD

float average() const#

Get the average.

Returns:

NO_DISCARD

float standard_deviation() const#

Get the standard deviation.

Returns:

NO_DISCARD

DataMetrics &set_maximum(float value)#

Set the maximum.

Parameters:

value

Returns:

DataMetrics&

DataMetrics &set_minimum(float value)#

Set the minimum.

Parameters:

value

Returns:

DataMetrics&

DataMetrics &set_average(float value)#

Set the average.

Parameters:

value

Returns:

DataMetrics&

DataMetrics &set_standard_deviation(float value)#

Set the standard deviation.

Parameters:

value

Returns:

DataMetrics&

class AveragePrecision#

Public Functions

AveragePrecision &set_average_precision(const std::string &key, float average_precision)#

Set the specified average precision.

Parameters:
  • key

  • average_precision

float average_precision(const std::string &key) const#

Get the specified average precision.

Parameters:

key

Returns:

NO_DISCARD

float mean_average_precision() const#

Get the mean average precision.

Returns:

NO_DISCARD

std::vector<std::string> keys() const#

Get the keys.

Returns:

NO_DISCARD const&

float precision() const#

Get the precision.

Note

Returns -1, if there is no precision property.

Returns:

NO_DISCARD

float recall() const#

Get the recall.

Note

Returns -1, if there is no recall property.

Returns:

NO_DISCARD

AveragePrecision &set_precision(float precision)#

Set the precision.

Parameters:

precision

Returns:

AveragePrecision&

AveragePrecision &set_recall(float recall)#

Set the recall.

Parameters:

recall

Returns:

AveragePrecision&

struct IPrecisionEvaluation : public virtual visionflow::param::IParameter#

IPrecisionEvaluation feature interface for IParameter classes.

Subclassed by visionflow::param::LocationModelEvaluationMetrics

Public Functions

virtual std::set<PrecisionEvaluationType> precision_evaluation_keys() const = 0#

Get the types of precision evaluation in this map.

Returns:

std::set<PrecisionEvaluationType>

virtual const DataMetrics &precision_evaluation(PrecisionEvaluationType type) const = 0#

Get the precision evaluation with the type.

Parameters:

type

Returns:

NO_DISCARD

virtual DataMetrics &precision_evaluation(PrecisionEvaluationType type) = 0#

Get the reference precision evaluation with the type.

Parameters:

type

Returns:

NO_DISCARD

virtual IPrecisionEvaluation &set_precision_evaluation(PrecisionEvaluationType type, const DataMetrics &data_metrics) = 0#

Set the precision evaluation with the type.

Parameters:
  • type

  • data_metrics

Returns:

IPrecisionEvaluation&

struct ITableList : public virtual visionflow::param::IParameter#

ITableList feature interface for IParameter classes.

Subclassed by visionflow::param::LocationModelEvaluationMetrics, visionflow::param::ModelEvaluationMetrics

Public Functions

virtual std::vector<MetricsEvaluationType> table_keys() const = 0#

Get the types of table in this map.

Returns:

std::vector<MetricsEvaluationType>

virtual const Table &table(MetricsEvaluationType type) const = 0#

Get the table with the type.

Parameters:

type

Returns:

NO_DISCARD

virtual Table &table(MetricsEvaluationType type) = 0#

Get the reference table with the type.

Parameters:

type

Returns:

NO_DISCARD

virtual ITableList &set_table(MetricsEvaluationType type, const Table &table) = 0#

Set the table.

Parameters:
  • type

  • table

Returns:

ITableList&

struct IAveragePrecisionList : public virtual visionflow::param::IParameter#

IAveragePrecisionList feature interface for IParameter classes.

Subclassed by visionflow::param::LocationModelEvaluationMetrics, visionflow::param::ModelEvaluationMetrics

Public Functions

virtual std::vector<MetricsEvaluationType> average_precision_keys() const = 0#

Get the types of average_precision in this map.

Returns:

std::vector<MetricsEvaluationType>

virtual const AveragePrecision &average_precision(MetricsEvaluationType type) const = 0#

Get the average precision with the type.

Parameters:

type

Returns:

NO_DISCARD

virtual AveragePrecision &average_precision(MetricsEvaluationType type) = 0#

Get the reference average precision with the type.

Parameters:

type

Returns:

NO_DISCARD

virtual IAveragePrecisionList &set_average_precision(MetricsEvaluationType type, const AveragePrecision &average_precision) = 0#

Set the average precision.

Parameters:
  • type

  • average_precision

Returns:

IAveragePrecisionList&

class ModelEvaluationMetrics : public virtual visionflow::param::ITableList, public virtual visionflow::param::IAveragePrecisionList#

Public Functions

virtual std::vector<MetricsEvaluationType> table_keys() const override#

Get the types of table in this map.

Returns:

std::vector<MetricsEvaluationType>

virtual const Table &table(MetricsEvaluationType type) const override#

Get the table with the type.

Parameters:

type

Throws:

excepts::DataNotFound – The table with the type does not exist.

Returns:

NO_DISCARD

virtual Table &table(MetricsEvaluationType type) override#

Get the reference table with the type.

Parameters:

type

Throws:

excepts::DataNotFound – The table with the type does not exist.

Returns:

NO_DISCARD

virtual ModelEvaluationMetrics &set_table(MetricsEvaluationType type, const Table &table) override#

Set the table.

Parameters:
  • type

  • table

Returns:

ITableList&

virtual std::vector<MetricsEvaluationType> average_precision_keys() const override#

Get the types of average_precision in this map.

Returns:

std::vector<MetricsEvaluationType>

virtual const AveragePrecision &average_precision(MetricsEvaluationType type) const override#

Get the average precision with the type.

Parameters:

type

Throws:

excepts::DataNotFound – The average precision with the type does not exist.

Returns:

NO_DISCARD

virtual AveragePrecision &average_precision(MetricsEvaluationType type) override#

Get the reference average precision with the type.

Parameters:

type

Throws:

excepts::DataNotFound – The average precision with the type does not exist.

Returns:

NO_DISCARD

virtual ModelEvaluationMetrics &set_average_precision(MetricsEvaluationType type, const AveragePrecision &average_precision) override#

Set the average precision.

Parameters:
  • type

  • average_precision

Returns:

IAveragePrecisionList&

class LocationModelEvaluationMetrics : public virtual visionflow::param::ITableList, public virtual visionflow::param::IPrecisionEvaluation, public virtual visionflow::param::IAveragePrecisionList#

Public Functions

virtual std::vector<MetricsEvaluationType> table_keys() const override#

Get the types of table in this map.

Returns:

std::vector<MetricsEvaluationType>

virtual const Table &table(MetricsEvaluationType type) const override#

Get the table with the type.

Parameters:

type

Throws:

excepts::DataNotFound – The table with the type does not exist.

Returns:

NO_DISCARD

virtual Table &table(MetricsEvaluationType type) override#

Get the reference table with the type.

Parameters:

type

Throws:

excepts::DataNotFound – The table with the type does not exist.

Returns:

NO_DISCARD

virtual LocationModelEvaluationMetrics &set_table(MetricsEvaluationType type, const Table &table) override#

Set the table.

Parameters:
  • type

  • table

Returns:

ITableList&

virtual std::set<PrecisionEvaluationType> precision_evaluation_keys() const override#

Get the types of precision evaluation in this map.

Returns:

std::set<PrecisionEvaluationType>

virtual const DataMetrics &precision_evaluation(PrecisionEvaluationType type) const override#

Get the precision evaluation with the type.

Parameters:

type

Throws:

excepts::DataNotFound – The precision evaluation with the type does not exist.

Returns:

NO_DISCARD

virtual DataMetrics &precision_evaluation(PrecisionEvaluationType type) override#

Get the reference precision evaluation with the type.

Parameters:

type

Throws:

excepts::DataNotFound – The precision evaluation with the type does not exist.

Returns:

NO_DISCARD

virtual LocationModelEvaluationMetrics &set_precision_evaluation(PrecisionEvaluationType type, const DataMetrics &data_metrics) override#

Set the precision evaluation with the type.

Parameters:
  • type

  • data_metrics

Returns:

LocationModelEvaluationMetrics&

virtual std::vector<MetricsEvaluationType> average_precision_keys() const override#

Get the types of average_precision in this map.

Returns:

std::vector<MetricsEvaluationType>

virtual const AveragePrecision &average_precision(MetricsEvaluationType type) const override#

Get the average precision with the type.

Parameters:

type

Throws:

excepts::DataNotFound – The average precision with the type does not exist.

Returns:

NO_DISCARD

virtual AveragePrecision &average_precision(MetricsEvaluationType type) override#

Get the reference average precision with the type.

Parameters:

type

Throws:

excepts::DataNotFound – The average precision with the type does not exist.

Returns:

NO_DISCARD

virtual LocationModelEvaluationMetrics &set_average_precision(MetricsEvaluationType type, const AveragePrecision &average_precision) override#

Set the average precision.

Parameters:
  • type

  • average_precision

Returns:

IAveragePrecisionList&

class ModelHealth : public visionflow::param::IParameter#

Model health.

DataAugmentation Parameters#

class GeoAugSlightRotation : public visionflow::param::ISchemable#

GeoAugSlightRotation Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

bool get_enable() const#

Get Enable.

Enable this parameter group.

See also

set_enable()

Returns:

bool Enable

GeoAugSlightRotation &set_enable(bool enable)#

Set Enable with bool value.

Enable this parameter group.

See also

get_enable()

Parameters:

enable – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

GeoAugSlightRotation the reference of this object.

const std::vector<double> &get_range() const#

Get Angle Range.

Slight rotation angle range (min, max)

See also

set_range()

Returns:

const std::vector<double> & Angle Range

GeoAugSlightRotation &set_range(std::vector<double> range)#

Set Angle Range with std::vector<double> value.

Slight rotation angle range (min, max)

See also

get_range()

Parameters:

range – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

GeoAugSlightRotation the reference of this object.

bool range_contains(double value) const#

Check if the Angle Range contains the value.

Returns:

bool true if the Angle Range contains the value, otherwise false.

double get_range_left() const#

Get left point value of Angle Range.

Returns:

const std::vector<double> & left point value of Angle Range

double get_range_right() const#

Get the right point value of Angle Range.

See also

set_range_left()

Returns:

const std::vector<double> & the right point value of Angle Range

GeoAugSlightRotation &set_range_left(double range_left)#

Set left point value of Angle Range with std::vector<double> value.

Slight rotation angle range (min, max)

See also

get_range_left()

Parameters:

range_left – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

GeoAugSlightRotation the reference of this object.

GeoAugSlightRotation &set_range_right(double range_right)#

Set the right point value of Angle Range with std::vector<double> value.

Slight rotation angle range (min, max)

Parameters:

range_right – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

GeoAugSlightRotation the reference of this object.

int get_step() const#

Get Angle Step.

Slight rotation angle step

See also

set_step()

Returns:

int Angle Step

GeoAugSlightRotation &set_step(int step)#

Set Angle Step with int value.

Slight rotation angle step

See also

get_step()

Parameters:

step – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

GeoAugSlightRotation the reference of this object.

class GeoAugShift : public visionflow::param::ISchemable#

GeoAugShift Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

bool get_enable() const#

Get Enable.

Enable this parameter group.

See also

set_enable()

Returns:

bool Enable

GeoAugShift &set_enable(bool enable)#

Set Enable with bool value.

Enable this parameter group.

See also

get_enable()

Parameters:

enable – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

GeoAugShift the reference of this object.

double get_shift_vertical() const#

Get Vertical Shift.

Vertical shift

Returns:

double Vertical Shift

GeoAugShift &set_shift_vertical(double shift_vertical)#

Set Vertical Shift with double value.

Vertical shift

Parameters:

shift_vertical – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

GeoAugShift the reference of this object.

double get_shift_horizontal() const#

Get Horizontal Shift.

Horizontal shift

Returns:

double Horizontal Shift

GeoAugShift &set_shift_horizontal(double shift_horizontal)#

Set Horizontal Shift with double value.

Horizontal shift

Parameters:

shift_horizontal – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

GeoAugShift the reference of this object.

class GeoAugScale : public visionflow::param::ISchemable#

GeoAugScale Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

bool get_enable() const#

Get Enable.

Enable this parameter group.

See also

set_enable()

Returns:

bool Enable

GeoAugScale &set_enable(bool enable)#

Set Enable with bool value.

Enable this parameter group.

See also

get_enable()

Parameters:

enable – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

GeoAugScale the reference of this object.

const std::vector<double> &get_range() const#

Get Scale Range.

Scale range (min, max)

See also

set_range()

Returns:

const std::vector<double> & Scale Range

GeoAugScale &set_range(std::vector<double> range)#

Set Scale Range with std::vector<double> value.

Scale range (min, max)

See also

get_range()

Parameters:

range – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

GeoAugScale the reference of this object.

bool range_contains(double value) const#

Check if the Scale Range contains the value.

Returns:

bool true if the Scale Range contains the value, otherwise false.

double get_range_left() const#

Get left point value of Scale Range.

Returns:

const std::vector<double> & left point value of Scale Range

double get_range_right() const#

Get the right point value of Scale Range.

See also

set_range_left()

Returns:

const std::vector<double> & the right point value of Scale Range

GeoAugScale &set_range_left(double range_left)#

Set left point value of Scale Range with std::vector<double> value.

Scale range (min, max)

See also

get_range_left()

Parameters:

range_left – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

GeoAugScale the reference of this object.

GeoAugScale &set_range_right(double range_right)#

Set the right point value of Scale Range with std::vector<double> value.

Scale range (min, max)

Parameters:

range_right – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

GeoAugScale the reference of this object.

class CategoryAreaAugment : public visionflow::param::ISchemable#

CategoryAreaAugment Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

bool get_enable() const#

Get Enable.

Enable this parameter group.

See also

set_enable()

Returns:

bool Enable

CategoryAreaAugment &set_enable(bool enable)#

Set Enable with bool value.

Enable this parameter group.

See also

get_enable()

Parameters:

enable – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

CategoryAreaAugment the reference of this object.

const std::vector<double> &get_range() const#

Get Label Augment Scale Range.

Label will be scale according to range

See also

set_range()

Returns:

const std::vector<double> & Label Augment Scale Range

CategoryAreaAugment &set_range(std::vector<double> range)#

Set Label Augment Scale Range with std::vector<double> value.

Label will be scale according to range

See also

get_range()

Parameters:

range – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

CategoryAreaAugment the reference of this object.

bool range_contains(double value) const#

Check if the Label Augment Scale Range contains the value.

Returns:

bool true if the Label Augment Scale Range contains the value, otherwise false.

double get_range_left() const#

Get left point value of Label Augment Scale Range.

Returns:

const std::vector<double> & left point value of Label Augment Scale Range

double get_range_right() const#

Get the right point value of Label Augment Scale Range.

See also

set_range_left()

Returns:

const std::vector<double> & the right point value of Label Augment Scale Range

CategoryAreaAugment &set_range_left(double range_left)#

Set left point value of Label Augment Scale Range with std::vector<double> value.

Label will be scale according to range

See also

get_range_left()

Parameters:

range_left – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

CategoryAreaAugment the reference of this object.

CategoryAreaAugment &set_range_right(double range_right)#

Set the right point value of Label Augment Scale Range with std::vector<double> value.

Label will be scale according to range

Parameters:

range_right – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

CategoryAreaAugment the reference of this object.

class GeoAugDistortion : public visionflow::param::ISchemable#

GeoAugDistortion Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

bool get_enable() const#

Get Enable.

Enable this parameter group.

See also

set_enable()

Returns:

bool Enable

GeoAugDistortion &set_enable(bool enable)#

Set Enable with bool value.

Enable this parameter group.

See also

get_enable()

Parameters:

enable – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

GeoAugDistortion the reference of this object.

const std::vector<double> &get_range() const#

Get Distortion Strength Range.

Distortion Strength range, From 0 to 2, the distortion effect gradually increases

See also

set_range()

Returns:

const std::vector<double> & Distortion Strength Range

GeoAugDistortion &set_range(std::vector<double> range)#

Set Distortion Strength Range with std::vector<double> value.

Distortion Strength range, From 0 to 2, the distortion effect gradually increases

See also

get_range()

Parameters:

range – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

GeoAugDistortion the reference of this object.

bool range_contains(double value) const#

Check if the Distortion Strength Range contains the value.

Returns:

bool true if the Distortion Strength Range contains the value, otherwise false.

double get_range_left() const#

Get left point value of Distortion Strength Range.

Returns:

const std::vector<double> & left point value of Distortion Strength Range

double get_range_right() const#

Get the right point value of Distortion Strength Range.

See also

set_range_left()

Returns:

const std::vector<double> & the right point value of Distortion Strength Range

GeoAugDistortion &set_range_left(double range_left)#

Set left point value of Distortion Strength Range with std::vector<double> value.

Distortion Strength range, From 0 to 2, the distortion effect gradually increases

See also

get_range_left()

Parameters:

range_left – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

GeoAugDistortion the reference of this object.

GeoAugDistortion &set_range_right(double range_right)#

Set the right point value of Distortion Strength Range with std::vector<double> value.

Distortion Strength range, From 0 to 2, the distortion effect gradually increases

Parameters:

range_right – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

GeoAugDistortion the reference of this object.

class GeometryAugmentation : public visionflow::param::ISchemable#

GeometryAugmentation Parameter class generated by jinja2 automatically.

Geometry augmentation parameters

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

bool get_flip_vertical() const#

Get Vertical Flip.

Flip training images vertically randomly with a probability of 0.5

Returns:

bool Vertical Flip

GeometryAugmentation &set_flip_vertical(bool flip_vertical)#

Set Vertical Flip with bool value.

Flip training images vertically randomly with a probability of 0.5

Parameters:

flip_vertical – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

GeometryAugmentation the reference of this object.

bool get_flip_horizontal() const#

Get Horizontal Flip.

Flip training images horizontally randomly with a probability of 0.5

Returns:

bool Horizontal Flip

GeometryAugmentation &set_flip_horizontal(bool flip_horizontal)#

Set Horizontal Flip with bool value.

Flip training images horizontally randomly with a probability of 0.5

Parameters:

flip_horizontal – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

GeometryAugmentation the reference of this object.

bool get_rotate_90() const#

Get Vertical Rotation.

Rotate the training image by a multiple of 90 degrees at random

See also

set_rotate_90()

Returns:

bool Vertical Rotation

GeometryAugmentation &set_rotate_90(bool rotate_90)#

Set Vertical Rotation with bool value.

Rotate the training image by a multiple of 90 degrees at random

See also

get_rotate_90()

Parameters:

rotate_90 – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

GeometryAugmentation the reference of this object.

bool get_rotate_180() const#

Get Centrosymmetric Rotation.

Rotate the training image by a multiple of 180 degrees at random

See also

set_rotate_180()

Returns:

bool Centrosymmetric Rotation

GeometryAugmentation &set_rotate_180(bool rotate_180)#

Set Centrosymmetric Rotation with bool value.

Rotate the training image by a multiple of 180 degrees at random

See also

get_rotate_180()

Parameters:

rotate_180 – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

GeometryAugmentation the reference of this object.

const GeoAugSlightRotation &get_slight_rotate() const#

Get Slight Rotation.

Randomly rotate the training data slightly in a certain angle range

Returns:

const GeoAugSlightRotation & Slight Rotation

GeometryAugmentation &set_slight_rotate(GeoAugSlightRotation slight_rotate)#

Set Slight Rotation with GeoAugSlightRotation value.

Randomly rotate the training data slightly in a certain angle range

Parameters:

slight_rotate – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

GeometryAugmentation the reference of this object.

GeoAugSlightRotation &get_slight_rotate()#

Get mutable reference of Slight Rotation.

Randomly rotate the training data slightly in a certain angle range

Returns:

GeometryAugmentation& the mutable reference of the group.

const GeoAugShift &get_shift() const#

Get Shift.

Randomly shift the training data horizontally and vertically by a certain proportion

See also

set_shift()

Returns:

const GeoAugShift & Shift

GeometryAugmentation &set_shift(GeoAugShift shift)#

Set Shift with GeoAugShift value.

Randomly shift the training data horizontally and vertically by a certain proportion

See also

get_shift()

Parameters:

shift – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

GeometryAugmentation the reference of this object.

GeoAugShift &get_shift()#

Get mutable reference of Shift.

Randomly shift the training data horizontally and vertically by a certain proportion

Returns:

GeometryAugmentation& the mutable reference of the group.

const GeoAugScale &get_scale() const#

Get Scale.

Randomly scale the training data by a certain proportion

See also

set_scale()

Returns:

const GeoAugScale & Scale

GeometryAugmentation &set_scale(GeoAugScale scale)#

Set Scale with GeoAugScale value.

Randomly scale the training data by a certain proportion

See also

get_scale()

Parameters:

scale – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

GeometryAugmentation the reference of this object.

GeoAugScale &get_scale()#

Get mutable reference of Scale.

Randomly scale the training data by a certain proportion

Returns:

GeometryAugmentation& the mutable reference of the group.

const GeoAugDistortion &get_distortion() const#

Get Distortion.

Randomly distort the training data to simulate image distortion caused by factors such as lens aging.

See also

set_distortion()

Returns:

const GeoAugDistortion & Distortion

GeometryAugmentation &set_distortion(GeoAugDistortion distortion)#

Set Distortion with GeoAugDistortion value.

Randomly distort the training data to simulate image distortion caused by factors such as lens aging.

See also

get_distortion()

Parameters:

distortion – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

GeometryAugmentation the reference of this object.

GeoAugDistortion &get_distortion()#

Get mutable reference of Distortion.

Randomly distort the training data to simulate image distortion caused by factors such as lens aging.

Returns:

GeometryAugmentation& the mutable reference of the group.

bool get_crop() const#

Get Crop Overflow Area.

Crop out spill areas caused by geometric transformations (translation, rotation) to keep the image size unchanged

See also

set_crop()

Returns:

bool Crop Overflow Area

GeometryAugmentation &set_crop(bool crop)#

Set Crop Overflow Area with bool value.

Crop out spill areas caused by geometric transformations (translation, rotation) to keep the image size unchanged

See also

get_crop()

Parameters:

crop – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

GeometryAugmentation the reference of this object.

class LabeledGeometryAugmentation : public visionflow::param::ISchemable#

LabeledGeometryAugmentation Parameter class generated by jinja2 automatically.

Defect geometry augmentation parameters

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

const std::map<std::string, CategoryAreaAugment> &get_scale() const#

Get LabeledScale.

There is an area difference between the target defect and the training set But no obviously texture difference.

See also

set_scale()

Returns:

const std::map<std::string, CategoryAreaAugment> & LabeledScale

LabeledGeometryAugmentation &set_scale(std::map<std::string, CategoryAreaAugment> scale)#

Set LabeledScale with std::map<std::string, CategoryAreaAugment> value.

There is an area difference between the target defect and the training set But no obviously texture difference.

See also

get_scale()

Parameters:

scale – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

LabeledGeometryAugmentation the reference of this object.

const CategoryAreaAugment &get_scale(const std::string &key) const#

Get value in LabeledScale with key.

Warning

The key must be exist in LabeledScale. otherwise, the behavior is undefined and will cause segmentation fault.

Returns:

const std::map<std::string, CategoryAreaAugment> & value in LabeledScale at key.

LabeledGeometryAugmentation &set_scale(const std::string &key, CategoryAreaAugment value)#

Set value in LabeledScale with key.

Parameters:
  • key – the key to set.

  • value – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

LabeledGeometryAugmentation the reference of this object.

bool scale_contains(const std::string &key) const#

Check if the key is exist in LabeledScale.

Returns:

bool true if the key is exist in LabeledScale, otherwise false.

size_t get_scale_size() const#

Get the size of LabeledScale.

Returns:

size_t the size of LabeledScale

CategoryAreaAugment &get_scale(const std::string &key)#

Get mutable reference of value in LabeledScale with key. A new key and default value will be created if the key does not exist.

Returns:

CategoryAreaAugment& the mutable reference of value in LabeledScale at key.

class DefectSimulation : public visionflow::param::ISchemable#

DefectSimulation Parameter class generated by jinja2 automatically.

Defect simulation parameters

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

bool get_scale_enable() const#

Get Defect Scale Simulation.

Scale the defect to possible sizes to accommodate changes in defect size

Returns:

bool Defect Scale Simulation

DefectSimulation &set_scale_enable(bool scale_enable)#

Set Defect Scale Simulation with bool value.

Scale the defect to possible sizes to accommodate changes in defect size

Parameters:

scale_enable – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

DefectSimulation the reference of this object.

class ImageAugBrightness : public visionflow::param::ISchemable#

ImageAugBrightness Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

bool get_enable() const#

Get Enable.

Enable this parameter group.

See also

set_enable()

Returns:

bool Enable

ImageAugBrightness &set_enable(bool enable)#

Set Enable with bool value.

Enable this parameter group.

See also

get_enable()

Parameters:

enable – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImageAugBrightness the reference of this object.

const std::vector<double> &get_range() const#

Get Brightness Range.

The illumination intensity range 0~1 for reduction, and 1~2 for enhancement.

See also

set_range()

Returns:

const std::vector<double> & Brightness Range

ImageAugBrightness &set_range(std::vector<double> range)#

Set Brightness Range with std::vector<double> value.

The illumination intensity range 0~1 for reduction, and 1~2 for enhancement.

See also

get_range()

Parameters:

range – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImageAugBrightness the reference of this object.

bool range_contains(double value) const#

Check if the Brightness Range contains the value.

Returns:

bool true if the Brightness Range contains the value, otherwise false.

double get_range_left() const#

Get left point value of Brightness Range.

Returns:

const std::vector<double> & left point value of Brightness Range

double get_range_right() const#

Get the right point value of Brightness Range.

See also

set_range_left()

Returns:

const std::vector<double> & the right point value of Brightness Range

ImageAugBrightness &set_range_left(double range_left)#

Set left point value of Brightness Range with std::vector<double> value.

The illumination intensity range 0~1 for reduction, and 1~2 for enhancement.

See also

get_range_left()

Parameters:

range_left – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImageAugBrightness the reference of this object.

ImageAugBrightness &set_range_right(double range_right)#

Set the right point value of Brightness Range with std::vector<double> value.

The illumination intensity range 0~1 for reduction, and 1~2 for enhancement.

Parameters:

range_right – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImageAugBrightness the reference of this object.

class ImageAugContrast : public visionflow::param::ISchemable#

ImageAugContrast Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

bool get_enable() const#

Get Enable.

Enable this parameter group.

See also

set_enable()

Returns:

bool Enable

ImageAugContrast &set_enable(bool enable)#

Set Enable with bool value.

Enable this parameter group.

See also

get_enable()

Parameters:

enable – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImageAugContrast the reference of this object.

const std::vector<double> &get_range() const#

Get Contrast Range.

The contrast range 0~1 for reduction, and 1~2 for enhancement.

See also

set_range()

Returns:

const std::vector<double> & Contrast Range

ImageAugContrast &set_range(std::vector<double> range)#

Set Contrast Range with std::vector<double> value.

The contrast range 0~1 for reduction, and 1~2 for enhancement.

See also

get_range()

Parameters:

range – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImageAugContrast the reference of this object.

bool range_contains(double value) const#

Check if the Contrast Range contains the value.

Returns:

bool true if the Contrast Range contains the value, otherwise false.

double get_range_left() const#

Get left point value of Contrast Range.

Returns:

const std::vector<double> & left point value of Contrast Range

double get_range_right() const#

Get the right point value of Contrast Range.

See also

set_range_left()

Returns:

const std::vector<double> & the right point value of Contrast Range

ImageAugContrast &set_range_left(double range_left)#

Set left point value of Contrast Range with std::vector<double> value.

The contrast range 0~1 for reduction, and 1~2 for enhancement.

See also

get_range_left()

Parameters:

range_left – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImageAugContrast the reference of this object.

ImageAugContrast &set_range_right(double range_right)#

Set the right point value of Contrast Range with std::vector<double> value.

The contrast range 0~1 for reduction, and 1~2 for enhancement.

Parameters:

range_right – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImageAugContrast the reference of this object.

class ImageAugColorFilter : public visionflow::param::ISchemable#

ImageAugColorFilter Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

bool get_enable() const#

Get Enable.

Enable this parameter group.

See also

set_enable()

Returns:

bool Enable

ImageAugColorFilter &set_enable(bool enable)#

Set Enable with bool value.

Enable this parameter group.

See also

get_enable()

Parameters:

enable – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImageAugColorFilter the reference of this object.

const std::vector<double> &get_range() const#

Get Color Filter Range.

Color Filter Range 0~2 from low to high.

See also

set_range()

Returns:

const std::vector<double> & Color Filter Range

ImageAugColorFilter &set_range(std::vector<double> range)#

Set Color Filter Range with std::vector<double> value.

Color Filter Range 0~2 from low to high.

See also

get_range()

Parameters:

range – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImageAugColorFilter the reference of this object.

bool range_contains(double value) const#

Check if the Color Filter Range contains the value.

Returns:

bool true if the Color Filter Range contains the value, otherwise false.

double get_range_left() const#

Get left point value of Color Filter Range.

Returns:

const std::vector<double> & left point value of Color Filter Range

double get_range_right() const#

Get the right point value of Color Filter Range.

See also

set_range_left()

Returns:

const std::vector<double> & the right point value of Color Filter Range

ImageAugColorFilter &set_range_left(double range_left)#

Set left point value of Color Filter Range with std::vector<double> value.

Color Filter Range 0~2 from low to high.

See also

get_range_left()

Parameters:

range_left – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImageAugColorFilter the reference of this object.

ImageAugColorFilter &set_range_right(double range_right)#

Set the right point value of Color Filter Range with std::vector<double> value.

Color Filter Range 0~2 from low to high.

Parameters:

range_right – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImageAugColorFilter the reference of this object.

class ImageAugNoise : public visionflow::param::ISchemable#

ImageAugNoise Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

bool get_enable() const#

Get Enable.

Enable this parameter group.

See also

set_enable()

Returns:

bool Enable

ImageAugNoise &set_enable(bool enable)#

Set Enable with bool value.

Enable this parameter group.

See also

get_enable()

Parameters:

enable – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImageAugNoise the reference of this object.

const std::vector<double> &get_range() const#

Get Noise Range.

Noise Range 0~2 from low to high.

See also

set_range()

Returns:

const std::vector<double> & Noise Range

ImageAugNoise &set_range(std::vector<double> range)#

Set Noise Range with std::vector<double> value.

Noise Range 0~2 from low to high.

See also

get_range()

Parameters:

range – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImageAugNoise the reference of this object.

bool range_contains(double value) const#

Check if the Noise Range contains the value.

Returns:

bool true if the Noise Range contains the value, otherwise false.

double get_range_left() const#

Get left point value of Noise Range.

Returns:

const std::vector<double> & left point value of Noise Range

double get_range_right() const#

Get the right point value of Noise Range.

See also

set_range_left()

Returns:

const std::vector<double> & the right point value of Noise Range

ImageAugNoise &set_range_left(double range_left)#

Set left point value of Noise Range with std::vector<double> value.

Noise Range 0~2 from low to high.

See also

get_range_left()

Parameters:

range_left – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImageAugNoise the reference of this object.

ImageAugNoise &set_range_right(double range_right)#

Set the right point value of Noise Range with std::vector<double> value.

Noise Range 0~2 from low to high.

Parameters:

range_right – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImageAugNoise the reference of this object.

class ImageAugIlluminationGradient : public visionflow::param::ISchemable#

ImageAugIlluminationGradient Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

bool get_enable() const#

Get Enable.

Enable this parameter group.

See also

set_enable()

Returns:

bool Enable

ImageAugIlluminationGradient &set_enable(bool enable)#

Set Enable with bool value.

Enable this parameter group.

See also

get_enable()

Parameters:

enable – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImageAugIlluminationGradient the reference of this object.

const std::vector<double> &get_range() const#

Get Illumination Gradient Range.

Illumination Gradient Range 0~2 from low to high.

See also

set_range()

Returns:

const std::vector<double> & Illumination Gradient Range

ImageAugIlluminationGradient &set_range(std::vector<double> range)#

Set Illumination Gradient Range with std::vector<double> value.

Illumination Gradient Range 0~2 from low to high.

See also

get_range()

Parameters:

range – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImageAugIlluminationGradient the reference of this object.

bool range_contains(double value) const#

Check if the Illumination Gradient Range contains the value.

Returns:

bool true if the Illumination Gradient Range contains the value, otherwise false.

double get_range_left() const#

Get left point value of Illumination Gradient Range.

Returns:

const std::vector<double> & left point value of Illumination Gradient Range

double get_range_right() const#

Get the right point value of Illumination Gradient Range.

See also

set_range_left()

Returns:

const std::vector<double> & the right point value of Illumination Gradient Range

ImageAugIlluminationGradient &set_range_left(double range_left)#

Set left point value of Illumination Gradient Range with std::vector<double> value.

Illumination Gradient Range 0~2 from low to high.

See also

get_range_left()

Parameters:

range_left – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImageAugIlluminationGradient the reference of this object.

ImageAugIlluminationGradient &set_range_right(double range_right)#

Set the right point value of Illumination Gradient Range with std::vector<double> value.

Illumination Gradient Range 0~2 from low to high.

Parameters:

range_right – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImageAugIlluminationGradient the reference of this object.

class ImageAugSmoothingOrSharpening : public visionflow::param::ISchemable#

ImageAugSmoothingOrSharpening Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

bool get_enable() const#

Get Enable.

Enable this parameter group.

See also

set_enable()

Returns:

bool Enable

ImageAugSmoothingOrSharpening &set_enable(bool enable)#

Set Enable with bool value.

Enable this parameter group.

See also

get_enable()

Parameters:

enable – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImageAugSmoothingOrSharpening the reference of this object.

const std::vector<double> &get_range() const#

Get Smoothing/Sharpening Range.

Randomly smooth or sharpen training images, where -1 to 0 indicates smoothing and 0 to 1 indicates sharpening.

See also

set_range()

Returns:

const std::vector<double> & Smoothing/Sharpening Range

ImageAugSmoothingOrSharpening &set_range(std::vector<double> range)#

Set Smoothing/Sharpening Range with std::vector<double> value.

Randomly smooth or sharpen training images, where -1 to 0 indicates smoothing and 0 to 1 indicates sharpening.

See also

get_range()

Parameters:

range – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImageAugSmoothingOrSharpening the reference of this object.

bool range_contains(double value) const#

Check if the Smoothing/Sharpening Range contains the value.

Returns:

bool true if the Smoothing/Sharpening Range contains the value, otherwise false.

double get_range_left() const#

Get left point value of Smoothing/Sharpening Range.

Returns:

const std::vector<double> & left point value of Smoothing/Sharpening Range

double get_range_right() const#

Get the right point value of Smoothing/Sharpening Range.

See also

set_range_left()

Returns:

const std::vector<double> & the right point value of Smoothing/Sharpening Range

ImageAugSmoothingOrSharpening &set_range_left(double range_left)#

Set left point value of Smoothing/Sharpening Range with std::vector<double> value.

Randomly smooth or sharpen training images, where -1 to 0 indicates smoothing and 0 to 1 indicates sharpening.

See also

get_range_left()

Parameters:

range_left – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImageAugSmoothingOrSharpening the reference of this object.

ImageAugSmoothingOrSharpening &set_range_right(double range_right)#

Set the right point value of Smoothing/Sharpening Range with std::vector<double> value.

Randomly smooth or sharpen training images, where -1 to 0 indicates smoothing and 0 to 1 indicates sharpening.

Parameters:

range_right – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImageAugSmoothingOrSharpening the reference of this object.

class ImageAugmentation : public visionflow::param::ISchemable#

ImageAugmentation Parameter class generated by jinja2 automatically.

Image Augmentation Parameters Group.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

const ImageAugBrightness &get_brightness() const#

Get Illumination Augmentation.

Augmenting training data with linear gray scale transformations

See also

set_brightness()

Returns:

const ImageAugBrightness & Illumination Augmentation

ImageAugmentation &set_brightness(ImageAugBrightness brightness)#

Set Illumination Augmentation with ImageAugBrightness value.

Augmenting training data with linear gray scale transformations

See also

get_brightness()

Parameters:

brightness – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImageAugmentation the reference of this object.

ImageAugBrightness &get_brightness()#

Get mutable reference of Illumination Augmentation.

Augmenting training data with linear gray scale transformations

Returns:

ImageAugmentation& the mutable reference of the group.

const ImageAugContrast &get_contrast() const#

Get Contrast Augmentation.

Augmenting training data by adjusting the contrast of the image while keeping the overall brightness of the image essentially unchanged to simulate the effect of different lighting conditions with different contrast.

See also

set_contrast()

Returns:

const ImageAugContrast & Contrast Augmentation

ImageAugmentation &set_contrast(ImageAugContrast contrast)#

Set Contrast Augmentation with ImageAugContrast value.

Augmenting training data by adjusting the contrast of the image while keeping the overall brightness of the image essentially unchanged to simulate the effect of different lighting conditions with different contrast.

See also

get_contrast()

Parameters:

contrast – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImageAugmentation the reference of this object.

ImageAugContrast &get_contrast()#

Get mutable reference of Contrast Augmentation.

Augmenting training data by adjusting the contrast of the image while keeping the overall brightness of the image essentially unchanged to simulate the effect of different lighting conditions with different contrast.

Returns:

ImageAugmentation& the mutable reference of the group.

const ImageAugNoise &get_noise() const#

Get Noise Augmentation.

Augmenting training data with adding gaussian noise to the image to simulate random noise generated by the camera or external environment.

See also

set_noise()

Returns:

const ImageAugNoise & Noise Augmentation

ImageAugmentation &set_noise(ImageAugNoise noise)#

Set Noise Augmentation with ImageAugNoise value.

Augmenting training data with adding gaussian noise to the image to simulate random noise generated by the camera or external environment.

See also

get_noise()

Parameters:

noise – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImageAugmentation the reference of this object.

ImageAugNoise &get_noise()#

Get mutable reference of Noise Augmentation.

Augmenting training data with adding gaussian noise to the image to simulate random noise generated by the camera or external environment.

Returns:

ImageAugmentation& the mutable reference of the group.

const ImageAugSmoothingOrSharpening &get_blur() const#

Get Smoothing/Sharpening.

Simulate scenes with inaccurate lens focus by smoothing or sharpening the image

See also

set_blur()

Returns:

const ImageAugSmoothingOrSharpening & Smoothing/Sharpening

ImageAugmentation &set_blur(ImageAugSmoothingOrSharpening blur)#

Set Smoothing/Sharpening with ImageAugSmoothingOrSharpening value.

Simulate scenes with inaccurate lens focus by smoothing or sharpening the image

See also

get_blur()

Parameters:

blur – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImageAugmentation the reference of this object.

ImageAugSmoothingOrSharpening &get_blur()#

Get mutable reference of Smoothing/Sharpening.

Simulate scenes with inaccurate lens focus by smoothing or sharpening the image

Returns:

ImageAugmentation& the mutable reference of the group.

const ImageAugColorFilter &get_color_filter() const#

Get Color Filter.

Simulate the different colors lighting effects by adding filters (only color images are supported), the color filter intensity controls the max intensity of the allowed color filters.

Returns:

const ImageAugColorFilter & Color Filter

ImageAugmentation &set_color_filter(ImageAugColorFilter color_filter)#

Set Color Filter with ImageAugColorFilter value.

Simulate the different colors lighting effects by adding filters (only color images are supported), the color filter intensity controls the max intensity of the allowed color filters.

Parameters:

color_filter – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImageAugmentation the reference of this object.

ImageAugColorFilter &get_color_filter()#

Get mutable reference of Color Filter.

Simulate the different colors lighting effects by adding filters (only color images are supported), the color filter intensity controls the max intensity of the allowed color filters.

Returns:

ImageAugmentation& the mutable reference of the group.

const ImageAugIlluminationGradient &get_illumination_gradient() const#

Get Illumination Gradient.

Simulate the illumination intensity changing gradient caused by the shift of the light position.

Returns:

const ImageAugIlluminationGradient & Illumination Gradient

ImageAugmentation &set_illumination_gradient(ImageAugIlluminationGradient illumination_gradient)#

Set Illumination Gradient with ImageAugIlluminationGradient value.

Simulate the illumination intensity changing gradient caused by the shift of the light position.

Parameters:

illumination_gradient – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImageAugmentation the reference of this object.

ImageAugIlluminationGradient &get_illumination_gradient()#

Get mutable reference of Illumination Gradient.

Simulate the illumination intensity changing gradient caused by the shift of the light position.

Returns:

ImageAugmentation& the mutable reference of the group.

class DataAugmentation : public visionflow::param::ISchemable#

DataAugmentation Parameter class generated by jinja2 automatically.

Data Augmentation Parameters Group.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

const GeometryAugmentation &get_geometry_augmentation() const#

Get Geometry Augmentation.

Geometry augmentation parameters. Enable the type of geometric changes that may exist in the real-world scenarios, by randomly geometrically augmenting the original training dataset to simulate that similar pictures may appear in the real-world scenarios, the corresponding generalization ability of the model can be improved.

Returns:

const GeometryAugmentation & Geometry Augmentation

DataAugmentation &set_geometry_augmentation(GeometryAugmentation geometry_augmentation)#

Set Geometry Augmentation with GeometryAugmentation value.

Geometry augmentation parameters. Enable the type of geometric changes that may exist in the real-world scenarios, by randomly geometrically augmenting the original training dataset to simulate that similar pictures may appear in the real-world scenarios, the corresponding generalization ability of the model can be improved.

Parameters:

geometry_augmentation – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

DataAugmentation the reference of this object.

GeometryAugmentation &get_geometry_augmentation()#

Get mutable reference of Geometry Augmentation.

Geometry augmentation parameters. Enable the type of geometric changes that may exist in the real-world scenarios, by randomly geometrically augmenting the original training dataset to simulate that similar pictures may appear in the real-world scenarios, the corresponding generalization ability of the model can be improved.

Returns:

DataAugmentation& the mutable reference of the group.

const ImageAugmentation &get_image_augmentation() const#

Get Image Augmentation.

Image augmentation parameters. By enabling parameters corresponding to imaging variations that may occur in real-world scenarios, and applying random image quality augmentation to the training data, the model’s generalization performance can be improved.

Returns:

const ImageAugmentation & Image Augmentation

DataAugmentation &set_image_augmentation(ImageAugmentation image_augmentation)#

Set Image Augmentation with ImageAugmentation value.

Image augmentation parameters. By enabling parameters corresponding to imaging variations that may occur in real-world scenarios, and applying random image quality augmentation to the training data, the model’s generalization performance can be improved.

Parameters:

image_augmentation – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

DataAugmentation the reference of this object.

ImageAugmentation &get_image_augmentation()#

Get mutable reference of Image Augmentation.

Image augmentation parameters. By enabling parameters corresponding to imaging variations that may occur in real-world scenarios, and applying random image quality augmentation to the training data, the model’s generalization performance can be improved.

Returns:

DataAugmentation& the mutable reference of the group.

ImagePreprocess Parameters#

enum visionflow::param::ImagePreprocessType#

Values:

enumerator kArithm = 0#
enumerator kHighPassFilter = 1#
enumerator kLowPassFilter = 2#
enumerator kFilter2D = 3#
enumerator kMorph = 4#
enumerator kLut = 5#
enumerator kSharpening = 6#
enumerator kHistEqu = 7#
enumerator kGammaTrans = 8#
enumerator kCvtColor = 9#
enumerator kFlip = 10#
enumerator kResize = 11#
enumerator kCirclePolar = 12#
enum visionflow::param::ImagePreprocessArithmType#

Values:

enumerator kArithmAdd = 0#
enumerator kArithmSub = 1#
enumerator kArithmMul = 2#
enumerator kArithmDiv = 3#
class ImagePreprocessArithmParameters : public visionflow::param::ISchemable#

ImagePreprocessArithmParameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

const ImagePreprocessArithmType &get_arithm_type() const#

Get Arithmetic Type.

Arithmetic Type

Returns:

const ImagePreprocessArithmType & Arithmetic Type

ImagePreprocessArithmParameters &set_arithm_type(ImagePreprocessArithmType arithm_type)#

Set Arithmetic Type with ImagePreprocessArithmType value.

Arithmetic Type

Parameters:

arithm_type – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessArithmParameters the reference of this object.

double get_scalar() const#

Get Second operand in arithmetic.

Execute each image pixel operate with scalar

See also

set_scalar()

Returns:

double Second operand in arithmetic

ImagePreprocessArithmParameters &set_scalar(double scalar)#

Set Second operand in arithmetic with double value.

Execute each image pixel operate with scalar

See also

get_scalar()

Parameters:

scalar – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessArithmParameters the reference of this object.

enum visionflow::param::ImagePreprocessFilterType#

Values:

enumerator kFilterGaussian = 0#
enumerator kFilterMean = 1#
enumerator kFilterMedian = 2#
enum visionflow::param::ImagePreprocessBorderType#

Values:

enumerator kBorderConstant = 0#
enumerator kBorderReplicate = 1#
enumerator kBorderReflect = 2#
enumerator kBorderReflect101 = 4#
enumerator kBorderTransparent = 5#
class ImagePreprocessHighPassFilterParameters : public visionflow::param::ISchemable#

ImagePreprocessHighPassFilterParameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

const ImagePreprocessFilterType &get_filter_type() const#

Get High Pass Filter Type.

High Pass Filter Type

Returns:

const ImagePreprocessFilterType & High Pass Filter Type

ImagePreprocessHighPassFilterParameters &set_filter_type(ImagePreprocessFilterType filter_type)#

Set High Pass Filter Type with ImagePreprocessFilterType value.

High Pass Filter Type

Parameters:

filter_type – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessHighPassFilterParameters the reference of this object.

int get_ksize_w() const#

Get Width of kernel.

Width of kernel

See also

set_ksize_w()

Returns:

int Width of kernel

ImagePreprocessHighPassFilterParameters &set_ksize_w(int ksize_w)#

Set Width of kernel with int value.

Width of kernel

See also

get_ksize_w()

Parameters:

ksize_w – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessHighPassFilterParameters the reference of this object.

int get_ksize_h() const#

Get Height of kernel.

Height of kernel. Note : median_blur doesn’t use this.

See also

set_ksize_h()

Returns:

int Height of kernel

ImagePreprocessHighPassFilterParameters &set_ksize_h(int ksize_h)#

Set Height of kernel with int value.

Height of kernel. Note : median_blur doesn’t use this.

See also

get_ksize_h()

Parameters:

ksize_h – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessHighPassFilterParameters the reference of this object.

double get_alpha() const#

Get alpha.

Multiple of difference between src and dst

See also

set_alpha()

Returns:

double alpha

ImagePreprocessHighPassFilterParameters &set_alpha(double alpha)#

Set alpha with double value.

Multiple of difference between src and dst

See also

get_alpha()

Parameters:

alpha – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessHighPassFilterParameters the reference of this object.

double get_beta() const#

Get beta.

Added value to the difference

See also

set_beta()

Returns:

double beta

ImagePreprocessHighPassFilterParameters &set_beta(double beta)#

Set beta with double value.

Added value to the difference

See also

get_beta()

Parameters:

beta – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessHighPassFilterParameters the reference of this object.

double get_sigma_x() const#

Get Standard deviation in X direction.

Gaussian kernel standard deviation in X direction (only used for kFilterGaussian)

See also

set_sigma_x()

Returns:

double Standard deviation in X direction

ImagePreprocessHighPassFilterParameters &set_sigma_x(double sigma_x)#

Set Standard deviation in X direction with double value.

Gaussian kernel standard deviation in X direction (only used for kFilterGaussian)

See also

get_sigma_x()

Parameters:

sigma_x – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessHighPassFilterParameters the reference of this object.

double get_sigma_y() const#

Get Standard deviation in Y direction.

Gaussian kernel standard deviation in Y direction. If sigma_y is zero, it is set to be equal to sigma_x, if both sigmas are zeros, they are computed from ksize_w and ksize_h. (only used for kFilterGaussian)

See also

set_sigma_y()

Returns:

double Standard deviation in Y direction

ImagePreprocessHighPassFilterParameters &set_sigma_y(double sigma_y)#

Set Standard deviation in Y direction with double value.

Gaussian kernel standard deviation in Y direction. If sigma_y is zero, it is set to be equal to sigma_x, if both sigmas are zeros, they are computed from ksize_w and ksize_h. (only used for kFilterGaussian)

See also

get_sigma_y()

Parameters:

sigma_y – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessHighPassFilterParameters the reference of this object.

const ImagePreprocessBorderType &get_border_type() const#

Get Border Type.

Border Type

Returns:

const ImagePreprocessBorderType & Border Type

ImagePreprocessHighPassFilterParameters &set_border_type(ImagePreprocessBorderType border_type)#

Set Border Type with ImagePreprocessBorderType value.

Border Type

Parameters:

border_type – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessHighPassFilterParameters the reference of this object.

class ImagePreprocessLowPassFilterParameters : public visionflow::param::ISchemable#

ImagePreprocessLowPassFilterParameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

const ImagePreprocessFilterType &get_filter_type() const#

Get Low Pass Filter Type.

Low Pass Filter Type

Returns:

const ImagePreprocessFilterType & Low Pass Filter Type

ImagePreprocessLowPassFilterParameters &set_filter_type(ImagePreprocessFilterType filter_type)#

Set Low Pass Filter Type with ImagePreprocessFilterType value.

Low Pass Filter Type

Parameters:

filter_type – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessLowPassFilterParameters the reference of this object.

int get_ksize_w() const#

Get Width of kernel.

Width of kernel

See also

set_ksize_w()

Returns:

int Width of kernel

ImagePreprocessLowPassFilterParameters &set_ksize_w(int ksize_w)#

Set Width of kernel with int value.

Width of kernel

See also

get_ksize_w()

Parameters:

ksize_w – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessLowPassFilterParameters the reference of this object.

int get_ksize_h() const#

Get Height of kernel.

Height of kernel. Note : median_blur doesn’t use this.

See also

set_ksize_h()

Returns:

int Height of kernel

ImagePreprocessLowPassFilterParameters &set_ksize_h(int ksize_h)#

Set Height of kernel with int value.

Height of kernel. Note : median_blur doesn’t use this.

See also

get_ksize_h()

Parameters:

ksize_h – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessLowPassFilterParameters the reference of this object.

double get_sigma_x() const#

Get Standard deviation in X direction.

Gaussian kernel standard deviation in X direction (only used for kFilterGaussian)

See also

set_sigma_x()

Returns:

double Standard deviation in X direction

ImagePreprocessLowPassFilterParameters &set_sigma_x(double sigma_x)#

Set Standard deviation in X direction with double value.

Gaussian kernel standard deviation in X direction (only used for kFilterGaussian)

See also

get_sigma_x()

Parameters:

sigma_x – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessLowPassFilterParameters the reference of this object.

double get_sigma_y() const#

Get Standard deviation in Y direction.

Gaussian kernel standard deviation in Y direction. If sigma_y is zero, it is set to be equal to sigma_x, if both sigmas are zeros, they are computed from ksize_w and ksize_h. (only used for kFilterGaussian)

See also

set_sigma_y()

Returns:

double Standard deviation in Y direction

ImagePreprocessLowPassFilterParameters &set_sigma_y(double sigma_y)#

Set Standard deviation in Y direction with double value.

Gaussian kernel standard deviation in Y direction. If sigma_y is zero, it is set to be equal to sigma_x, if both sigmas are zeros, they are computed from ksize_w and ksize_h. (only used for kFilterGaussian)

See also

get_sigma_y()

Parameters:

sigma_y – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessLowPassFilterParameters the reference of this object.

const ImagePreprocessBorderType &get_border_type() const#

Get Border Type.

Border Type

Returns:

const ImagePreprocessBorderType & Border Type

ImagePreprocessLowPassFilterParameters &set_border_type(ImagePreprocessBorderType border_type)#

Set Border Type with ImagePreprocessBorderType value.

Border Type

Parameters:

border_type – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessLowPassFilterParameters the reference of this object.

class ImagePreprocessFilter2DParameters : public visionflow::param::ISchemable#

ImagePreprocessFilter2DParameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

int get_ksize() const#

Get Size of kernel.

Size of kernel

See also

set_ksize()

Returns:

int Size of kernel

ImagePreprocessFilter2DParameters &set_ksize(int ksize)#

Set Size of kernel with int value.

Size of kernel

See also

get_ksize()

Parameters:

ksize – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessFilter2DParameters the reference of this object.

const std::vector<double> &get_kernel() const#

Get Filter2D kernel.

convolution kernel, a single-channel floating point matrix, it has ksize * ksize elements and in row precedence

See also

set_kernel()

Returns:

const std::vector<double> & Filter2D kernel

ImagePreprocessFilter2DParameters &set_kernel(std::vector<double> kernel)#

Set Filter2D kernel with std::vector<double> value.

convolution kernel, a single-channel floating point matrix, it has ksize * ksize elements and in row precedence

See also

get_kernel()

Parameters:

kernel – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessFilter2DParameters the reference of this object.

double get_kernel(size_t index) const#

Get value in Filter2D kernel with index.

Warning

The index must be less than get_kernel_size(). otherwise, the behavior is undefined and will cause segmentation fault.

Returns:

double value in Filter2D kernel at index.

size_t get_kernel_size() const#

Get the size of Filter2D kernel.

Returns:

size_t the size of Filter2D kernel

enum visionflow::param::ImagePreprocessMorphType#

Values:

enumerator kMorphErode = 0#
enumerator kMorphDilate = 1#
enumerator kMorphOpen = 2#
enumerator kMorphClose = 3#
enum visionflow::param::ImagePreprocessMorphShape#

Values:

enumerator kMorphRect = 0#
enumerator kMorphCross = 1#
enumerator kMorphEllipse = 2#
class ImagePreprocessMorphParameters : public visionflow::param::ISchemable#

ImagePreprocessMorphParameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

const ImagePreprocessMorphType &get_morph_type() const#

Get Morphology Type.

Morphology Type

See also

set_morph_type()

Returns:

const ImagePreprocessMorphType & Morphology Type

ImagePreprocessMorphParameters &set_morph_type(ImagePreprocessMorphType morph_type)#

Set Morphology Type with ImagePreprocessMorphType value.

Morphology Type

See also

get_morph_type()

Parameters:

morph_type – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessMorphParameters the reference of this object.

const ImagePreprocessMorphShape &get_morph_shape() const#

Get Morphology Shape.

Morphology Shape

Returns:

const ImagePreprocessMorphShape & Morphology Shape

ImagePreprocessMorphParameters &set_morph_shape(ImagePreprocessMorphShape morph_shape)#

Set Morphology Shape with ImagePreprocessMorphShape value.

Morphology Shape

Parameters:

morph_shape – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessMorphParameters the reference of this object.

int get_ksize_w() const#

Get Width of kernel.

Width of kernel

See also

set_ksize_w()

Returns:

int Width of kernel

ImagePreprocessMorphParameters &set_ksize_w(int ksize_w)#

Set Width of kernel with int value.

Width of kernel

See also

get_ksize_w()

Parameters:

ksize_w – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessMorphParameters the reference of this object.

int get_ksize_h() const#

Get Height of kernel.

Height of kernel

See also

set_ksize_h()

Returns:

int Height of kernel

ImagePreprocessMorphParameters &set_ksize_h(int ksize_h)#

Set Height of kernel with int value.

Height of kernel

See also

get_ksize_h()

Parameters:

ksize_h – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessMorphParameters the reference of this object.

class ImagePreprocessLutParameters : public visionflow::param::ISchemable#

ImagePreprocessLutParameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

const std::vector<int> &get_lut() const#

Get Look up table.

Look up table

See also

set_lut()

Returns:

const std::vector<int> & Look up table

ImagePreprocessLutParameters &set_lut(std::vector<int> lut)#

Set Look up table with std::vector<int> value.

Look up table

See also

get_lut()

Parameters:

lut – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessLutParameters the reference of this object.

int get_lut(size_t index) const#

Get value in Look up table with index.

Warning

The index must be less than get_lut_size(). otherwise, the behavior is undefined and will cause segmentation fault.

Returns:

int value in Look up table at index.

size_t get_lut_size() const#

Get the size of Look up table.

Returns:

size_t the size of Look up table

class ImagePreprocessSharpenParameters : public visionflow::param::ISchemable#

ImagePreprocessSharpenParameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

int get_ksize_w() const#

Get Width of kernel.

Width of kernel

See also

set_ksize_w()

Returns:

int Width of kernel

ImagePreprocessSharpenParameters &set_ksize_w(int ksize_w)#

Set Width of kernel with int value.

Width of kernel

See also

get_ksize_w()

Parameters:

ksize_w – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessSharpenParameters the reference of this object.

int get_ksize_h() const#

Get Height of kernel.

Height of kernel

See also

set_ksize_h()

Returns:

int Height of kernel

ImagePreprocessSharpenParameters &set_ksize_h(int ksize_h)#

Set Height of kernel with int value.

Height of kernel

See also

get_ksize_h()

Parameters:

ksize_h – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessSharpenParameters the reference of this object.

double get_factor() const#

Get Sharpening factor.

Sharpening factor

See also

set_factor()

Returns:

double Sharpening factor

ImagePreprocessSharpenParameters &set_factor(double factor)#

Set Sharpening factor with double value.

Sharpening factor

See also

get_factor()

Parameters:

factor – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessSharpenParameters the reference of this object.

class ImagePreprocessGammaTransParameters : public visionflow::param::ISchemable#

ImagePreprocessGammaTransParameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

double get_gamma() const#

Get Gamma Parameters.

Gamma Parameters

See also

set_gamma()

Returns:

double Gamma Parameters

ImagePreprocessGammaTransParameters &set_gamma(double gamma)#

Set Gamma Parameters with double value.

Gamma Parameters

See also

get_gamma()

Parameters:

gamma – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessGammaTransParameters the reference of this object.

int get_alpha() const#

Get Alpha Parameters.

Alpha Parameters

See also

set_alpha()

Returns:

int Alpha Parameters

ImagePreprocessGammaTransParameters &set_alpha(int alpha)#

Set Alpha Parameters with int value.

Alpha Parameters

See also

get_alpha()

Parameters:

alpha – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessGammaTransParameters the reference of this object.

int get_beta() const#

Get Beta Parameters.

Beta Parameters

See also

set_beta()

Returns:

int Beta Parameters

ImagePreprocessGammaTransParameters &set_beta(int beta)#

Set Beta Parameters with int value.

Beta Parameters

See also

get_beta()

Parameters:

beta – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessGammaTransParameters the reference of this object.

enum visionflow::param::ImagePreprocessColorConversionType#

Values:

enumerator kColorBGR2BGRA = 0#
enumerator kColorBGRA2BGR = 1#
enumerator kColorBGR2RGBA = 2#
enumerator kColorRGBA2BGR = 3#
enumerator kColorBGR2RGB = 4#
enumerator kColorBGRA2RGBA = 5#
enumerator kColorBGR2Gray = 6#
enumerator kColorRGB2Gray = 7#
enumerator kColorGray2BGR = 8#
enumerator kColorGray2BGRA = 9#
enumerator kColorBGRA2Gray = 10#
enumerator kColorRGBA2Gray = 11#
enumerator kColorBGR2YCrCb = 36#
enumerator kColorRGB2YCrCb = 37#
enumerator kColorYCrCb2BGR = 38#
enumerator kColorYCrCb2RGB = 39#
enumerator kColorBGR2HSV = 40#
enumerator kColorRGB2HSV = 41#
enumerator kColorBGR2Lab = 44#
enumerator kColorRGB2Lab = 45#
enumerator kColorBGR2Luv = 50#
enumerator kColorRGB2Luv = 51#
enumerator kColorBGR2HLS = 52#
enumerator kColorRGB2HLS = 53#
enumerator kColorHSV2BGR = 54#
enumerator kColorHSV2RGB = 55#
enumerator kColorBGR2YUV = 82#
enumerator kColorRGB2YUV = 83#
enumerator kColorYUV2BGR = 84#
enumerator kColorYUV2RGB = 85#
class ImagePreprocessCvtColorParameters : public visionflow::param::ISchemable#

ImagePreprocessCvtColorParameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

const ImagePreprocessColorConversionType &get_cvt_type() const#

Get Color Conversion Type.

Color Conversion Type

See also

set_cvt_type()

Returns:

const ImagePreprocessColorConversionType & Color Conversion Type

ImagePreprocessCvtColorParameters &set_cvt_type(ImagePreprocessColorConversionType cvt_type)#

Set Color Conversion Type with ImagePreprocessColorConversionType value.

Color Conversion Type

See also

get_cvt_type()

Parameters:

cvt_type – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessCvtColorParameters the reference of this object.

const std::vector<double> &get_coeffs() const#

Get Color Conversion Coefficients.

User-defined vector of coefficients for converting color images to grayscale images. Only used in kColorBGR2Gray, kColorRGB2Gray, kColorBGRA2Gray and kColorRGBA2Gray. 0 <= coefficients <= 1. The sum of the coefficients should be less than or equal to 1. When the coeffs is empty, the default value {0.114F, 0.587F, 0.299F} will be used. If one coeffs is 1, it extracts corresponding channel from source image. The of result is a single-channel image.

See also

set_coeffs()

Returns:

const std::vector<double> & Color Conversion Coefficients

ImagePreprocessCvtColorParameters &set_coeffs(std::vector<double> coeffs)#

Set Color Conversion Coefficients with std::vector<double> value.

User-defined vector of coefficients for converting color images to grayscale images. Only used in kColorBGR2Gray, kColorRGB2Gray, kColorBGRA2Gray and kColorRGBA2Gray. 0 <= coefficients <= 1. The sum of the coefficients should be less than or equal to 1. When the coeffs is empty, the default value {0.114F, 0.587F, 0.299F} will be used. If one coeffs is 1, it extracts corresponding channel from source image. The of result is a single-channel image.

See also

get_coeffs()

Parameters:

coeffs – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessCvtColorParameters the reference of this object.

double get_coeffs(size_t index) const#

Get value in Color Conversion Coefficients with index.

Warning

The index must be less than get_coeffs_size(). otherwise, the behavior is undefined and will cause segmentation fault.

Returns:

double value in Color Conversion Coefficients at index.

size_t get_coeffs_size() const#

Get the size of Color Conversion Coefficients.

Returns:

size_t the size of Color Conversion Coefficients

enum visionflow::param::ImagePreprocessFlipType#

Values:

enumerator kFlipVertical = 0#
enumerator kFlipHorizontal = 1#
enumerator kFlipBoth = 2#
enumerator kFlip45 = 3#
enumerator kFlip135 = 4#
class ImagePreprocessFlipParameters : public visionflow::param::ISchemable#

ImagePreprocessFlipParameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

const ImagePreprocessFlipType &get_flip_type() const#

Get Flip Type.

Flip Type

See also

set_flip_type()

Returns:

const ImagePreprocessFlipType & Flip Type

ImagePreprocessFlipParameters &set_flip_type(ImagePreprocessFlipType flip_type)#

Set Flip Type with ImagePreprocessFlipType value.

Flip Type

See also

get_flip_type()

Parameters:

flip_type – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessFlipParameters the reference of this object.

enum visionflow::param::ImagePreprocessInterMethod#

Values:

enumerator kInterNearest = 0#
enumerator kInterLinear = 1#
enumerator kInterCubic = 2#
enumerator kInterArea = 3#
class ImagePreprocessResizeParameters : public visionflow::param::ISchemable#

ImagePreprocessResizeParameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

int get_dst_w() const#

Get Target Width.

Target Width

See also

set_dst_w()

Returns:

int Target Width

ImagePreprocessResizeParameters &set_dst_w(int dst_w)#

Set Target Width with int value.

Target Width

See also

get_dst_w()

Parameters:

dst_w – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessResizeParameters the reference of this object.

int get_dst_h() const#

Get Target Height.

Target Height

See also

set_dst_h()

Returns:

int Target Height

ImagePreprocessResizeParameters &set_dst_h(int dst_h)#

Set Target Height with int value.

Target Height

See also

get_dst_h()

Parameters:

dst_h – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessResizeParameters the reference of this object.

double get_x_scale() const#

Get Scale factor in x direction.

Scale factor in x direction, only used when both dst_w and dst_h is zero.

See also

set_x_scale()

Returns:

double Scale factor in x direction

ImagePreprocessResizeParameters &set_x_scale(double x_scale)#

Set Scale factor in x direction with double value.

Scale factor in x direction, only used when both dst_w and dst_h is zero.

See also

get_x_scale()

Parameters:

x_scale – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessResizeParameters the reference of this object.

double get_y_scale() const#

Get Scale factor in y direction.

Scale factor in y direction, only used when both dst_w and dst_h is zero.

See also

set_y_scale()

Returns:

double Scale factor in y direction

ImagePreprocessResizeParameters &set_y_scale(double y_scale)#

Set Scale factor in y direction with double value.

Scale factor in y direction, only used when both dst_w and dst_h is zero.

See also

get_y_scale()

Parameters:

y_scale – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessResizeParameters the reference of this object.

const ImagePreprocessInterMethod &get_inter_method() const#

Get Interpolation Method.

Interpolation Method

Returns:

const ImagePreprocessInterMethod & Interpolation Method

ImagePreprocessResizeParameters &set_inter_method(ImagePreprocessInterMethod inter_method)#

Set Interpolation Method with ImagePreprocessInterMethod value.

Interpolation Method

Parameters:

inter_method – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessResizeParameters the reference of this object.

class ImagePreprocessCirclePolarParameters : public visionflow::param::ISchemable#

ImagePreprocessCirclePolarParameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

double get_x() const#

Get X-Value.

X-coordinate of the center point of the annular section

See also

set_x()

Returns:

double X-Value

ImagePreprocessCirclePolarParameters &set_x(double x)#

Set X-Value with double value.

X-coordinate of the center point of the annular section

See also

get_x()

Parameters:

x – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessCirclePolarParameters the reference of this object.

double get_y() const#

Get Y-Value.

Y-coordinate of the center point of the annular section

See also

set_y()

Returns:

double Y-Value

ImagePreprocessCirclePolarParameters &set_y(double y)#

Set Y-Value with double value.

Y-coordinate of the center point of the annular section

See also

get_y()

Parameters:

y – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessCirclePolarParameters the reference of this object.

double get_start_radius() const#

Get Start Radius.

Start radius of the annular section

Returns:

double Start Radius

ImagePreprocessCirclePolarParameters &set_start_radius(double start_radius)#

Set Start Radius with double value.

Start radius of the annular section

Parameters:

start_radius – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessCirclePolarParameters the reference of this object.

double get_end_radius() const#

Get End Radius.

End radius of the annular section

See also

set_end_radius()

Returns:

double End Radius

ImagePreprocessCirclePolarParameters &set_end_radius(double end_radius)#

Set End Radius with double value.

End radius of the annular section

See also

get_end_radius()

Parameters:

end_radius – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessCirclePolarParameters the reference of this object.

double get_start_angle() const#

Get Start Angle.

Start angle (Degree) of the annular section

Returns:

double Start Angle

ImagePreprocessCirclePolarParameters &set_start_angle(double start_angle)#

Set Start Angle with double value.

Start angle (Degree) of the annular section

Parameters:

start_angle – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessCirclePolarParameters the reference of this object.

double get_end_angle() const#

Get End Angle.

End angle (Degree) of the annular section

See also

set_end_angle()

Returns:

double End Angle

ImagePreprocessCirclePolarParameters &set_end_angle(double end_angle)#

Set End Angle with double value.

End angle (Degree) of the annular section

See also

get_end_angle()

Parameters:

end_angle – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessCirclePolarParameters the reference of this object.

int get_dst_w() const#

Get Target Width.

Target Width. If both dst_w and dst_h is zero, it will be set adaptively with given annulus.

See also

set_dst_w()

Returns:

int Target Width

ImagePreprocessCirclePolarParameters &set_dst_w(int dst_w)#

Set Target Width with int value.

Target Width. If both dst_w and dst_h is zero, it will be set adaptively with given annulus.

See also

get_dst_w()

Parameters:

dst_w – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessCirclePolarParameters the reference of this object.

int get_dst_h() const#

Get Target Height.

Target Height. If both dst_w and dst_h is zero, it will be set adaptively with given annulus.

See also

set_dst_h()

Returns:

int Target Height

ImagePreprocessCirclePolarParameters &set_dst_h(int dst_h)#

Set Target Height with int value.

Target Height. If both dst_w and dst_h is zero, it will be set adaptively with given annulus.

See also

get_dst_h()

Parameters:

dst_h – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessCirclePolarParameters the reference of this object.

const ImagePreprocessInterMethod &get_inter_method() const#

Get Interpolation Method.

Interpolation Method

Returns:

const ImagePreprocessInterMethod & Interpolation Method

ImagePreprocessCirclePolarParameters &set_inter_method(ImagePreprocessInterMethod inter_method)#

Set Interpolation Method with ImagePreprocessInterMethod value.

Interpolation Method

Parameters:

inter_method – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessCirclePolarParameters the reference of this object.

const ImagePreprocessBorderType &get_border_type() const#

Get Border Type.

Border Type

Returns:

const ImagePreprocessBorderType & Border Type

ImagePreprocessCirclePolarParameters &set_border_type(ImagePreprocessBorderType border_type)#

Set Border Type with ImagePreprocessBorderType value.

Border Type

Parameters:

border_type – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessCirclePolarParameters the reference of this object.

class ImagePreprocessParameters : public visionflow::param::ISchemable#

ImagePreprocessParameters Parameter class generated by jinja2 automatically.

Image Preprocess Parameter Group

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

const ImagePreprocessType &get_type() const#

Get Image Preprocess Type.

Image Preprocess Type

See also

set_type()

Returns:

const ImagePreprocessType & Image Preprocess Type

ImagePreprocessParameters &set_type(ImagePreprocessType type)#

Set Image Preprocess Type with ImagePreprocessType value.

Image Preprocess Type

See also

get_type()

Parameters:

type – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessParameters the reference of this object.

const ImagePreprocessArithmParameters &get_arithm() const#

Get Arithm Parameters.

Arithm Parameters

See also

set_arithm()

Returns:

const ImagePreprocessArithmParameters & Arithm Parameters

ImagePreprocessParameters &set_arithm(ImagePreprocessArithmParameters arithm)#

Set Arithm Parameters with ImagePreprocessArithmParameters value.

Arithm Parameters

See also

get_arithm()

Parameters:

arithm – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessParameters the reference of this object.

ImagePreprocessArithmParameters &get_arithm()#

Get mutable reference of Arithm Parameters.

Arithm Parameters

Returns:

ImagePreprocessParameters& the mutable reference of the group.

const ImagePreprocessHighPassFilterParameters &get_high_pass_filter() const#

Get High Pass Filter Parameters.

High Pass Filter Parameters

Returns:

const ImagePreprocessHighPassFilterParameters & High Pass Filter Parameters

ImagePreprocessParameters &set_high_pass_filter(ImagePreprocessHighPassFilterParameters high_pass_filter)#

Set High Pass Filter Parameters with ImagePreprocessHighPassFilterParameters value.

High Pass Filter Parameters

Parameters:

high_pass_filter – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessParameters the reference of this object.

ImagePreprocessHighPassFilterParameters &get_high_pass_filter()#

Get mutable reference of High Pass Filter Parameters.

High Pass Filter Parameters

Returns:

ImagePreprocessParameters& the mutable reference of the group.

const ImagePreprocessLowPassFilterParameters &get_low_pass_filter() const#

Get Low Pass Filter Parameters.

Low Pass Filter Parameters

Returns:

const ImagePreprocessLowPassFilterParameters & Low Pass Filter Parameters

ImagePreprocessParameters &set_low_pass_filter(ImagePreprocessLowPassFilterParameters low_pass_filter)#

Set Low Pass Filter Parameters with ImagePreprocessLowPassFilterParameters value.

Low Pass Filter Parameters

Parameters:

low_pass_filter – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessParameters the reference of this object.

ImagePreprocessLowPassFilterParameters &get_low_pass_filter()#

Get mutable reference of Low Pass Filter Parameters.

Low Pass Filter Parameters

Returns:

ImagePreprocessParameters& the mutable reference of the group.

const ImagePreprocessFilter2DParameters &get_filter2d() const#

Get Filter2D Parameters.

Filter2D Parameters

See also

set_filter2d()

Returns:

const ImagePreprocessFilter2DParameters & Filter2D Parameters

ImagePreprocessParameters &set_filter2d(ImagePreprocessFilter2DParameters filter2d)#

Set Filter2D Parameters with ImagePreprocessFilter2DParameters value.

Filter2D Parameters

See also

get_filter2d()

Parameters:

filter2d – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessParameters the reference of this object.

ImagePreprocessFilter2DParameters &get_filter2d()#

Get mutable reference of Filter2D Parameters.

Filter2D Parameters

Returns:

ImagePreprocessParameters& the mutable reference of the group.

const ImagePreprocessMorphParameters &get_morph() const#

Get Morphology Parameters.

Morphology Parameters

See also

set_morph()

Returns:

const ImagePreprocessMorphParameters & Morphology Parameters

ImagePreprocessParameters &set_morph(ImagePreprocessMorphParameters morph)#

Set Morphology Parameters with ImagePreprocessMorphParameters value.

Morphology Parameters

See also

get_morph()

Parameters:

morph – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessParameters the reference of this object.

ImagePreprocessMorphParameters &get_morph()#

Get mutable reference of Morphology Parameters.

Morphology Parameters

Returns:

ImagePreprocessParameters& the mutable reference of the group.

const ImagePreprocessLutParameters &get_lut() const#

Get Lut Parameters.

Lut Parameters

See also

set_lut()

Returns:

const ImagePreprocessLutParameters & Lut Parameters

ImagePreprocessParameters &set_lut(ImagePreprocessLutParameters lut)#

Set Lut Parameters with ImagePreprocessLutParameters value.

Lut Parameters

See also

get_lut()

Parameters:

lut – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessParameters the reference of this object.

ImagePreprocessLutParameters &get_lut()#

Get mutable reference of Lut Parameters.

Lut Parameters

Returns:

ImagePreprocessParameters& the mutable reference of the group.

const ImagePreprocessSharpenParameters &get_sharpen() const#

Get Sharpen Parameters.

Sharpen Parameters

See also

set_sharpen()

Returns:

const ImagePreprocessSharpenParameters & Sharpen Parameters

ImagePreprocessParameters &set_sharpen(ImagePreprocessSharpenParameters sharpen)#

Set Sharpen Parameters with ImagePreprocessSharpenParameters value.

Sharpen Parameters

See also

get_sharpen()

Parameters:

sharpen – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessParameters the reference of this object.

ImagePreprocessSharpenParameters &get_sharpen()#

Get mutable reference of Sharpen Parameters.

Sharpen Parameters

Returns:

ImagePreprocessParameters& the mutable reference of the group.

const ImagePreprocessGammaTransParameters &get_gamma_trans() const#

Get Gamma Transformation Parameters.

Gamma Transformation Parameters

Returns:

const ImagePreprocessGammaTransParameters & Gamma Transformation Parameters

ImagePreprocessParameters &set_gamma_trans(ImagePreprocessGammaTransParameters gamma_trans)#

Set Gamma Transformation Parameters with ImagePreprocessGammaTransParameters value.

Gamma Transformation Parameters

Parameters:

gamma_trans – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessParameters the reference of this object.

ImagePreprocessGammaTransParameters &get_gamma_trans()#

Get mutable reference of Gamma Transformation Parameters.

Gamma Transformation Parameters

Returns:

ImagePreprocessParameters& the mutable reference of the group.

const ImagePreprocessCvtColorParameters &get_cvt_color() const#

Get Color Conversion Parameters.

Color Conversion Parameters

See also

set_cvt_color()

Returns:

const ImagePreprocessCvtColorParameters & Color Conversion Parameters

ImagePreprocessParameters &set_cvt_color(ImagePreprocessCvtColorParameters cvt_color)#

Set Color Conversion Parameters with ImagePreprocessCvtColorParameters value.

Color Conversion Parameters

See also

get_cvt_color()

Parameters:

cvt_color – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessParameters the reference of this object.

ImagePreprocessCvtColorParameters &get_cvt_color()#

Get mutable reference of Color Conversion Parameters.

Color Conversion Parameters

Returns:

ImagePreprocessParameters& the mutable reference of the group.

const ImagePreprocessFlipParameters &get_flip() const#

Get Flip Parameters.

Flip Parameters

See also

set_flip()

Returns:

const ImagePreprocessFlipParameters & Flip Parameters

ImagePreprocessParameters &set_flip(ImagePreprocessFlipParameters flip)#

Set Flip Parameters with ImagePreprocessFlipParameters value.

Flip Parameters

See also

get_flip()

Parameters:

flip – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessParameters the reference of this object.

ImagePreprocessFlipParameters &get_flip()#

Get mutable reference of Flip Parameters.

Flip Parameters

Returns:

ImagePreprocessParameters& the mutable reference of the group.

const ImagePreprocessResizeParameters &get_resize() const#

Get Resize Parameters.

Resize Parameters

See also

set_resize()

Returns:

const ImagePreprocessResizeParameters & Resize Parameters

ImagePreprocessParameters &set_resize(ImagePreprocessResizeParameters resize)#

Set Resize Parameters with ImagePreprocessResizeParameters value.

Resize Parameters

See also

get_resize()

Parameters:

resize – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessParameters the reference of this object.

ImagePreprocessResizeParameters &get_resize()#

Get mutable reference of Resize Parameters.

Resize Parameters

Returns:

ImagePreprocessParameters& the mutable reference of the group.

const ImagePreprocessCirclePolarParameters &get_circle_polar() const#

Get Circle Polar Parameters.

Circle Polar Parameters

Returns:

const ImagePreprocessCirclePolarParameters & Circle Polar Parameters

ImagePreprocessParameters &set_circle_polar(ImagePreprocessCirclePolarParameters circle_polar)#

Set Circle Polar Parameters with ImagePreprocessCirclePolarParameters value.

Circle Polar Parameters

Parameters:

circle_polar – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessParameters the reference of this object.

ImagePreprocessCirclePolarParameters &get_circle_polar()#

Get mutable reference of Circle Polar Parameters.

Circle Polar Parameters

Returns:

ImagePreprocessParameters& the mutable reference of the group.

class ImagePreprocessParametersList : public visionflow::param::ISchemable#

ImagePreprocessParametersList Parameter class generated by jinja2 automatically.

Parameter list for a single visible image in an Image

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

const std::vector<ImagePreprocessParameters> &get_params_list() const#

Get Image Preprocess Parameter List.

Image Preprocess Parameter List for a single visible image, each propressing function will be executed in sequence, and only the final result will be saved.

Returns:

const std::vector<ImagePreprocessParameters> & Image Preprocess Parameter List

ImagePreprocessParametersList &set_params_list(std::vector<ImagePreprocessParameters> params_list)#

Set Image Preprocess Parameter List with std::vector<ImagePreprocessParameters> value.

Image Preprocess Parameter List for a single visible image, each propressing function will be executed in sequence, and only the final result will be saved.

Parameters:

params_list – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessParametersList the reference of this object.

const ImagePreprocessParameters &get_params_list(size_t index) const#

Get value in Image Preprocess Parameter List with index.

Warning

The index must be less than get_params_list_size(). otherwise, the behavior is undefined and will cause segmentation fault.

Returns:

const ImagePreprocessParameters & value in Image Preprocess Parameter List at index.

size_t get_params_list_size() const#

Get the size of Image Preprocess Parameter List.

Returns:

size_t the size of Image Preprocess Parameter List

ImagePreprocessParameters &get_params_list(size_t index)#

Get mutable reference of value in Image Preprocess Parameter List with index.

Warning

The index must be less than get_params_list_size(). otherwise, the behavior is undefined and will cause segmentation fault.

Returns:

ImagePreprocessParameters& the mutable reference of value in Image Preprocess Parameter List at index.

class ImagePreprocessParametersListSet : public visionflow::param::SchemableParameter#

ImagePreprocessParametersListSet Parameter class generated by jinja2 automatically.

Parameter group for a set of Image Preprocess Parameter

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

const std::vector<ImagePreprocessParametersList> &get_img_preproc_params() const#

Get Image Preprocess Parameter Sets.

Image Preprocess Parameter Sets. Each ImagePreprocessParametersList in set means a series of preprocessing mothods for a visual image in Image

Returns:

const std::vector<ImagePreprocessParametersList> & Image Preprocess Parameter Sets

ImagePreprocessParametersListSet &set_img_preproc_params(std::vector<ImagePreprocessParametersList> img_preproc_params)#

Set Image Preprocess Parameter Sets with std::vector<ImagePreprocessParametersList> value.

Image Preprocess Parameter Sets. Each ImagePreprocessParametersList in set means a series of preprocessing mothods for a visual image in Image

Parameters:

img_preproc_params – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ImagePreprocessParametersListSet the reference of this object.

const ImagePreprocessParametersList &get_img_preproc_params(size_t index) const#

Get value in Image Preprocess Parameter Sets with index.

Warning

The index must be less than get_img_preproc_params_size(). otherwise, the behavior is undefined and will cause segmentation fault.

Returns:

const ImagePreprocessParametersList & value in Image Preprocess Parameter Sets at index.

size_t get_img_preproc_params_size() const#

Get the size of Image Preprocess Parameter Sets.

Returns:

size_t the size of Image Preprocess Parameter Sets

ImagePreprocessParametersList &get_img_preproc_params(size_t index)#

Get mutable reference of value in Image Preprocess Parameter Sets with index.

Warning

The index must be less than get_img_preproc_params_size(). otherwise, the behavior is undefined and will cause segmentation fault.

Returns:

ImagePreprocessParametersList& the mutable reference of value in Image Preprocess Parameter Sets at index.

Segmentation Training Parameters#

class SegmentationInputShape : public visionflow::param::ISchemable#

SegmentationInputShape Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

bool get_enable() const#

Get Enable.

Enable this parameter group.

See also

set_enable()

Returns:

bool Enable

SegmentationInputShape &set_enable(bool enable)#

Set Enable with bool value.

Enable this parameter group.

See also

get_enable()

Parameters:

enable – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

SegmentationInputShape the reference of this object.

int get_base_input_width() const#

Get Base Input Width.

Base Input Width

Returns:

int Base Input Width

SegmentationInputShape &set_base_input_width(int base_input_width)#

Set Base Input Width with int value.

Base Input Width

Parameters:

base_input_width – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

SegmentationInputShape the reference of this object.

int get_base_input_height() const#

Get Base Input Height.

Base Input Height

Returns:

int Base Input Height

SegmentationInputShape &set_base_input_height(int base_input_height)#

Set Base Input Height with int value.

Base Input Height

Parameters:

base_input_height – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

SegmentationInputShape the reference of this object.

enum visionflow::param::ImageSplitMode#

Values:

enumerator kAuto = 0#
enumerator kManual = 1#
class SegmentationImageSplit : public visionflow::param::ISchemable#

SegmentationImageSplit Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

const ImageSplitMode &get_split_set_method() const#

Get Split Method.

Auto : The algorithm adapts the recommended resolution levelManual according to the original map size and minimum marking size: the resolution level is based on manual setting Brief description of algorithm : The algorithm scales the short edge of the image to 256*resolution level before feeding to the network, and the long edge scales equally to the input network.

Returns:

const ImageSplitMode & Split Method

SegmentationImageSplit &set_split_set_method(ImageSplitMode split_set_method)#

Set Split Method with ImageSplitMode value.

Auto : The algorithm adapts the recommended resolution levelManual according to the original map size and minimum marking size: the resolution level is based on manual setting Brief description of algorithm : The algorithm scales the short edge of the image to 256*resolution level before feeding to the network, and the long edge scales equally to the input network.

Parameters:

split_set_method – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

SegmentationImageSplit the reference of this object.

int get_max_split() const#

Get Resolution Level.

The short side of the image input will be scaled to (base_size*Resolution Level), and the long side will be scaled proportionally. When the max precision set is higher than the required precision of the algorithm, the precision will be automatically reduced. The applied precision can be acquired from figuration files of the trained model

See also

set_max_split()

Returns:

int Resolution Level

SegmentationImageSplit &set_max_split(int max_split)#

Set Resolution Level with int value.

The short side of the image input will be scaled to (base_size*Resolution Level), and the long side will be scaled proportionally. When the max precision set is higher than the required precision of the algorithm, the precision will be automatically reduced. The applied precision can be acquired from figuration files of the trained model

See also

get_max_split()

Parameters:

max_split – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

SegmentationImageSplit the reference of this object.

class SegmentationModelParameters : public visionflow::param::ISchemable#

SegmentationModelParameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

const std::string &get_model_arch() const#

Get Model Architecture.

The ‘Tiny Defects’ model has better detection effect on small defects, and the ‘Comprehensive Model’ has better comprehensive effect. Recommended to use the ‘Comprehensive Model’ when the detection effect of the Tiny Defects model is poor. ‘Contrastive Model’ is only for contrastive segmentation. The ‘High Precision Model’ detects defect edges more finer, allowing resolution level to be reduced by 1/2 to 3/4 compared to the ‘Tiny Defects’ model and the ‘Comprehensive Model’.

See also

set_model_arch()

Returns:

const std::string & Model Architecture

SegmentationModelParameters &set_model_arch(std::string model_arch)#

Set Model Architecture with std::string value.

The ‘Tiny Defects’ model has better detection effect on small defects, and the ‘Comprehensive Model’ has better comprehensive effect. Recommended to use the ‘Comprehensive Model’ when the detection effect of the Tiny Defects model is poor. ‘Contrastive Model’ is only for contrastive segmentation. The ‘High Precision Model’ detects defect edges more finer, allowing resolution level to be reduced by 1/2 to 3/4 compared to the ‘Tiny Defects’ model and the ‘Comprehensive Model’.

See also

get_model_arch()

Parameters:

model_arch – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

SegmentationModelParameters the reference of this object.

bool get_shift_stable() const#

Get With Shift Stable.

With shift stable, the adaptability of the model to the slight shift of the target can be improved, but the training and inference speed will be 20 percent slower

Returns:

bool With Shift Stable

SegmentationModelParameters &set_shift_stable(bool shift_stable)#

Set With Shift Stable with bool value.

With shift stable, the adaptability of the model to the slight shift of the target can be improved, but the training and inference speed will be 20 percent slower

Parameters:

shift_stable – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

SegmentationModelParameters the reference of this object.

class SegmentationTrainingSampleStrategy : public visionflow::param::ISchemable#

SegmentationTrainingSampleStrategy Parameter class generated by jinja2 automatically.

Segmentation training parameters to control the the input data.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

double get_hard_case_rate() const#

Get Sample Rate of Hard Case.

The larger the value set, the higher the attention to the hard case

Returns:

double Sample Rate of Hard Case

SegmentationTrainingSampleStrategy &set_hard_case_rate(double hard_case_rate)#

Set Sample Rate of Hard Case with double value.

The larger the value set, the higher the attention to the hard case

Parameters:

hard_case_rate – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

SegmentationTrainingSampleStrategy the reference of this object.

int get_hard_case_split() const#

Get Hard Case Split.

Number of hard case discrete coordinates, Default value is recommended.

Returns:

int Hard Case Split

SegmentationTrainingSampleStrategy &set_hard_case_split(int hard_case_split)#

Set Hard Case Split with int value.

Number of hard case discrete coordinates, Default value is recommended.

Parameters:

hard_case_split – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

SegmentationTrainingSampleStrategy the reference of this object.

const SegmentationImageSplit &get_image_split() const#

Get Image Split.

Image Split Parameters

Returns:

const SegmentationImageSplit & Image Split

SegmentationTrainingSampleStrategy &set_image_split(SegmentationImageSplit image_split)#

Set Image Split with SegmentationImageSplit value.

Image Split Parameters

Parameters:

image_split – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

SegmentationTrainingSampleStrategy the reference of this object.

SegmentationImageSplit &get_image_split()#

Get mutable reference of Image Split.

Image Split Parameters

Returns:

SegmentationTrainingSampleStrategy& the mutable reference of the group.

const SegmentationInputShape &get_input_shape() const#

Get Customize Network Input Shape.

Customize Network Input Shape

Returns:

const SegmentationInputShape & Customize Network Input Shape

SegmentationTrainingSampleStrategy &set_input_shape(SegmentationInputShape input_shape)#

Set Customize Network Input Shape with SegmentationInputShape value.

Customize Network Input Shape

Parameters:

input_shape – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

SegmentationTrainingSampleStrategy the reference of this object.

SegmentationInputShape &get_input_shape()#

Get mutable reference of Customize Network Input Shape.

Customize Network Input Shape

Returns:

SegmentationTrainingSampleStrategy& the mutable reference of the group.

class SegmentationTrainingParameters : public visionflow::param::SchemableParameter#

SegmentationTrainingParameters Parameter class generated by jinja2 automatically.

Segmentation Training Parameters Group.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

int get_epoch() const#

Get Epochs.

Number of iterations to train. 1 Epoch means all selected images will be trained for 1 time.

See also

set_epoch()

Returns:

int Epochs

SegmentationTrainingParameters &set_epoch(int epoch)#

Set Epochs with int value.

Number of iterations to train. 1 Epoch means all selected images will be trained for 1 time.

See also

get_epoch()

Parameters:

epoch – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

SegmentationTrainingParameters the reference of this object.

int get_batch_size() const#

Get Training Batch Size.

The number of images involved in training in each iteration of network training. A suitable batch size can make full use of hardware and improve the convergence speed. Common values are 4, 8, and 16. The classification module needs to be set larger, generally 32, 64

See also

set_batch_size()

Returns:

int Training Batch Size

SegmentationTrainingParameters &set_batch_size(int batch_size)#

Set Training Batch Size with int value.

The number of images involved in training in each iteration of network training. A suitable batch size can make full use of hardware and improve the convergence speed. Common values are 4, 8, and 16. The classification module needs to be set larger, generally 32, 64

See also

get_batch_size()

Parameters:

batch_size – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

SegmentationTrainingParameters the reference of this object.

const SegmentationTrainingSampleStrategy &get_sampling_strategy() const#

Get Sampling Strategy.

Sampling Strategy Parameters

Returns:

const SegmentationTrainingSampleStrategy & Sampling Strategy

SegmentationTrainingParameters &set_sampling_strategy(SegmentationTrainingSampleStrategy sampling_strategy)#

Set Sampling Strategy with SegmentationTrainingSampleStrategy value.

Sampling Strategy Parameters

Parameters:

sampling_strategy – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

SegmentationTrainingParameters the reference of this object.

SegmentationTrainingSampleStrategy &get_sampling_strategy()#

Get mutable reference of Sampling Strategy.

Sampling Strategy Parameters

Returns:

SegmentationTrainingParameters& the mutable reference of the group.

const TrainingMode &get_training_mode() const#

Get Training Mode.

Normal Train is the default mode for training a new model. Increment Train will retrain on previous model knowledge.

Returns:

const TrainingMode & Training Mode

SegmentationTrainingParameters &set_training_mode(TrainingMode training_mode)#

Set Training Mode with TrainingMode value.

Normal Train is the default mode for training a new model. Increment Train will retrain on previous model knowledge.

Parameters:

training_mode – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

SegmentationTrainingParameters the reference of this object.

bool get_only_check() const#

Get Only Check.

Default is False. If set to True, the trainer will only check if it is possible to train in the given training mode without actually performing the training.

See also

set_only_check()

Returns:

bool Only Check

SegmentationTrainingParameters &set_only_check(bool only_check)#

Set Only Check with bool value.

Default is False. If set to True, the trainer will only check if it is possible to train in the given training mode without actually performing the training.

See also

get_only_check()

Parameters:

only_check – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

SegmentationTrainingParameters the reference of this object.

const SegmentationModelParameters &get_model_param() const#

Get Model Parameters.

Select the appropriate basic model according to different detection targets and speed requirements

Returns:

const SegmentationModelParameters & Model Parameters

SegmentationTrainingParameters &set_model_param(SegmentationModelParameters model_param)#

Set Model Parameters with SegmentationModelParameters value.

Select the appropriate basic model according to different detection targets and speed requirements

Parameters:

model_param – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

SegmentationTrainingParameters the reference of this object.

SegmentationModelParameters &get_model_param()#

Get mutable reference of Model Parameters.

Select the appropriate basic model according to different detection targets and speed requirements

Returns:

SegmentationTrainingParameters& the mutable reference of the group.

const DataAugmentation &get_augmentations() const#

Get Data Augmentation.

Data Augmentation Parameters

Returns:

const DataAugmentation & Data Augmentation

SegmentationTrainingParameters &set_augmentations(DataAugmentation augmentations)#

Set Data Augmentation with DataAugmentation value.

Data Augmentation Parameters

Parameters:

augmentations – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

SegmentationTrainingParameters the reference of this object.

DataAugmentation &get_augmentations()#

Get mutable reference of Data Augmentation.

Data Augmentation Parameters

Returns:

SegmentationTrainingParameters& the mutable reference of the group.

const DefectSimulation &get_defect_simulation() const#

Get Defect Simulation.

Defect simulation parameters. Enable to allow defects to appear in different positions, angles, and sizes in the same image, thereby increasing the possibility of combining defects with the background, the corresponding generalization ability of the model can be improved.

Returns:

const DefectSimulation & Defect Simulation

SegmentationTrainingParameters &set_defect_simulation(DefectSimulation defect_simulation)#

Set Defect Simulation with DefectSimulation value.

Defect simulation parameters. Enable to allow defects to appear in different positions, angles, and sizes in the same image, thereby increasing the possibility of combining defects with the background, the corresponding generalization ability of the model can be improved.

Parameters:

defect_simulation – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

SegmentationTrainingParameters the reference of this object.

DefectSimulation &get_defect_simulation()#

Get mutable reference of Defect Simulation.

Defect simulation parameters. Enable to allow defects to appear in different positions, angles, and sizes in the same image, thereby increasing the possibility of combining defects with the background, the corresponding generalization ability of the model can be improved.

Returns:

SegmentationTrainingParameters& the mutable reference of the group.

Segmentation Inference Parameters#

class SegmentationInferenceParameters : public visionflow::param::SchemableParameter#

SegmentationInferenceParameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

bool get_infer_score() const#

Get Inference Feature Map.

Inference to get the feature map with pixel score or not. This option is only used for Segmentation tool. In the segmentation tool, disabling this option can significantly improve the inference speed but might result in the absence of accurate scoring for regions.

Returns:

bool Inference Feature Map

SegmentationInferenceParameters &set_infer_score(bool infer_score)#

Set Inference Feature Map with bool value.

Inference to get the feature map with pixel score or not. This option is only used for Segmentation tool. In the segmentation tool, disabling this option can significantly improve the inference speed but might result in the absence of accurate scoring for regions.

Parameters:

infer_score – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

SegmentationInferenceParameters the reference of this object.

Unsuper Segmentation Training Parameters#

class UnsuperSegmentationInputShape : public visionflow::param::ISchemable#

UnsuperSegmentationInputShape Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

bool get_enable() const#

Get Enable.

Enable this parameter group.

See also

set_enable()

Returns:

bool Enable

UnsuperSegmentationInputShape &set_enable(bool enable)#

Set Enable with bool value.

Enable this parameter group.

See also

get_enable()

Parameters:

enable – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

UnsuperSegmentationInputShape the reference of this object.

int get_sampling_width() const#

Get Sampling Input Width.

Sampling Input Width

Returns:

int Sampling Input Width

UnsuperSegmentationInputShape &set_sampling_width(int sampling_width)#

Set Sampling Input Width with int value.

Sampling Input Width

Parameters:

sampling_width – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

UnsuperSegmentationInputShape the reference of this object.

int get_sampling_height() const#

Get Sampling Input Height.

Sampling Input Height

Returns:

int Sampling Input Height

UnsuperSegmentationInputShape &set_sampling_height(int sampling_height)#

Set Sampling Input Height with int value.

Sampling Input Height

Parameters:

sampling_height – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

UnsuperSegmentationInputShape the reference of this object.

class UnsuperSegmentationTrainingParameters : public visionflow::param::SchemableParameter#

UnsuperSegmentationTrainingParameters Parameter class generated by jinja2 automatically.

Unsuper Segmentation Training Parameters Group.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

int get_epoch() const#

Get Epochs.

Number of iterations to train. 1 Epoch means all selected images will be trained for 1 time.

See also

set_epoch()

Returns:

int Epochs

UnsuperSegmentationTrainingParameters &set_epoch(int epoch)#

Set Epochs with int value.

Number of iterations to train. 1 Epoch means all selected images will be trained for 1 time.

See also

get_epoch()

Parameters:

epoch – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

UnsuperSegmentationTrainingParameters the reference of this object.

int get_batch_size() const#

Get Batch Size.

The number of images involved in training in each iteration of network training. A suitable batch size can make full use of hardware and improve the convergence speed. Common values are 4, 8, and 16. The classification module needs to be set larger, generally 32, 64

See also

set_batch_size()

Returns:

int Batch Size

UnsuperSegmentationTrainingParameters &set_batch_size(int batch_size)#

Set Batch Size with int value.

The number of images involved in training in each iteration of network training. A suitable batch size can make full use of hardware and improve the convergence speed. Common values are 4, 8, and 16. The classification module needs to be set larger, generally 32, 64

See also

get_batch_size()

Parameters:

batch_size – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

UnsuperSegmentationTrainingParameters the reference of this object.

const UnsuperSegmentationSamplingParameters &get_sampling_strategy() const#

Get Sampling Strategy.

Sampling Parameters

Returns:

const UnsuperSegmentationSamplingParameters & Sampling Strategy

UnsuperSegmentationTrainingParameters &set_sampling_strategy(UnsuperSegmentationSamplingParameters sampling_strategy)#

Set Sampling Strategy with UnsuperSegmentationSamplingParameters value.

Sampling Parameters

Parameters:

sampling_strategy – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

UnsuperSegmentationTrainingParameters the reference of this object.

UnsuperSegmentationSamplingParameters &get_sampling_strategy()#

Get mutable reference of Sampling Strategy.

Sampling Parameters

Returns:

UnsuperSegmentationTrainingParameters& the mutable reference of the group.

const UnsuperSegmentationModelParameters &get_model_param() const#

Get Model Parameters.

Model Parameters

Returns:

const UnsuperSegmentationModelParameters & Model Parameters

UnsuperSegmentationTrainingParameters &set_model_param(UnsuperSegmentationModelParameters model_param)#

Set Model Parameters with UnsuperSegmentationModelParameters value.

Model Parameters

Parameters:

model_param – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

UnsuperSegmentationTrainingParameters the reference of this object.

UnsuperSegmentationModelParameters &get_model_param()#

Get mutable reference of Model Parameters.

Model Parameters

Returns:

UnsuperSegmentationTrainingParameters& the mutable reference of the group.

const DataAugmentation &get_augmentations() const#

Get Data Augmentation.

Data Augmentation Parameters

Returns:

const DataAugmentation & Data Augmentation

UnsuperSegmentationTrainingParameters &set_augmentations(DataAugmentation augmentations)#

Set Data Augmentation with DataAugmentation value.

Data Augmentation Parameters

Parameters:

augmentations – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

UnsuperSegmentationTrainingParameters the reference of this object.

DataAugmentation &get_augmentations()#

Get mutable reference of Data Augmentation.

Data Augmentation Parameters

Returns:

UnsuperSegmentationTrainingParameters& the mutable reference of the group.

class UnsuperSegmentationSamplingParameters : public visionflow::param::ISchemable#

UnsuperSegmentationSamplingParameters Parameter class generated by jinja2 automatically.

Unsuper Segmentation Training Sample Parameters Group.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

const UnsuperSegmentationInputShape &get_sampling_input_shape() const#

Get Customize Network Input Shape.

Custom model input size. When this parameter group is enabled, input images will be resized to the custom size before training.

Returns:

const UnsuperSegmentationInputShape & Customize Network Input Shape

UnsuperSegmentationSamplingParameters &set_sampling_input_shape(UnsuperSegmentationInputShape sampling_input_shape)#

Set Customize Network Input Shape with UnsuperSegmentationInputShape value.

Custom model input size. When this parameter group is enabled, input images will be resized to the custom size before training.

Parameters:

sampling_input_shape – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

UnsuperSegmentationSamplingParameters the reference of this object.

UnsuperSegmentationInputShape &get_sampling_input_shape()#

Get mutable reference of Customize Network Input Shape.

Custom model input size. When this parameter group is enabled, input images will be resized to the custom size before training.

Returns:

UnsuperSegmentationSamplingParameters& the mutable reference of the group.

bool get_local_sampling() const#

Get Local Sampling Strategy.

when enable : Crop a patch(Input Shape) of image to train instead of whole image, increasing train speed but might make performance decline when image is complex

Returns:

bool Local Sampling Strategy

UnsuperSegmentationSamplingParameters &set_local_sampling(bool local_sampling)#

Set Local Sampling Strategy with bool value.

when enable : Crop a patch(Input Shape) of image to train instead of whole image, increasing train speed but might make performance decline when image is complex

Parameters:

local_sampling – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

UnsuperSegmentationSamplingParameters the reference of this object.

int get_sampling_resolution() const#

Get Sampling Resolution Level.

The short side of the image input will be scaled to (Sampling Input Size * Sampling Resolution), and the long side will be scaled proportionally.

Returns:

int Sampling Resolution Level

UnsuperSegmentationSamplingParameters &set_sampling_resolution(int sampling_resolution)#

Set Sampling Resolution Level with int value.

The short side of the image input will be scaled to (Sampling Input Size * Sampling Resolution), and the long side will be scaled proportionally.

Parameters:

sampling_resolution – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

UnsuperSegmentationSamplingParameters the reference of this object.

bool get_image_consistent_optimize() const#

Get High Consistent Image.

Enable when image looks like the same in all region, such as texture image, it helps speed up train and might get better performance in such kind of image

Returns:

bool High Consistent Image

UnsuperSegmentationSamplingParameters &set_image_consistent_optimize(bool image_consistent_optimize)#

Set High Consistent Image with bool value.

Enable when image looks like the same in all region, such as texture image, it helps speed up train and might get better performance in such kind of image

Parameters:

image_consistent_optimize – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

UnsuperSegmentationSamplingParameters the reference of this object.

class UnsuperSegmentationModelParameters : public visionflow::param::ISchemable#

UnsuperSegmentationModelParameters Parameter class generated by jinja2 automatically.

Unsuper Segmentation Model Parameters Group.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

const std::string &get_model_arch() const#

Get Model Architecture.

High-Precision-Model training slow but get better result, using for complex image; Training Fast Model training fast but might get worse performance than High-Precision-Model

See also

set_model_arch()

Returns:

const std::string & Model Architecture

UnsuperSegmentationModelParameters &set_model_arch(std::string model_arch)#

Set Model Architecture with std::string value.

High-Precision-Model training slow but get better result, using for complex image; Training Fast Model training fast but might get worse performance than High-Precision-Model

See also

get_model_arch()

Parameters:

model_arch – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

UnsuperSegmentationModelParameters the reference of this object.

bool get_add_logical_model() const#

Get Logical Defect Detect.

increase detect performance for logical defect,such as character lost or duplicate, but increasing training and inference speed

Returns:

bool Logical Defect Detect

UnsuperSegmentationModelParameters &set_add_logical_model(bool add_logical_model)#

Set Logical Defect Detect with bool value.

increase detect performance for logical defect,such as character lost or duplicate, but increasing training and inference speed

Parameters:

add_logical_model – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

UnsuperSegmentationModelParameters the reference of this object.

Unsuper Classification Training Parameters#

class UnsuperClassificationInputShape : public visionflow::param::ISchemable#

UnsuperClassificationInputShape Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

bool get_enable() const#

Get Enable.

Enable this parameter group.

See also

set_enable()

Returns:

bool Enable

UnsuperClassificationInputShape &set_enable(bool enable)#

Set Enable with bool value.

Enable this parameter group.

See also

get_enable()

Parameters:

enable – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

UnsuperClassificationInputShape the reference of this object.

int get_base_input_width() const#

Get Base Input Width.

Base Input Width

Returns:

int Base Input Width

UnsuperClassificationInputShape &set_base_input_width(int base_input_width)#

Set Base Input Width with int value.

Base Input Width

Parameters:

base_input_width – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

UnsuperClassificationInputShape the reference of this object.

int get_base_input_height() const#

Get Base Input Height.

Base Input Height

Returns:

int Base Input Height

UnsuperClassificationInputShape &set_base_input_height(int base_input_height)#

Set Base Input Height with int value.

Base Input Height

Parameters:

base_input_height – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

UnsuperClassificationInputShape the reference of this object.

class UnsuperClassificationTrainingParameters : public visionflow::param::SchemableParameter#

UnsuperClassificationTrainingParameters Parameter class generated by jinja2 automatically.

Unsuper Classification Training Parameters Group.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

int get_epoch() const#

Get Epochs.

Number of iterations to train. 1 Epoch means all selected images will be trained for 1 time.

See also

set_epoch()

Returns:

int Epochs

UnsuperClassificationTrainingParameters &set_epoch(int epoch)#

Set Epochs with int value.

Number of iterations to train. 1 Epoch means all selected images will be trained for 1 time.

See also

get_epoch()

Parameters:

epoch – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

UnsuperClassificationTrainingParameters the reference of this object.

int get_batch_size() const#

Get Training Batch Size.

The number of images involved in training in each iteration of network training. A suitable batch size can make full use of hardware and improve the convergence speed. Common values are 4, 8, and 16. The classification module needs to be set larger, generally 32, 64

See also

set_batch_size()

Returns:

int Training Batch Size

UnsuperClassificationTrainingParameters &set_batch_size(int batch_size)#

Set Training Batch Size with int value.

The number of images involved in training in each iteration of network training. A suitable batch size can make full use of hardware and improve the convergence speed. Common values are 4, 8, and 16. The classification module needs to be set larger, generally 32, 64

See also

get_batch_size()

Parameters:

batch_size – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

UnsuperClassificationTrainingParameters the reference of this object.

const UnsuperClassificationInputShape &get_input_shape() const#

Get Customize Network Input Shape.

Custom model input size. When this parameter group is enabled, input images will be resized to the custom size before training.

Returns:

const UnsuperClassificationInputShape & Customize Network Input Shape

UnsuperClassificationTrainingParameters &set_input_shape(UnsuperClassificationInputShape input_shape)#

Set Customize Network Input Shape with UnsuperClassificationInputShape value.

Custom model input size. When this parameter group is enabled, input images will be resized to the custom size before training.

Parameters:

input_shape – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

UnsuperClassificationTrainingParameters the reference of this object.

UnsuperClassificationInputShape &get_input_shape()#

Get mutable reference of Customize Network Input Shape.

Custom model input size. When this parameter group is enabled, input images will be resized to the custom size before training.

Returns:

UnsuperClassificationTrainingParameters& the mutable reference of the group.

const std::string &get_model_arch() const#

Get Model Architecture.

Currently only one baseline model

See also

set_model_arch()

Returns:

const std::string & Model Architecture

UnsuperClassificationTrainingParameters &set_model_arch(std::string model_arch)#

Set Model Architecture with std::string value.

Currently only one baseline model

See also

get_model_arch()

Parameters:

model_arch – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

UnsuperClassificationTrainingParameters the reference of this object.

const DataAugmentation &get_augmentations() const#

Get Data Augmentation.

Data Augmentation Parameters

Returns:

const DataAugmentation & Data Augmentation

UnsuperClassificationTrainingParameters &set_augmentations(DataAugmentation augmentations)#

Set Data Augmentation with DataAugmentation value.

Data Augmentation Parameters

Parameters:

augmentations – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

UnsuperClassificationTrainingParameters the reference of this object.

DataAugmentation &get_augmentations()#

Get mutable reference of Data Augmentation.

Data Augmentation Parameters

Returns:

UnsuperClassificationTrainingParameters& the mutable reference of the group.

Unsuper Segmentation Inference Parameters#

class UnsuperDefectRadius : public visionflow::param::ISchemable#

UnsuperDefectRadius Parameter class generated by jinja2 automatically.

Parameters using for define defect size

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

bool get_auto_set() const#

Get Automatic Setting.

Network adjust defect radius automatically

See also

set_auto_set()

Returns:

bool Automatic Setting

UnsuperDefectRadius &set_auto_set(bool auto_set)#

Set Automatic Setting with bool value.

Network adjust defect radius automatically

See also

get_auto_set()

Parameters:

auto_set – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

UnsuperDefectRadius the reference of this object.

int get_size() const#

Get Defect Radius.

Defect radius size

See also

set_size()

Returns:

int Defect Radius

UnsuperDefectRadius &set_size(int size)#

Set Defect Radius with int value.

Defect radius size

See also

get_size()

Parameters:

size – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

UnsuperDefectRadius the reference of this object.

class UnsuperSegmentationInferenceParameters : public visionflow::param::SchemableParameter#

UnsuperSegmentationInferenceParameters Parameter class generated by jinja2 automatically.

UnsuperSegmentationInferenceParameters

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

int get_minimum_defect_size() const#

Get Minimum Defect Size.

Minimum detect that customer want to detect, but too small will increase overkill

Returns:

int Minimum Defect Size

UnsuperSegmentationInferenceParameters &set_minimum_defect_size(int minimum_defect_size)#

Set Minimum Defect Size with int value.

Minimum detect that customer want to detect, but too small will increase overkill

Parameters:

minimum_defect_size – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

UnsuperSegmentationInferenceParameters the reference of this object.

int get_sampling_density() const#

Get Sampling Density.

smaller value will make result more precise, but increase inference time

Returns:

int Sampling Density

UnsuperSegmentationInferenceParameters &set_sampling_density(int sampling_density)#

Set Sampling Density with int value.

smaller value will make result more precise, but increase inference time

Parameters:

sampling_density – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

UnsuperSegmentationInferenceParameters the reference of this object.

Unsuper Classification Inference Parameters#

class UnsuperClassificationInferenceParameters : public visionflow::param::SchemableParameter#

UnsuperClassificationInferenceParameters Parameter class generated by jinja2 automatically.

Parameters using for unsuper classification inference

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

double get_ng_thresh() const#

Get NG Threshold.

Image will be set to ok when score < NG Threshold, and set to ng when score > NG Threshold

See also

set_ng_thresh()

Returns:

double NG Threshold

UnsuperClassificationInferenceParameters &set_ng_thresh(double ng_thresh)#

Set NG Threshold with double value.

Image will be set to ok when score < NG Threshold, and set to ng when score > NG Threshold

See also

get_ng_thresh()

Parameters:

ng_thresh – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

UnsuperClassificationInferenceParameters the reference of this object.

const UnsuperDefectRadius &get_defect_radius() const#

Get Defect Radius.

Expected defect size

Returns:

const UnsuperDefectRadius & Defect Radius

UnsuperClassificationInferenceParameters &set_defect_radius(UnsuperDefectRadius defect_radius)#

Set Defect Radius with UnsuperDefectRadius value.

Expected defect size

Parameters:

defect_radius – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

UnsuperClassificationInferenceParameters the reference of this object.

UnsuperDefectRadius &get_defect_radius()#

Get mutable reference of Defect Radius.

Expected defect size

Returns:

UnsuperClassificationInferenceParameters& the mutable reference of the group.

Filter Parameters#

class AxialSideLengthRange : public visionflow::param::ISchemable#

AxialSideLengthRange Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

bool get_enable() const#

Get Enable.

Enable this parameter group.

See also

set_enable()

Returns:

bool Enable

AxialSideLengthRange &set_enable(bool enable)#

Set Enable with bool value.

Enable this parameter group.

See also

get_enable()

Parameters:

enable – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

AxialSideLengthRange the reference of this object.

const std::vector<int> &get_x_axis_side_range() const#

Get X-Axis Side Length Range.

The X-axis side length range of regions you want to keep.

Returns:

const std::vector<int> & X-Axis Side Length Range

AxialSideLengthRange &set_x_axis_side_range(std::vector<int> x_axis_side_range)#

Set X-Axis Side Length Range with std::vector<int> value.

The X-axis side length range of regions you want to keep.

Parameters:

x_axis_side_range – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

AxialSideLengthRange the reference of this object.

bool x_axis_side_range_contains(int value) const#

Check if the X-Axis Side Length Range contains the value.

Returns:

bool true if the X-Axis Side Length Range contains the value, otherwise false.

int get_x_axis_side_range_left() const#

Get left point value of X-Axis Side Length Range.

Returns:

const std::vector<int> & left point value of X-Axis Side Length Range

int get_x_axis_side_range_right() const#

Get the right point value of X-Axis Side Length Range.

Returns:

const std::vector<int> & the right point value of X-Axis Side Length Range

AxialSideLengthRange &set_x_axis_side_range_left(int x_axis_side_range_left)#

Set left point value of X-Axis Side Length Range with std::vector<int> value.

The X-axis side length range of regions you want to keep.

Parameters:

x_axis_side_range_left – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

AxialSideLengthRange the reference of this object.

AxialSideLengthRange &set_x_axis_side_range_right(int x_axis_side_range_right)#

Set the right point value of X-Axis Side Length Range with std::vector<int> value.

The X-axis side length range of regions you want to keep.

Parameters:

x_axis_side_range_right – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

AxialSideLengthRange the reference of this object.

const std::vector<int> &get_y_axis_side_range() const#

Get Y-Axis Side Length Range.

The Y-axis side length range of regions you want to keep.

Returns:

const std::vector<int> & Y-Axis Side Length Range

AxialSideLengthRange &set_y_axis_side_range(std::vector<int> y_axis_side_range)#

Set Y-Axis Side Length Range with std::vector<int> value.

The Y-axis side length range of regions you want to keep.

Parameters:

y_axis_side_range – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

AxialSideLengthRange the reference of this object.

bool y_axis_side_range_contains(int value) const#

Check if the Y-Axis Side Length Range contains the value.

Returns:

bool true if the Y-Axis Side Length Range contains the value, otherwise false.

int get_y_axis_side_range_left() const#

Get left point value of Y-Axis Side Length Range.

Returns:

const std::vector<int> & left point value of Y-Axis Side Length Range

int get_y_axis_side_range_right() const#

Get the right point value of Y-Axis Side Length Range.

Returns:

const std::vector<int> & the right point value of Y-Axis Side Length Range

AxialSideLengthRange &set_y_axis_side_range_left(int y_axis_side_range_left)#

Set left point value of Y-Axis Side Length Range with std::vector<int> value.

The Y-axis side length range of regions you want to keep.

Parameters:

y_axis_side_range_left – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

AxialSideLengthRange the reference of this object.

AxialSideLengthRange &set_y_axis_side_range_right(int y_axis_side_range_right)#

Set the right point value of Y-Axis Side Length Range with std::vector<int> value.

The Y-axis side length range of regions you want to keep.

Parameters:

y_axis_side_range_right – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

AxialSideLengthRange the reference of this object.

const std::vector<double> &get_x_y_ratio_range() const#

Get X/Y Ratio Range.

The range of the ratio of X-axis side length to the Y-axis side length of the regions that you want to keep.

Returns:

const std::vector<double> & X/Y Ratio Range

AxialSideLengthRange &set_x_y_ratio_range(std::vector<double> x_y_ratio_range)#

Set X/Y Ratio Range with std::vector<double> value.

The range of the ratio of X-axis side length to the Y-axis side length of the regions that you want to keep.

Parameters:

x_y_ratio_range – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

AxialSideLengthRange the reference of this object.

bool x_y_ratio_range_contains(double value) const#

Check if the X/Y Ratio Range contains the value.

Returns:

bool true if the X/Y Ratio Range contains the value, otherwise false.

double get_x_y_ratio_range_left() const#

Get left point value of X/Y Ratio Range.

Returns:

const std::vector<double> & left point value of X/Y Ratio Range

double get_x_y_ratio_range_right() const#

Get the right point value of X/Y Ratio Range.

Returns:

const std::vector<double> & the right point value of X/Y Ratio Range

AxialSideLengthRange &set_x_y_ratio_range_left(double x_y_ratio_range_left)#

Set left point value of X/Y Ratio Range with std::vector<double> value.

The range of the ratio of X-axis side length to the Y-axis side length of the regions that you want to keep.

Parameters:

x_y_ratio_range_left – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

AxialSideLengthRange the reference of this object.

AxialSideLengthRange &set_x_y_ratio_range_right(double x_y_ratio_range_right)#

Set the right point value of X/Y Ratio Range with std::vector<double> value.

The range of the ratio of X-axis side length to the Y-axis side length of the regions that you want to keep.

Parameters:

x_y_ratio_range_right – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

AxialSideLengthRange the reference of this object.

class SideLengthRange : public visionflow::param::ISchemable#

SideLengthRange Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

bool get_enable() const#

Get Enable.

Enable this parameter group.

See also

set_enable()

Returns:

bool Enable

SideLengthRange &set_enable(bool enable)#

Set Enable with bool value.

Enable this parameter group.

See also

get_enable()

Parameters:

enable – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

SideLengthRange the reference of this object.

bool get_on_rotate_rect() const#

Get Filter On Min-Area-Rect.

The “Longer Side Length Range” and “Shorter Side Length Range” will be applied to the min-area rotate rectangle of each region if this option is enabled, otherwise, they will be applied to the axial bounding rect.

Returns:

bool Filter On Min-Area-Rect

SideLengthRange &set_on_rotate_rect(bool on_rotate_rect)#

Set Filter On Min-Area-Rect with bool value.

The “Longer Side Length Range” and “Shorter Side Length Range” will be applied to the min-area rotate rectangle of each region if this option is enabled, otherwise, they will be applied to the axial bounding rect.

Parameters:

on_rotate_rect – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

SideLengthRange the reference of this object.

const std::vector<int> &get_longer_side_range() const#

Get Longer Side Length Range.

The longer side length range of regions you want to keep.

Returns:

const std::vector<int> & Longer Side Length Range

SideLengthRange &set_longer_side_range(std::vector<int> longer_side_range)#

Set Longer Side Length Range with std::vector<int> value.

The longer side length range of regions you want to keep.

Parameters:

longer_side_range – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

SideLengthRange the reference of this object.

bool longer_side_range_contains(int value) const#

Check if the Longer Side Length Range contains the value.

Returns:

bool true if the Longer Side Length Range contains the value, otherwise false.

int get_longer_side_range_left() const#

Get left point value of Longer Side Length Range.

Returns:

const std::vector<int> & left point value of Longer Side Length Range

int get_longer_side_range_right() const#

Get the right point value of Longer Side Length Range.

Returns:

const std::vector<int> & the right point value of Longer Side Length Range

SideLengthRange &set_longer_side_range_left(int longer_side_range_left)#

Set left point value of Longer Side Length Range with std::vector<int> value.

The longer side length range of regions you want to keep.

Parameters:

longer_side_range_left – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

SideLengthRange the reference of this object.

SideLengthRange &set_longer_side_range_right(int longer_side_range_right)#

Set the right point value of Longer Side Length Range with std::vector<int> value.

The longer side length range of regions you want to keep.

Parameters:

longer_side_range_right – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

SideLengthRange the reference of this object.

const std::vector<int> &get_shorter_side_range() const#

Get Shorter Side Length Range.

The shorter side length range of regions you want to keep.

Returns:

const std::vector<int> & Shorter Side Length Range

SideLengthRange &set_shorter_side_range(std::vector<int> shorter_side_range)#

Set Shorter Side Length Range with std::vector<int> value.

The shorter side length range of regions you want to keep.

Parameters:

shorter_side_range – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

SideLengthRange the reference of this object.

bool shorter_side_range_contains(int value) const#

Check if the Shorter Side Length Range contains the value.

Returns:

bool true if the Shorter Side Length Range contains the value, otherwise false.

int get_shorter_side_range_left() const#

Get left point value of Shorter Side Length Range.

Returns:

const std::vector<int> & left point value of Shorter Side Length Range

int get_shorter_side_range_right() const#

Get the right point value of Shorter Side Length Range.

Returns:

const std::vector<int> & the right point value of Shorter Side Length Range

SideLengthRange &set_shorter_side_range_left(int shorter_side_range_left)#

Set left point value of Shorter Side Length Range with std::vector<int> value.

The shorter side length range of regions you want to keep.

Parameters:

shorter_side_range_left – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

SideLengthRange the reference of this object.

SideLengthRange &set_shorter_side_range_right(int shorter_side_range_right)#

Set the right point value of Shorter Side Length Range with std::vector<int> value.

The shorter side length range of regions you want to keep.

Parameters:

shorter_side_range_right – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

SideLengthRange the reference of this object.

const std::vector<double> &get_aspect_ratio_range() const#

Get Aspect Ratio Range.

The range of the ratio of the short side to the long side of the regions that you want to keep.

Returns:

const std::vector<double> & Aspect Ratio Range

SideLengthRange &set_aspect_ratio_range(std::vector<double> aspect_ratio_range)#

Set Aspect Ratio Range with std::vector<double> value.

The range of the ratio of the short side to the long side of the regions that you want to keep.

Parameters:

aspect_ratio_range – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

SideLengthRange the reference of this object.

bool aspect_ratio_range_contains(double value) const#

Check if the Aspect Ratio Range contains the value.

Returns:

bool true if the Aspect Ratio Range contains the value, otherwise false.

double get_aspect_ratio_range_left() const#

Get left point value of Aspect Ratio Range.

Returns:

const std::vector<double> & left point value of Aspect Ratio Range

double get_aspect_ratio_range_right() const#

Get the right point value of Aspect Ratio Range.

Returns:

const std::vector<double> & the right point value of Aspect Ratio Range

SideLengthRange &set_aspect_ratio_range_left(double aspect_ratio_range_left)#

Set left point value of Aspect Ratio Range with std::vector<double> value.

The range of the ratio of the short side to the long side of the regions that you want to keep.

Parameters:

aspect_ratio_range_left – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

SideLengthRange the reference of this object.

SideLengthRange &set_aspect_ratio_range_right(double aspect_ratio_range_right)#

Set the right point value of Aspect Ratio Range with std::vector<double> value.

The range of the ratio of the short side to the long side of the regions that you want to keep.

Parameters:

aspect_ratio_range_right – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

SideLengthRange the reference of this object.

class FilterScript : public visionflow::param::ISchemable#

FilterScript Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

bool get_enable() const#

Get Enable.

Enable this parameter group.

See also

set_enable()

Returns:

bool Enable

FilterScript &set_enable(bool enable)#

Set Enable with bool value.

Enable this parameter group.

See also

get_enable()

Parameters:

enable – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

FilterScript the reference of this object.

const std::string &get_filter_script() const#

Get Filter Script.

The python filter script.

Returns:

const std::string & Filter Script

FilterScript &set_filter_script(std::string filter_script)#

Set Filter Script with std::string value.

The python filter script.

Parameters:

filter_script – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

FilterScript the reference of this object.

class SingleClassPolygonsFilterParameters : public visionflow::param::ISchemable#

SingleClassPolygonsFilterParameters Parameter class generated by jinja2 automatically.

Common Regions filter parameters to filter regions.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

bool get_enable() const#

Get Enable.

Enable this parameter group.

See also

set_enable()

Returns:

bool Enable

SingleClassPolygonsFilterParameters &set_enable(bool enable)#

Set Enable with bool value.

Enable this parameter group.

See also

get_enable()

Parameters:

enable – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

SingleClassPolygonsFilterParameters the reference of this object.

double get_score_threshold() const#

Get Score Threshold.

Only retains regions with score greater than this threshold.

Returns:

double Score Threshold

SingleClassPolygonsFilterParameters &set_score_threshold(double score_threshold)#

Set Score Threshold with double value.

Only retains regions with score greater than this threshold.

Parameters:

score_threshold – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

SingleClassPolygonsFilterParameters the reference of this object.

const std::vector<int> &get_area_range() const#

Get Area Range.

The area range of the regions you want to keep

See also

set_area_range()

Returns:

const std::vector<int> & Area Range

SingleClassPolygonsFilterParameters &set_area_range(std::vector<int> area_range)#

Set Area Range with std::vector<int> value.

The area range of the regions you want to keep

See also

get_area_range()

Parameters:

area_range – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

SingleClassPolygonsFilterParameters the reference of this object.

bool area_range_contains(int value) const#

Check if the Area Range contains the value.

Returns:

bool true if the Area Range contains the value, otherwise false.

int get_area_range_left() const#

Get left point value of Area Range.

Returns:

const std::vector<int> & left point value of Area Range

int get_area_range_right() const#

Get the right point value of Area Range.

Returns:

const std::vector<int> & the right point value of Area Range

SingleClassPolygonsFilterParameters &set_area_range_left(int area_range_left)#

Set left point value of Area Range with std::vector<int> value.

The area range of the regions you want to keep

Parameters:

area_range_left – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

SingleClassPolygonsFilterParameters the reference of this object.

SingleClassPolygonsFilterParameters &set_area_range_right(int area_range_right)#

Set the right point value of Area Range with std::vector<int> value.

The area range of the regions you want to keep

Parameters:

area_range_right – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

SingleClassPolygonsFilterParameters the reference of this object.

const AxialSideLengthRange &get_axial_side_filter() const#

Get Axial-Side-Length Filter.

Filter regions with X/Y-axis side length.

Returns:

const AxialSideLengthRange & Axial-Side-Length Filter

SingleClassPolygonsFilterParameters &set_axial_side_filter(AxialSideLengthRange axial_side_filter)#

Set Axial-Side-Length Filter with AxialSideLengthRange value.

Filter regions with X/Y-axis side length.

Parameters:

axial_side_filter – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

SingleClassPolygonsFilterParameters the reference of this object.

AxialSideLengthRange &get_axial_side_filter()#

Get mutable reference of Axial-Side-Length Filter.

Filter regions with X/Y-axis side length.

Returns:

SingleClassPolygonsFilterParameters& the mutable reference of the group.

const SideLengthRange &get_side_filter() const#

Get Side-Length Filter.

Filter regions with Side length

Returns:

const SideLengthRange & Side-Length Filter

SingleClassPolygonsFilterParameters &set_side_filter(SideLengthRange side_filter)#

Set Side-Length Filter with SideLengthRange value.

Filter regions with Side length

Parameters:

side_filter – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

SingleClassPolygonsFilterParameters the reference of this object.

SideLengthRange &get_side_filter()#

Get mutable reference of Side-Length Filter.

Filter regions with Side length

Returns:

SingleClassPolygonsFilterParameters& the mutable reference of the group.

class PolygonsFilterParameters : public visionflow::param::SchemableParameter#

PolygonsFilterParameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

const std::map<std::string, SingleClassPolygonsFilterParameters> &get_class_thresholds() const#

Get Class Polygon Thresholds.

Polygon thresholds (area, side-length,etc.) named with the label classes according to which to filter the polygons.

Returns:

const std::map<std::string, SingleClassPolygonsFilterParameters> & Class Polygon Thresholds

PolygonsFilterParameters &set_class_thresholds(std::map<std::string, SingleClassPolygonsFilterParameters> class_thresholds)#

Set Class Polygon Thresholds with std::map<std::string, SingleClassPolygonsFilterParameters> value.

Polygon thresholds (area, side-length,etc.) named with the label classes according to which to filter the polygons.

Parameters:

class_thresholds – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

PolygonsFilterParameters the reference of this object.

const SingleClassPolygonsFilterParameters &get_class_thresholds(const std::string &key) const#

Get value in Class Polygon Thresholds with key.

Warning

The key must be exist in Class Polygon Thresholds. otherwise, the behavior is undefined and will cause segmentation fault.

Returns:

const std::map<std::string, SingleClassPolygonsFilterParameters> & value in Class Polygon Thresholds at key.

PolygonsFilterParameters &set_class_thresholds(const std::string &key, SingleClassPolygonsFilterParameters value)#

Set value in Class Polygon Thresholds with key.

Parameters:
  • key – the key to set.

  • value – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

PolygonsFilterParameters the reference of this object.

bool class_thresholds_contains(const std::string &key) const#

Check if the key is exist in Class Polygon Thresholds.

Returns:

bool true if the key is exist in Class Polygon Thresholds, otherwise false.

size_t get_class_thresholds_size() const#

Get the size of Class Polygon Thresholds.

Returns:

size_t the size of Class Polygon Thresholds

SingleClassPolygonsFilterParameters &get_class_thresholds(const std::string &key)#

Get mutable reference of value in Class Polygon Thresholds with key. A new key and default value will be created if the key does not exist.

Returns:

SingleClassPolygonsFilterParameters& the mutable reference of value in Class Polygon Thresholds at key.

const SingleClassPolygonsFilterParameters &get_additional_threshold() const#

Get Additional Probability Thresholds.

Additional polygon threshold for other label classes not in “Class Polygon Thresholds”. The filter operator will filter all feature maps whose label class is not in “Class Polygon Thresholds” with the additional threshold.

Returns:

const SingleClassPolygonsFilterParameters & Additional Probability Thresholds

PolygonsFilterParameters &set_additional_threshold(SingleClassPolygonsFilterParameters additional_threshold)#

Set Additional Probability Thresholds with SingleClassPolygonsFilterParameters value.

Additional polygon threshold for other label classes not in “Class Polygon Thresholds”. The filter operator will filter all feature maps whose label class is not in “Class Polygon Thresholds” with the additional threshold.

Parameters:

additional_threshold – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

PolygonsFilterParameters the reference of this object.

SingleClassPolygonsFilterParameters &get_additional_threshold()#

Get mutable reference of Additional Probability Thresholds.

Additional polygon threshold for other label classes not in “Class Polygon Thresholds”. The filter operator will filter all feature maps whose label class is not in “Class Polygon Thresholds” with the additional threshold.

Returns:

PolygonsFilterParameters& the mutable reference of the group.

const FilterScript &get_script_filter() const#

Get Custom python filter script.

Filter regions with customized python script.

Returns:

const FilterScript & Custom python filter script

PolygonsFilterParameters &set_script_filter(FilterScript script_filter)#

Set Custom python filter script with FilterScript value.

Filter regions with customized python script.

Parameters:

script_filter – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

PolygonsFilterParameters the reference of this object.

FilterScript &get_script_filter()#

Get mutable reference of Custom python filter script.

Filter regions with customized python script.

Returns:

PolygonsFilterParameters& the mutable reference of the group.

const std::map<std::string, TypeValuePair> &get_user_vars() const#

Get User Defined Variables.

The key of the map is the name of the python object and the value of the map is a pair of string which means type-value of the python object.

See also

set_user_vars()

Returns:

const std::map<std::string, TypeValuePair> & User Defined Variables

PolygonsFilterParameters &set_user_vars(std::map<std::string, TypeValuePair> user_vars)#

Set User Defined Variables with std::map<std::string, TypeValuePair> value.

The key of the map is the name of the python object and the value of the map is a pair of string which means type-value of the python object.

See also

get_user_vars()

Parameters:

user_vars – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

PolygonsFilterParameters the reference of this object.

const TypeValuePair &get_user_vars(const std::string &key) const#

Get value in User Defined Variables with key.

Warning

The key must be exist in User Defined Variables. otherwise, the behavior is undefined and will cause segmentation fault.

Returns:

const std::map<std::string, TypeValuePair> & value in User Defined Variables at key.

PolygonsFilterParameters &set_user_vars(const std::string &key, TypeValuePair value)#

Set value in User Defined Variables with key.

Parameters:
  • key – the key to set.

  • value – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

PolygonsFilterParameters the reference of this object.

bool user_vars_contains(const std::string &key) const#

Check if the key is exist in User Defined Variables.

Returns:

bool true if the key is exist in User Defined Variables, otherwise false.

size_t get_user_vars_size() const#

Get the size of User Defined Variables.

Returns:

size_t the size of User Defined Variables

TypeValuePair &get_user_vars(const std::string &key)#

Get mutable reference of value in User Defined Variables with key. A new key and default value will be created if the key does not exist.

Returns:

TypeValuePair& the mutable reference of value in User Defined Variables at key.

class FeatureMapFilterParameters : public visionflow::param::SchemableParameter#

FeatureMapFilterParameters Parameter class generated by jinja2 automatically.

Parameters to config the feature map filter.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

const std::map<std::string, double> &get_class_thresholds() const#

Get Class Probability Thresholds.

Thresholds named with the label classes according to which to binarize the feature map.

Returns:

const std::map<std::string, double> & Class Probability Thresholds

FeatureMapFilterParameters &set_class_thresholds(std::map<std::string, double> class_thresholds)#

Set Class Probability Thresholds with std::map<std::string, double> value.

Thresholds named with the label classes according to which to binarize the feature map.

Parameters:

class_thresholds – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

FeatureMapFilterParameters the reference of this object.

double get_class_thresholds(const std::string &key) const#

Get value in Class Probability Thresholds with key.

Warning

The key must be exist in Class Probability Thresholds. otherwise, the behavior is undefined and will cause segmentation fault.

Returns:

const std::map<std::string, double> & value in Class Probability Thresholds at key.

FeatureMapFilterParameters &set_class_thresholds(const std::string &key, double value)#

Set value in Class Probability Thresholds with key.

Parameters:
  • key – the key to set.

  • value – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

FeatureMapFilterParameters the reference of this object.

bool class_thresholds_contains(const std::string &key) const#

Check if the key is exist in Class Probability Thresholds.

Returns:

bool true if the key is exist in Class Probability Thresholds, otherwise false.

size_t get_class_thresholds_size() const#

Get the size of Class Probability Thresholds.

Returns:

size_t the size of Class Probability Thresholds

double get_additional_threshold() const#

Get Additional Probability Thresholds.

Additional threshold for other label classes not in “Class Probability Thresholds”. The visionflow::opers::FeatureMapFilter will filter all feature maps whose label class is not in “Class Probability Thresholds” with the additional threshold.

Returns:

double Additional Probability Thresholds

FeatureMapFilterParameters &set_additional_threshold(double additional_threshold)#

Set Additional Probability Thresholds with double value.

Additional threshold for other label classes not in “Class Probability Thresholds”. The visionflow::opers::FeatureMapFilter will filter all feature maps whose label class is not in “Class Probability Thresholds” with the additional threshold.

Parameters:

additional_threshold – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

FeatureMapFilterParameters the reference of this object.

int get_dilate_pixels() const#

Get Dilate Pixels.

Dilate the filtered regions by the specified pixels. This option can be used to merge closely scattered defects together.

Returns:

int Dilate Pixels

FeatureMapFilterParameters &set_dilate_pixels(int dilate_pixels)#

Set Dilate Pixels with int value.

Dilate the filtered regions by the specified pixels. This option can be used to merge closely scattered defects together.

Parameters:

dilate_pixels – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

FeatureMapFilterParameters the reference of this object.

bool get_enable_polygon_score() const#

Get Calculate Defect Region Score.

Provide every defect region score(0~1), bigger value means the region has more possibility to be a defect

Returns:

bool Calculate Defect Region Score

FeatureMapFilterParameters &set_enable_polygon_score(bool enable_polygon_score)#

Set Calculate Defect Region Score with bool value.

Provide every defect region score(0~1), bigger value means the region has more possibility to be a defect

Parameters:

enable_polygon_score – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

FeatureMapFilterParameters the reference of this object.

Training logs#

class LossCurve : public visionflow::param::ISchemable#

LossCurve Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

const std::vector<double> &get_values() const#

Get values.

A loss curve

See also

set_values()

Returns:

const std::vector<double> & values

LossCurve &set_values(std::vector<double> values)#

Set values with std::vector<double> value.

A loss curve

See also

get_values()

Parameters:

values – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

LossCurve the reference of this object.

double get_values(size_t index) const#

Get value in values with index.

Warning

The index must be less than get_values_size(). otherwise, the behavior is undefined and will cause segmentation fault.

Returns:

double value in values at index.

size_t get_values_size() const#

Get the size of values.

Returns:

size_t the size of values

class TrainingLog : public visionflow::param::SchemableParameter#

TrainingLog Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

int64_t get_start_at() const#

Get Start Time.

The training task start time.

See also

set_start_at()

Returns:

int64_t Start Time

TrainingLog &set_start_at(int64_t start_at)#

Set Start Time with int64_t value.

The training task start time.

See also

get_start_at()

Parameters:

start_at – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

TrainingLog the reference of this object.

int64_t get_end_at() const#

Get End Time.

The training task finish time.

See also

set_end_at()

Returns:

int64_t End Time

TrainingLog &set_end_at(int64_t end_at)#

Set End Time with int64_t value.

The training task finish time.

See also

get_end_at()

Parameters:

end_at – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

TrainingLog the reference of this object.

const std::map<std::string, LossCurve> &get_loss() const#

Get Loss.

Loss curves with name. Note that curve named VFLOW-EPOCH-INDEX is the epoch index of each loss data, and note that VFLOW-EPOCH-INDEX is not exists in the data generated by the old version library.

See also

set_loss()

Returns:

const std::map<std::string, LossCurve> & Loss

TrainingLog &set_loss(std::map<std::string, LossCurve> loss)#

Set Loss with std::map<std::string, LossCurve> value.

Loss curves with name. Note that curve named VFLOW-EPOCH-INDEX is the epoch index of each loss data, and note that VFLOW-EPOCH-INDEX is not exists in the data generated by the old version library.

See also

get_loss()

Parameters:

loss – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

TrainingLog the reference of this object.

const LossCurve &get_loss(const std::string &key) const#

Get value in Loss with key.

Warning

The key must be exist in Loss. otherwise, the behavior is undefined and will cause segmentation fault.

Returns:

const std::map<std::string, LossCurve> & value in Loss at key.

TrainingLog &set_loss(const std::string &key, LossCurve value)#

Set value in Loss with key.

Parameters:
  • key – the key to set.

  • value – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

TrainingLog the reference of this object.

bool loss_contains(const std::string &key) const#

Check if the key is exist in Loss.

Returns:

bool true if the key is exist in Loss, otherwise false.

size_t get_loss_size() const#

Get the size of Loss.

Returns:

size_t the size of Loss

LossCurve &get_loss(const std::string &key)#

Get mutable reference of value in Loss with key. A new key and default value will be created if the key does not exist.

Returns:

LossCurve& the mutable reference of value in Loss at key.

Training Mode#

enum visionflow::param::TrainingMode#

Values:

enumerator kNormalTrain = 0#
enumerator kIncrementalTrain = 1#

Inference Type#

enum visionflow::param::InferType#

Values:

enumerator QuickStart = 1#
enumerator FastProcessing = 2#
enumerator FastProcessingHighPrecision = 3#

Ungrouped Parameters#

class InferenceBatchSize : public visionflow::param::SchemableParameter#

InferenceBatchSize Parameter class generated by jinja2 automatically.

Inference BatchSize and Inference Mode. Currently only contains batch size. It may need to be refactored in the future.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

int get_batch_size() const#

Get Inference Batch Size.

The batch size for inference. You can set it to the number of pictures you wish to infer at the same time. Usually the default value of 1 is sufficient. Note that if you set larger batches without giving enough images per inference, it may actually slow down inference.

See also

set_batch_size()

Returns:

int Inference Batch Size

InferenceBatchSize &set_batch_size(int batch_size)#

Set Inference Batch Size with int value.

The batch size for inference. You can set it to the number of pictures you wish to infer at the same time. Usually the default value of 1 is sufficient. Note that if you set larger batches without giving enough images per inference, it may actually slow down inference.

See also

get_batch_size()

Parameters:

batch_size – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

InferenceBatchSize the reference of this object.

const InferType &get_infer_mode() const#

Get Inference Mode.

The running mode of inference. The default value is QuickStart. The following options are available: ‘Quick Start’ mode start quickly but inference little slower;’Fast Processing High Precision’ mode initialize slower but inference faster; ‘Fast Processing’ mode initialize slower but inference fastest and maybe lose some accuracy.

See also

set_infer_mode()

Returns:

const InferType & Inference Mode

InferenceBatchSize &set_infer_mode(InferType infer_mode)#

Set Inference Mode with InferType value.

The running mode of inference. The default value is QuickStart. The following options are available: ‘Quick Start’ mode start quickly but inference little slower;’Fast Processing High Precision’ mode initialize slower but inference faster; ‘Fast Processing’ mode initialize slower but inference fastest and maybe lose some accuracy.

See also

get_infer_mode()

Parameters:

infer_mode – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

InferenceBatchSize the reference of this object.

class TRTCalibParameters : public visionflow::param::SchemableParameter#

TRTCalibParameters Parameter class generated by jinja2 automatically.

TensorRT Int8 Calibrator Parameters

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

bool get_place_holder() const#

Get PlaceHolder.

Returns:

bool PlaceHolder

TRTCalibParameters &set_place_holder(bool place_holder)#

Set PlaceHolder with bool value.

Parameters:

place_holder – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

TRTCalibParameters the reference of this object.

GeometrySearch Parameters#

enum visionflow::param::TemplateMode#

Values:

enumerator kValueByPixel = 0#
enumerator kValueByRatio = 1#
class KeyPointNode : public visionflow::param::ISchemable#

KeyPointNode Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

double get_x() const#

Get X-Value.

X-direction coordinate value of the center of the key point. When the template models set to kValueByPixel, X-Value should be set using pixel value. When the template models set to kValueByRatio, X-Value should be set using ratio value. When the Area Value Type is modified, X-Value needs to be modified.

See also

set_x()

Returns:

double X-Value

KeyPointNode &set_x(double x)#

Set X-Value with double value.

X-direction coordinate value of the center of the key point. When the template models set to kValueByPixel, X-Value should be set using pixel value. When the template models set to kValueByRatio, X-Value should be set using ratio value. When the Area Value Type is modified, X-Value needs to be modified.

See also

get_x()

Parameters:

x – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

KeyPointNode the reference of this object.

double get_y() const#

Get Y-Value.

Y-direction coordinate value of the center of the key point. When the template models set to kValueByPixel, Y-Value should be set using pixel value. When the template models set to kValueByRatio, Y-Value should be set using ratio value. When the Area Value Type is modified, Y-Value needs to be modified.

See also

set_y()

Returns:

double Y-Value

KeyPointNode &set_y(double y)#

Set Y-Value with double value.

Y-direction coordinate value of the center of the key point. When the template models set to kValueByPixel, Y-Value should be set using pixel value. When the template models set to kValueByRatio, Y-Value should be set using ratio value. When the Area Value Type is modified, Y-Value needs to be modified.

See also

get_y()

Parameters:

y – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

KeyPointNode the reference of this object.

const std::string &get_name() const#

Get Name.

The name that can be matched by the node

See also

set_name()

Returns:

const std::string & Name

KeyPointNode &set_name(std::string name)#

Set Name with std::string value.

The name that can be matched by the node

See also

get_name()

Parameters:

name – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

KeyPointNode the reference of this object.

class MultiNameKeyPointNode : public visionflow::param::ISchemable#

MultiNameKeyPointNode Parameter class generated by jinja2 automatically.

Define the position of the node and a set of names that can be matched by the node.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

double get_x() const#

Get X-Value.

X-direction coordinate value of the key point, specified either in absolute pixel or relative ratio, depending on the chosen TemplateMode. If using kValueByRatio mode, the value is relative to the view width.

See also

set_x()

Returns:

double X-Value

MultiNameKeyPointNode &set_x(double x)#

Set X-Value with double value.

X-direction coordinate value of the key point, specified either in absolute pixel or relative ratio, depending on the chosen TemplateMode. If using kValueByRatio mode, the value is relative to the view width.

See also

get_x()

Parameters:

x – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

MultiNameKeyPointNode the reference of this object.

double get_y() const#

Get Y-Value.

Y-direction coordinate value of the key point, specified either in absolute pixel or relative ratio, depending on the chosen TemplateMode. If using kValueByRatio mode, the value is relative to the view height.

See also

set_y()

Returns:

double Y-Value

MultiNameKeyPointNode &set_y(double y)#

Set Y-Value with double value.

Y-direction coordinate value of the key point, specified either in absolute pixel or relative ratio, depending on the chosen TemplateMode. If using kValueByRatio mode, the value is relative to the view height.

See also

get_y()

Parameters:

y – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

MultiNameKeyPointNode the reference of this object.

const std::vector<std::string> &get_names() const#

Get Names.

The names that can be matched by the node

See also

set_names()

Returns:

const std::vector<std::string> & Names

MultiNameKeyPointNode &set_names(std::vector<std::string> names)#

Set Names with std::vector<std::string> value.

The names that can be matched by the node

See also

get_names()

Parameters:

names – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

MultiNameKeyPointNode the reference of this object.

const std::string &get_names(size_t index) const#

Get value in Names with index.

Warning

The index must be less than get_names_size(). otherwise, the behavior is undefined and will cause segmentation fault.

Returns:

const std::string & value in Names at index.

size_t get_names_size() const#

Get the size of Names.

Returns:

size_t the size of Names

GeometrySearch Training Parameters#

class SetGeometrySearchGranularityManually : public visionflow::param::ISchemable#

SetGeometrySearchGranularityManually Parameter class generated by jinja2 automatically.

GeometrySearch granularity parameter group

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

bool get_enable() const#

Get Enable.

Enable this parameter group.

See also

set_enable()

Returns:

bool Enable

SetGeometrySearchGranularityManually &set_enable(bool enable)#

Set Enable with bool value.

Enable this parameter group.

See also

get_enable()

Parameters:

enable – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

SetGeometrySearchGranularityManually the reference of this object.

double get_granularity() const#

Get Granularity.

Customize granularity. Granularity indicates the scale of feature point. Higher granularity will generate more sparse and fewer feature points. Higher granularity will also speed up the infer process but with lower accuracy. We do not recommend to set to 1. 2 or higher will be a better choice for most applications.

Returns:

double Granularity

SetGeometrySearchGranularityManually &set_granularity(double granularity)#

Set Granularity with double value.

Customize granularity. Granularity indicates the scale of feature point. Higher granularity will generate more sparse and fewer feature points. Higher granularity will also speed up the infer process but with lower accuracy. We do not recommend to set to 1. 2 or higher will be a better choice for most applications.

Parameters:

granularity – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

SetGeometrySearchGranularityManually the reference of this object.

class SetGeometrySearchNoiseThreshManually : public visionflow::param::ISchemable#

SetGeometrySearchNoiseThreshManually Parameter class generated by jinja2 automatically.

GeometrySearch noise threshold.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

bool get_enable() const#

Get Enable.

Enable this parameter group.

See also

set_enable()

Returns:

bool Enable

SetGeometrySearchNoiseThreshManually &set_enable(bool enable)#

Set Enable with bool value.

Enable this parameter group.

See also

get_enable()

Parameters:

enable – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

SetGeometrySearchNoiseThreshManually the reference of this object.

int get_noise_thresh() const#

Get Noise Threshold.

Noise Threshold. Feature points with lower gradient magnitude than noise threshold will be ignore. Suggestive value: 20~60.

Returns:

int Noise Threshold

SetGeometrySearchNoiseThreshManually &set_noise_thresh(int noise_thresh)#

Set Noise Threshold with int value.

Noise Threshold. Feature points with lower gradient magnitude than noise threshold will be ignore. Suggestive value: 20~60.

Parameters:

noise_thresh – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

SetGeometrySearchNoiseThreshManually the reference of this object.

class SetGeometrySearchFeatChainMagRelativeThreshManually : public visionflow::param::ISchemable#

SetGeometrySearchFeatChainMagRelativeThreshManually Parameter class generated by jinja2 automatically.

GeometrySearch feature chain magnitude threshold

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

bool get_enable() const#

Get Enable.

Enable this parameter group.

See also

set_enable()

Returns:

bool Enable

SetGeometrySearchFeatChainMagRelativeThreshManually &set_enable(bool enable)#

Set Enable with bool value.

Enable this parameter group.

See also

get_enable()

Parameters:

enable – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

SetGeometrySearchFeatChainMagRelativeThreshManually the reference of this object.

double get_total_magnitude_relative_thresh() const#

Get Magnitude Relative Threshold.

Set relative total gradient magnitude threshold for feature chains.The actual threshold will be max length of chains * relative threshold.

Returns:

double Magnitude Relative Threshold

SetGeometrySearchFeatChainMagRelativeThreshManually &set_total_magnitude_relative_thresh(double total_magnitude_relative_thresh)#

Set Magnitude Relative Threshold with double value.

Set relative total gradient magnitude threshold for feature chains.The actual threshold will be max length of chains * relative threshold.

Parameters:

total_magnitude_relative_thresh – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

SetGeometrySearchFeatChainMagRelativeThreshManually the reference of this object.

class SetGeometrySearchDownSampleRatioManually : public visionflow::param::ISchemable#

SetGeometrySearchDownSampleRatioManually Parameter class generated by jinja2 automatically.

GeometrySearch down sample ratio.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

bool get_enable() const#

Get Enable.

Enable this parameter group.

See also

set_enable()

Returns:

bool Enable

SetGeometrySearchDownSampleRatioManually &set_enable(bool enable)#

Set Enable with bool value.

Enable this parameter group.

See also

get_enable()

Parameters:

enable – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

SetGeometrySearchDownSampleRatioManually the reference of this object.

double get_down_sample_ratio() const#

Get Down sample ratio.

Image down sample ratio during training and inference. Higher down sample ratio will effectively speed up training and inference with some degree of accuracy loss. Suggestive value: 2~8.

Returns:

double Down sample ratio

SetGeometrySearchDownSampleRatioManually &set_down_sample_ratio(double down_sample_ratio)#

Set Down sample ratio with double value.

Image down sample ratio during training and inference. Higher down sample ratio will effectively speed up training and inference with some degree of accuracy loss. Suggestive value: 2~8.

Parameters:

down_sample_ratio – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

SetGeometrySearchDownSampleRatioManually the reference of this object.

GeometrySearch Inference Parameters#

enum visionflow::param::GeometrySearchSearchMode#

Values:

enumerator kQuick = 0#
enumerator kFine = 1#
enumerator kRobustFine = 2#
class GeometrySearchDuplicate : public visionflow::param::ISchemable#

GeometrySearchDuplicate Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

double get_target_overlap_ratio() const#

Get Target Overlap Ratio.

Minimum overlap ratio of two targets to be regard as duplicate.overlap =max(1-2*abs(cx1-cx2)/(w1+w2),0)*max(1-2*abs(cy1-cy2)/(h1+h2), 0)

Returns:

double Target Overlap Ratio

GeometrySearchDuplicate &set_target_overlap_ratio(double target_overlap_ratio)#

Set Target Overlap Ratio with double value.

Minimum overlap ratio of two targets to be regard as duplicate.overlap =max(1-2*abs(cx1-cx2)/(w1+w2),0)*max(1-2*abs(cy1-cy2)/(h1+h2), 0)

Parameters:

target_overlap_ratio – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

GeometrySearchDuplicate the reference of this object.

double get_scale_duplicate() const#

Get Scale Duplicate Ratio.

Maximum scale ration of two target of be regard as duplicate, only have effect when Target Overlap Ratio if larger than Target Overlap Ratio threshold.

Returns:

double Scale Duplicate Ratio

GeometrySearchDuplicate &set_scale_duplicate(double scale_duplicate)#

Set Scale Duplicate Ratio with double value.

Maximum scale ration of two target of be regard as duplicate, only have effect when Target Overlap Ratio if larger than Target Overlap Ratio threshold.

Parameters:

scale_duplicate – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

GeometrySearchDuplicate the reference of this object.

int get_rotate_duplicate() const#

Get Rotate Duplicate Ratio.

Maximum rotate difference (in degree) of two target of be regard as duplicate, only have effect when Target Overlap Ratio if larger than Target Overlap Ratio threshold.

Returns:

int Rotate Duplicate Ratio

GeometrySearchDuplicate &set_rotate_duplicate(int rotate_duplicate)#

Set Rotate Duplicate Ratio with int value.

Maximum rotate difference (in degree) of two target of be regard as duplicate, only have effect when Target Overlap Ratio if larger than Target Overlap Ratio threshold.

Parameters:

rotate_duplicate – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

GeometrySearchDuplicate the reference of this object.

CameraCalibration Training Parameters#

enum visionflow::param::FreedomDegreeType#

the type of freedom degree

Values:

enumerator kFreedomDegreeNonlinear = 0#

nonlinear

enumerator kFreedomDegreeTranslationRotationScale = 1#

translation, rotation and scale

enumerator kFreedomDegreeAffine = 2#

affine

enumerator kFreedomDegreePerspective = 3#

perspective

enum visionflow::param::CalibrationBoardType#

the type of calibration board

Values:

enumerator kAQBoardRect = 0#

Calibration board with black dots on white background.

enumerator kChessBoard = 1#

checkerboard

Polarity Mode Parameters#

enum visionflow::param::PolarityMode#

Values:

enumerator kBlackOnWhite = 0#
enumerator kWhiteOnBlack = 1#
enumerator kUnspecified = 2#

OCR Parameters#

class RegularExpression : public visionflow::param::ISchemable#

RegularExpression Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

bool get_enable() const#

Get Enable.

Enable this parameter group.

See also

set_enable()

Returns:

bool Enable

RegularExpression &set_enable(bool enable)#

Set Enable with bool value.

Enable this parameter group.

See also

get_enable()

Parameters:

enable – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

RegularExpression the reference of this object.

const std::string &get_pattern() const#

Get Pattern.

Regular expression pattern.

See also

set_pattern()

Returns:

const std::string & Pattern

RegularExpression &set_pattern(std::string pattern)#

Set Pattern with std::string value.

Regular expression pattern.

See also

get_pattern()

Parameters:

pattern – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

RegularExpression the reference of this object.

class OCRArea : public visionflow::param::ISchemable#

OCRArea Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

double get_x() const#

Get X-Value.

X-direction coordinate value of the center of the area. When the template mode is set to kValueByPixel, X-Value should be set using pixel value. When the template mode is set to kValueByRatio, X-Value should be set using ratio value. When the template mode is modified, X-Value needs to be modified.

See also

set_x()

Returns:

double X-Value

OCRArea &set_x(double x)#

Set X-Value with double value.

X-direction coordinate value of the center of the area. When the template mode is set to kValueByPixel, X-Value should be set using pixel value. When the template mode is set to kValueByRatio, X-Value should be set using ratio value. When the template mode is modified, X-Value needs to be modified.

See also

get_x()

Parameters:

x – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRArea the reference of this object.

double get_y() const#

Get Y-Value.

Y-direction coordinate value of the center of the area. When the template mode is set to kValueByPixel, Y-Value should be set using pixel value. When the template mode is set to kValueByRatio, Y-Value should be set using ratio value. When the template mode is modified, Y-Value needs to be modified.

See also

set_y()

Returns:

double Y-Value

OCRArea &set_y(double y)#

Set Y-Value with double value.

Y-direction coordinate value of the center of the area. When the template mode is set to kValueByPixel, Y-Value should be set using pixel value. When the template mode is set to kValueByRatio, Y-Value should be set using ratio value. When the template mode is modified, Y-Value needs to be modified.

See also

get_y()

Parameters:

y – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRArea the reference of this object.

double get_w() const#

Get W-Value.

width of the area. When the template mode is set to kValueByPixel, W-Value should be set using pixel value. When the template mode is set to kValueByRatio, W-Value should be set using ratio value. When the template mode is modified, W-Value needs to be modified.

See also

set_w()

Returns:

double W-Value

OCRArea &set_w(double w)#

Set W-Value with double value.

width of the area. When the template mode is set to kValueByPixel, W-Value should be set using pixel value. When the template mode is set to kValueByRatio, W-Value should be set using ratio value. When the template mode is modified, W-Value needs to be modified.

See also

get_w()

Parameters:

w – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRArea the reference of this object.

double get_h() const#

Get H-Value.

height of the area. When the template mode is set to kValueByPixel, H-Value should be set using pixel value. When the template mode is set to kValueRatio, H-Value should be set using ratio value. When the template mode is modified, H-Value needs to be modified.

See also

set_h()

Returns:

double H-Value

OCRArea &set_h(double h)#

Set H-Value with double value.

height of the area. When the template mode is set to kValueByPixel, H-Value should be set using pixel value. When the template mode is set to kValueRatio, H-Value should be set using ratio value. When the template mode is modified, H-Value needs to be modified.

See also

get_h()

Parameters:

h – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRArea the reference of this object.

class OCRStringTemplateArea : public visionflow::param::ISchemable#

OCRStringTemplateArea Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

const OCRArea &get_area() const#

Get Area Parameters.

Parameters defining the base area for OCR, including X, Y, W, H values.

See also

set_area()

Returns:

const OCRArea & Area Parameters

OCRStringTemplateArea &set_area(OCRArea area)#

Set Area Parameters with OCRArea value.

Parameters defining the base area for OCR, including X, Y, W, H values.

See also

get_area()

Parameters:

area – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRStringTemplateArea the reference of this object.

OCRArea &get_area()#

Get mutable reference of Area Parameters.

Parameters defining the base area for OCR, including X, Y, W, H values.

Returns:

OCRStringTemplateArea& the mutable reference of the group.

int get_max_matches() const#

Get Maximum Matches.

Maximum number of templates to remain within view. Results are sorted based on the deviation of characters from the string, and only the top ‘max_matches’ results are retained. All results are provided by default.

Returns:

int Maximum Matches

OCRStringTemplateArea &set_max_matches(int max_matches)#

Set Maximum Matches with int value.

Maximum number of templates to remain within view. Results are sorted based on the deviation of characters from the string, and only the top ‘max_matches’ results are retained. All results are provided by default.

Parameters:

max_matches – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRStringTemplateArea the reference of this object.

int get_min_length() const#

Get Minimum String Length.

String shorter than the minimum length will be ignored.

See also

set_min_length()

Returns:

int Minimum String Length

OCRStringTemplateArea &set_min_length(int min_length)#

Set Minimum String Length with int value.

String shorter than the minimum length will be ignored.

See also

get_min_length()

Parameters:

min_length – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRStringTemplateArea the reference of this object.

double get_max_char_interval() const#

Get Maximum Character Interval.

The maximum interval between characters in a string, Two characters with interval longer than this threshold will be matched into two different strings.

Returns:

double Maximum Character Interval

OCRStringTemplateArea &set_max_char_interval(double max_char_interval)#

Set Maximum Character Interval with double value.

The maximum interval between characters in a string, Two characters with interval longer than this threshold will be matched into two different strings.

Parameters:

max_char_interval – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRStringTemplateArea the reference of this object.

int get_main_direction() const#

Get String Main Direction.

Direction of strings based on statistics. (It is specified that the positive x-axis direction is 0 degrees, positive values representing the direction towards the positive y-axis, negative values indicating the direction towards the negative y-axis.)

Returns:

int String Main Direction

OCRStringTemplateArea &set_main_direction(int main_direction)#

Set String Main Direction with int value.

Direction of strings based on statistics. (It is specified that the positive x-axis direction is 0 degrees, positive values representing the direction towards the positive y-axis, negative values indicating the direction towards the negative y-axis.)

Parameters:

main_direction – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRStringTemplateArea the reference of this object.

int get_angle_range() const#

Get Rotate Angle Range.

The rotate angle range of the string, which means that the string can be rotated slightly within an angular range centered on the main direction.

Returns:

int Rotate Angle Range

OCRStringTemplateArea &set_angle_range(int angle_range)#

Set Rotate Angle Range with int value.

The rotate angle range of the string, which means that the string can be rotated slightly within an angular range centered on the main direction.

Parameters:

angle_range – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRStringTemplateArea the reference of this object.

const RegularExpression &get_regular_expression() const#

Get Regular Expression.

Regular expression matching parameters.

Returns:

const RegularExpression & Regular Expression

OCRStringTemplateArea &set_regular_expression(RegularExpression regular_expression)#

Set Regular Expression with RegularExpression value.

Regular expression matching parameters.

Parameters:

regular_expression – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRStringTemplateArea the reference of this object.

RegularExpression &get_regular_expression()#

Get mutable reference of Regular Expression.

Regular expression matching parameters.

Returns:

OCRStringTemplateArea& the mutable reference of the group.

const RegularExpression &get_string_filter_template() const#

Get String Filter Template.

This parameter serves as a filter for the output strings. The user-defined rules in this template determine the expected character types in the output strings. Any string that does not match the template will be filtered out from the final results.

Returns:

const RegularExpression & String Filter Template

OCRStringTemplateArea &set_string_filter_template(RegularExpression string_filter_template)#

Set String Filter Template with RegularExpression value.

This parameter serves as a filter for the output strings. The user-defined rules in this template determine the expected character types in the output strings. Any string that does not match the template will be filtered out from the final results.

Parameters:

string_filter_template – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRStringTemplateArea the reference of this object.

RegularExpression &get_string_filter_template()#

Get mutable reference of String Filter Template.

This parameter serves as a filter for the output strings. The user-defined rules in this template determine the expected character types in the output strings. Any string that does not match the template will be filtered out from the final results.

Returns:

OCRStringTemplateArea& the mutable reference of the group.

const RegularExpression &get_string_fix_template() const#

Get String Fix Template.

This parameter is used to correct the output strings based on user-defined rules. It defines the expected character types in the output strings. If the output strings do not match the template, they will be corrected.

Returns:

const RegularExpression & String Fix Template

OCRStringTemplateArea &set_string_fix_template(RegularExpression string_fix_template)#

Set String Fix Template with RegularExpression value.

This parameter is used to correct the output strings based on user-defined rules. It defines the expected character types in the output strings. If the output strings do not match the template, they will be corrected.

Parameters:

string_fix_template – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRStringTemplateArea the reference of this object.

RegularExpression &get_string_fix_template()#

Get mutable reference of String Fix Template.

This parameter is used to correct the output strings based on user-defined rules. It defines the expected character types in the output strings. If the output strings do not match the template, they will be corrected.

Returns:

OCRStringTemplateArea& the mutable reference of the group.

class OCRNodeTemplateArea : public visionflow::param::ISchemable#

OCRNodeTemplateArea Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

const OCRArea &get_area() const#

Get Area Parameters.

Parameters defining the base area for OCR, including X, Y, W, H values.

See also

set_area()

Returns:

const OCRArea & Area Parameters

OCRNodeTemplateArea &set_area(OCRArea area)#

Set Area Parameters with OCRArea value.

Parameters defining the base area for OCR, including X, Y, W, H values.

See also

get_area()

Parameters:

area – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRNodeTemplateArea the reference of this object.

OCRArea &get_area()#

Get mutable reference of Area Parameters.

Parameters defining the base area for OCR, including X, Y, W, H values.

Returns:

OCRNodeTemplateArea& the mutable reference of the group.

int get_max_matches() const#

Get Maximum Matches.

Maximum number of templates to remain within view. Results are sorted based on the match distance in ascending order, and only the top ‘max_matches’ results are retained. All results are provided by default.

Returns:

int Maximum Matches

OCRNodeTemplateArea &set_max_matches(int max_matches)#

Set Maximum Matches with int value.

Maximum number of templates to remain within view. Results are sorted based on the match distance in ascending order, and only the top ‘max_matches’ results are retained. All results are provided by default.

Parameters:

max_matches – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRNodeTemplateArea the reference of this object.

const std::vector<MultiNameKeyPointNode> &get_points() const#

Get Keypoints.

The key points of the template.

See also

set_points()

Returns:

const std::vector<MultiNameKeyPointNode> & Keypoints

OCRNodeTemplateArea &set_points(std::vector<MultiNameKeyPointNode> points)#

Set Keypoints with std::vector<MultiNameKeyPointNode> value.

The key points of the template.

See also

get_points()

Parameters:

points – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRNodeTemplateArea the reference of this object.

const MultiNameKeyPointNode &get_points(size_t index) const#

Get value in Keypoints with index.

Warning

The index must be less than get_points_size(). otherwise, the behavior is undefined and will cause segmentation fault.

Returns:

const MultiNameKeyPointNode & value in Keypoints at index.

size_t get_points_size() const#

Get the size of Keypoints.

Returns:

size_t the size of Keypoints

MultiNameKeyPointNode &get_points(size_t index)#

Get mutable reference of value in Keypoints with index.

Warning

The index must be less than get_points_size(). otherwise, the behavior is undefined and will cause segmentation fault.

Returns:

MultiNameKeyPointNode& the mutable reference of value in Keypoints at index.

double get_max_distance() const#

Get Max Distance.

The maximum allowed distance between the template keypoints and the keypoints to be matched. Results with a distance greater than this value will be filtered out. The value can be either in absolute pixel or relative to the view height, depending on the template_mode.

Returns:

double Max Distance

OCRNodeTemplateArea &set_max_distance(double max_distance)#

Set Max Distance with double value.

The maximum allowed distance between the template keypoints and the keypoints to be matched. Results with a distance greater than this value will be filtered out. The value can be either in absolute pixel or relative to the view height, depending on the template_mode.

Parameters:

max_distance – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRNodeTemplateArea the reference of this object.

bool get_is_scalable() const#

Get Target Scalable.

Enable this option if the size of target to be matched is not fixed. And you should set the target scale range.

Returns:

bool Target Scalable

OCRNodeTemplateArea &set_is_scalable(bool is_scalable)#

Set Target Scalable with bool value.

Enable this option if the size of target to be matched is not fixed. And you should set the target scale range.

Parameters:

is_scalable – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRNodeTemplateArea the reference of this object.

const std::vector<double> &get_scale_range() const#

Get Scale Range.

The target scale range.

Returns:

const std::vector<double> & Scale Range

OCRNodeTemplateArea &set_scale_range(std::vector<double> scale_range)#

Set Scale Range with std::vector<double> value.

The target scale range.

Parameters:

scale_range – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRNodeTemplateArea the reference of this object.

bool scale_range_contains(double value) const#

Check if the Scale Range contains the value.

Returns:

bool true if the Scale Range contains the value, otherwise false.

double get_scale_range_left() const#

Get left point value of Scale Range.

Returns:

const std::vector<double> & left point value of Scale Range

double get_scale_range_right() const#

Get the right point value of Scale Range.

Returns:

const std::vector<double> & the right point value of Scale Range

OCRNodeTemplateArea &set_scale_range_left(double scale_range_left)#

Set left point value of Scale Range with std::vector<double> value.

The target scale range.

Parameters:

scale_range_left – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRNodeTemplateArea the reference of this object.

OCRNodeTemplateArea &set_scale_range_right(double scale_range_right)#

Set the right point value of Scale Range with std::vector<double> value.

The target scale range.

Parameters:

scale_range_right – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRNodeTemplateArea the reference of this object.

bool get_is_rotatable() const#

Get Target Rotatable.

Enable this option if the angle of target to be matched is not fixed, And you should set the target rotate angle range.

Returns:

bool Target Rotatable

OCRNodeTemplateArea &set_is_rotatable(bool is_rotatable)#

Set Target Rotatable with bool value.

Enable this option if the angle of target to be matched is not fixed, And you should set the target rotate angle range.

Parameters:

is_rotatable – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRNodeTemplateArea the reference of this object.

const std::vector<int> &get_rotate_range() const#

Get Rotate Range (Degree).

The target rotate range.

Returns:

const std::vector<int> & Rotate Range (Degree)

OCRNodeTemplateArea &set_rotate_range(std::vector<int> rotate_range)#

Set Rotate Range (Degree) with std::vector<int> value.

The target rotate range.

Parameters:

rotate_range – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRNodeTemplateArea the reference of this object.

bool rotate_range_contains(int value) const#

Check if the Rotate Range (Degree) contains the value.

Returns:

bool true if the Rotate Range (Degree) contains the value, otherwise false.

int get_rotate_range_left() const#

Get left point value of Rotate Range (Degree).

Returns:

const std::vector<int> & left point value of Rotate Range (Degree)

int get_rotate_range_right() const#

Get the right point value of Rotate Range (Degree).

Returns:

const std::vector<int> & the right point value of Rotate Range (Degree)

OCRNodeTemplateArea &set_rotate_range_left(int rotate_range_left)#

Set left point value of Rotate Range (Degree) with std::vector<int> value.

The target rotate range.

Parameters:

rotate_range_left – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRNodeTemplateArea the reference of this object.

OCRNodeTemplateArea &set_rotate_range_right(int rotate_range_right)#

Set the right point value of Rotate Range (Degree) with std::vector<int> value.

The target rotate range.

Parameters:

rotate_range_right – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRNodeTemplateArea the reference of this object.

const RegularExpression &get_string_filter_template() const#

Get String Filter Template.

This parameter serves as a filter for the output strings. The user-defined rules in this template determine the expected character types in the output strings. Any string that does not match the template will be filtered out from the final results.

Returns:

const RegularExpression & String Filter Template

OCRNodeTemplateArea &set_string_filter_template(RegularExpression string_filter_template)#

Set String Filter Template with RegularExpression value.

This parameter serves as a filter for the output strings. The user-defined rules in this template determine the expected character types in the output strings. Any string that does not match the template will be filtered out from the final results.

Parameters:

string_filter_template – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRNodeTemplateArea the reference of this object.

RegularExpression &get_string_filter_template()#

Get mutable reference of String Filter Template.

This parameter serves as a filter for the output strings. The user-defined rules in this template determine the expected character types in the output strings. Any string that does not match the template will be filtered out from the final results.

Returns:

OCRNodeTemplateArea& the mutable reference of the group.

const RegularExpression &get_string_fix_template() const#

Get String Fix Template.

This parameter is used to correct the output strings based on user-defined rules. It defines the expected character types in the output strings. If the output strings do not match the template, they will be corrected.

Returns:

const RegularExpression & String Fix Template

OCRNodeTemplateArea &set_string_fix_template(RegularExpression string_fix_template)#

Set String Fix Template with RegularExpression value.

This parameter is used to correct the output strings based on user-defined rules. It defines the expected character types in the output strings. If the output strings do not match the template, they will be corrected.

Parameters:

string_fix_template – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRNodeTemplateArea the reference of this object.

RegularExpression &get_string_fix_template()#

Get mutable reference of String Fix Template.

This parameter is used to correct the output strings based on user-defined rules. It defines the expected character types in the output strings. If the output strings do not match the template, they will be corrected.

Returns:

OCRNodeTemplateArea& the mutable reference of the group.

class OCRNodeTemplate : public visionflow::param::ISchemable#

OCRNodeTemplate Parameter class generated by jinja2 automatically.

Node template is used to match strings of any shape.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

bool get_enable() const#

Get Enable.

Enable this parameter group.

See also

set_enable()

Returns:

bool Enable

OCRNodeTemplate &set_enable(bool enable)#

Set Enable with bool value.

Enable this parameter group.

See also

get_enable()

Parameters:

enable – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRNodeTemplate the reference of this object.

const TemplateMode &get_template_mode() const#

Get Template Mode.

Determines the unit of measurement for template areas. Value By Pixel indicates measurement in pixel values, while Value By Ratio uses relative ratios.

Returns:

const TemplateMode & Template Mode

OCRNodeTemplate &set_template_mode(TemplateMode template_mode)#

Set Template Mode with TemplateMode value.

Determines the unit of measurement for template areas. Value By Pixel indicates measurement in pixel values, while Value By Ratio uses relative ratios.

Parameters:

template_mode – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRNodeTemplate the reference of this object.

int get_max_matches() const#

Get Maximum Matches.

Maximum number of templates to remain within view. Results are sorted based on the match distance in ascending order, and only the top ‘max_matches’ results are retained. All results are provided by default.

Returns:

int Maximum Matches

OCRNodeTemplate &set_max_matches(int max_matches)#

Set Maximum Matches with int value.

Maximum number of templates to remain within view. Results are sorted based on the match distance in ascending order, and only the top ‘max_matches’ results are retained. All results are provided by default.

Parameters:

max_matches – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRNodeTemplate the reference of this object.

const std::vector<MultiNameKeyPointNode> &get_points() const#

Get Keypoints.

The key points of the template.

See also

set_points()

Returns:

const std::vector<MultiNameKeyPointNode> & Keypoints

OCRNodeTemplate &set_points(std::vector<MultiNameKeyPointNode> points)#

Set Keypoints with std::vector<MultiNameKeyPointNode> value.

The key points of the template.

See also

get_points()

Parameters:

points – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRNodeTemplate the reference of this object.

const MultiNameKeyPointNode &get_points(size_t index) const#

Get value in Keypoints with index.

Warning

The index must be less than get_points_size(). otherwise, the behavior is undefined and will cause segmentation fault.

Returns:

const MultiNameKeyPointNode & value in Keypoints at index.

size_t get_points_size() const#

Get the size of Keypoints.

Returns:

size_t the size of Keypoints

MultiNameKeyPointNode &get_points(size_t index)#

Get mutable reference of value in Keypoints with index.

Warning

The index must be less than get_points_size(). otherwise, the behavior is undefined and will cause segmentation fault.

Returns:

MultiNameKeyPointNode& the mutable reference of value in Keypoints at index.

double get_max_distance() const#

Get Max Distance.

The maximum allowed distance between the template keypoints and the keypoints to be matched. Results with a distance greater than this value will be filtered out. The value can be either in absolute pixel or relative to the view height, depending on the template_mode.

Returns:

double Max Distance

OCRNodeTemplate &set_max_distance(double max_distance)#

Set Max Distance with double value.

The maximum allowed distance between the template keypoints and the keypoints to be matched. Results with a distance greater than this value will be filtered out. The value can be either in absolute pixel or relative to the view height, depending on the template_mode.

Parameters:

max_distance – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRNodeTemplate the reference of this object.

bool get_is_scalable() const#

Get Target Scalable.

Enable this option if the size of target to be matched is not fixed. And you should set the target scale range.

Returns:

bool Target Scalable

OCRNodeTemplate &set_is_scalable(bool is_scalable)#

Set Target Scalable with bool value.

Enable this option if the size of target to be matched is not fixed. And you should set the target scale range.

Parameters:

is_scalable – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRNodeTemplate the reference of this object.

const std::vector<double> &get_scale_range() const#

Get Scale Range.

The target scale range.

Returns:

const std::vector<double> & Scale Range

OCRNodeTemplate &set_scale_range(std::vector<double> scale_range)#

Set Scale Range with std::vector<double> value.

The target scale range.

Parameters:

scale_range – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRNodeTemplate the reference of this object.

bool scale_range_contains(double value) const#

Check if the Scale Range contains the value.

Returns:

bool true if the Scale Range contains the value, otherwise false.

double get_scale_range_left() const#

Get left point value of Scale Range.

Returns:

const std::vector<double> & left point value of Scale Range

double get_scale_range_right() const#

Get the right point value of Scale Range.

Returns:

const std::vector<double> & the right point value of Scale Range

OCRNodeTemplate &set_scale_range_left(double scale_range_left)#

Set left point value of Scale Range with std::vector<double> value.

The target scale range.

Parameters:

scale_range_left – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRNodeTemplate the reference of this object.

OCRNodeTemplate &set_scale_range_right(double scale_range_right)#

Set the right point value of Scale Range with std::vector<double> value.

The target scale range.

Parameters:

scale_range_right – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRNodeTemplate the reference of this object.

bool get_is_rotatable() const#

Get Target Rotatable.

Enable this option if the angle of target to be matched is not fixed, And you should set the target rotate angle range.

Returns:

bool Target Rotatable

OCRNodeTemplate &set_is_rotatable(bool is_rotatable)#

Set Target Rotatable with bool value.

Enable this option if the angle of target to be matched is not fixed, And you should set the target rotate angle range.

Parameters:

is_rotatable – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRNodeTemplate the reference of this object.

const std::vector<int> &get_rotate_range() const#

Get Rotate Range (Degree).

The target rotate range.

Returns:

const std::vector<int> & Rotate Range (Degree)

OCRNodeTemplate &set_rotate_range(std::vector<int> rotate_range)#

Set Rotate Range (Degree) with std::vector<int> value.

The target rotate range.

Parameters:

rotate_range – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRNodeTemplate the reference of this object.

bool rotate_range_contains(int value) const#

Check if the Rotate Range (Degree) contains the value.

Returns:

bool true if the Rotate Range (Degree) contains the value, otherwise false.

int get_rotate_range_left() const#

Get left point value of Rotate Range (Degree).

Returns:

const std::vector<int> & left point value of Rotate Range (Degree)

int get_rotate_range_right() const#

Get the right point value of Rotate Range (Degree).

Returns:

const std::vector<int> & the right point value of Rotate Range (Degree)

OCRNodeTemplate &set_rotate_range_left(int rotate_range_left)#

Set left point value of Rotate Range (Degree) with std::vector<int> value.

The target rotate range.

Parameters:

rotate_range_left – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRNodeTemplate the reference of this object.

OCRNodeTemplate &set_rotate_range_right(int rotate_range_right)#

Set the right point value of Rotate Range (Degree) with std::vector<int> value.

The target rotate range.

Parameters:

rotate_range_right – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRNodeTemplate the reference of this object.

const RegularExpression &get_string_filter_template() const#

Get String Filter Template.

This parameter serves as a filter for the output strings. The user-defined rules in this template determine the expected character types in the output strings. Any string that does not match the template will be filtered out from the final results.

Returns:

const RegularExpression & String Filter Template

OCRNodeTemplate &set_string_filter_template(RegularExpression string_filter_template)#

Set String Filter Template with RegularExpression value.

This parameter serves as a filter for the output strings. The user-defined rules in this template determine the expected character types in the output strings. Any string that does not match the template will be filtered out from the final results.

Parameters:

string_filter_template – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRNodeTemplate the reference of this object.

RegularExpression &get_string_filter_template()#

Get mutable reference of String Filter Template.

This parameter serves as a filter for the output strings. The user-defined rules in this template determine the expected character types in the output strings. Any string that does not match the template will be filtered out from the final results.

Returns:

OCRNodeTemplate& the mutable reference of the group.

const RegularExpression &get_string_fix_template() const#

Get String Fix Template.

This parameter is used to correct the output strings based on user-defined rules. It defines the expected character types in the output strings. If the output strings do not match the template, they will be corrected.

Returns:

const RegularExpression & String Fix Template

OCRNodeTemplate &set_string_fix_template(RegularExpression string_fix_template)#

Set String Fix Template with RegularExpression value.

This parameter is used to correct the output strings based on user-defined rules. It defines the expected character types in the output strings. If the output strings do not match the template, they will be corrected.

Parameters:

string_fix_template – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRNodeTemplate the reference of this object.

RegularExpression &get_string_fix_template()#

Get mutable reference of String Fix Template.

This parameter is used to correct the output strings based on user-defined rules. It defines the expected character types in the output strings. If the output strings do not match the template, they will be corrected.

Returns:

OCRNodeTemplate& the mutable reference of the group.

const std::map<std::string, OCRArea> &get_areas() const#

Get Areas.

The areas inside the template. The key of the map is the name of area. The value of the map is the parameter of area.

See also

set_areas()

Returns:

const std::map<std::string, OCRArea> & Areas

OCRNodeTemplate &set_areas(std::map<std::string, OCRArea> areas)#

Set Areas with std::map<std::string, OCRArea> value.

The areas inside the template. The key of the map is the name of area. The value of the map is the parameter of area.

See also

get_areas()

Parameters:

areas – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRNodeTemplate the reference of this object.

const OCRArea &get_areas(const std::string &key) const#

Get value in Areas with key.

Warning

The key must be exist in Areas. otherwise, the behavior is undefined and will cause segmentation fault.

Returns:

const std::map<std::string, OCRArea> & value in Areas at key.

OCRNodeTemplate &set_areas(const std::string &key, OCRArea value)#

Set value in Areas with key.

Parameters:
  • key – the key to set.

  • value – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRNodeTemplate the reference of this object.

bool areas_contains(const std::string &key) const#

Check if the key is exist in Areas.

Returns:

bool true if the key is exist in Areas, otherwise false.

size_t get_areas_size() const#

Get the size of Areas.

Returns:

size_t the size of Areas

OCRArea &get_areas(const std::string &key)#

Get mutable reference of value in Areas with key. A new key and default value will be created if the key does not exist.

Returns:

OCRArea& the mutable reference of value in Areas at key.

const std::map<std::string, OCRNodeTemplateArea> &get_node_template_areas() const#

Get Areas.

A dictionary mapping unique identifiers to OCRNodeTemplateArea objects. Each key-value pair defines a unique ‘area’ and its matching rules for node template matching. The matching operation is strictly applied within these specified areas.

Returns:

const std::map<std::string, OCRNodeTemplateArea> & Areas

OCRNodeTemplate &set_node_template_areas(std::map<std::string, OCRNodeTemplateArea> node_template_areas)#

Set Areas with std::map<std::string, OCRNodeTemplateArea> value.

A dictionary mapping unique identifiers to OCRNodeTemplateArea objects. Each key-value pair defines a unique ‘area’ and its matching rules for node template matching. The matching operation is strictly applied within these specified areas.

Parameters:

node_template_areas – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRNodeTemplate the reference of this object.

const OCRNodeTemplateArea &get_node_template_areas(const std::string &key) const#

Get value in Areas with key.

Warning

The key must be exist in Areas. otherwise, the behavior is undefined and will cause segmentation fault.

Returns:

const std::map<std::string, OCRNodeTemplateArea> & value in Areas at key.

OCRNodeTemplate &set_node_template_areas(const std::string &key, OCRNodeTemplateArea value)#

Set value in Areas with key.

Parameters:
  • key – the key to set.

  • value – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRNodeTemplate the reference of this object.

bool node_template_areas_contains(const std::string &key) const#

Check if the key is exist in Areas.

Returns:

bool true if the key is exist in Areas, otherwise false.

size_t get_node_template_areas_size() const#

Get the size of Areas.

Returns:

size_t the size of Areas

OCRNodeTemplateArea &get_node_template_areas(const std::string &key)#

Get mutable reference of value in Areas with key. A new key and default value will be created if the key does not exist.

Returns:

OCRNodeTemplateArea& the mutable reference of value in Areas at key.

class OCRStringTemplate : public visionflow::param::ISchemable#

OCRStringTemplate Parameter class generated by jinja2 automatically.

String template is used to control how to match characters into strings.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

bool get_enable() const#

Get Enable.

Enable this parameter group.

See also

set_enable()

Returns:

bool Enable

OCRStringTemplate &set_enable(bool enable)#

Set Enable with bool value.

Enable this parameter group.

See also

get_enable()

Parameters:

enable – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRStringTemplate the reference of this object.

int get_max_matches() const#

Get Maximum Matches.

Maximum number of templates to remain within view. Results are sorted based on the deviation of characters from the string, and only the top ‘max_matches’ results are retained. All results are provided by default.

Returns:

int Maximum Matches

OCRStringTemplate &set_max_matches(int max_matches)#

Set Maximum Matches with int value.

Maximum number of templates to remain within view. Results are sorted based on the deviation of characters from the string, and only the top ‘max_matches’ results are retained. All results are provided by default.

Parameters:

max_matches – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRStringTemplate the reference of this object.

int get_min_length() const#

Get Minimum String Length.

String shorter than the minimum length will be ignored.

See also

set_min_length()

Returns:

int Minimum String Length

OCRStringTemplate &set_min_length(int min_length)#

Set Minimum String Length with int value.

String shorter than the minimum length will be ignored.

See also

get_min_length()

Parameters:

min_length – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRStringTemplate the reference of this object.

double get_max_char_interval() const#

Get Maximum Character Interval.

The maximum interval between characters in a string, Two characters with interval longer than this threshold will be matched into two different strings.

Returns:

double Maximum Character Interval

OCRStringTemplate &set_max_char_interval(double max_char_interval)#

Set Maximum Character Interval with double value.

The maximum interval between characters in a string, Two characters with interval longer than this threshold will be matched into two different strings.

Parameters:

max_char_interval – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRStringTemplate the reference of this object.

int get_main_direction() const#

Get String Main Direction.

Direction of strings based on statistics. (It is specified that the positive x-axis direction is 0 degrees, positive values representing the direction towards the positive y-axis, negative values indicating the direction towards the negative y-axis.)

Returns:

int String Main Direction

OCRStringTemplate &set_main_direction(int main_direction)#

Set String Main Direction with int value.

Direction of strings based on statistics. (It is specified that the positive x-axis direction is 0 degrees, positive values representing the direction towards the positive y-axis, negative values indicating the direction towards the negative y-axis.)

Parameters:

main_direction – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRStringTemplate the reference of this object.

int get_angle_range() const#

Get Rotate Angle Range.

The rotate angle range of the string, which means that the string can be rotated slightly within an angular range centered on the main direction.

Returns:

int Rotate Angle Range

OCRStringTemplate &set_angle_range(int angle_range)#

Set Rotate Angle Range with int value.

The rotate angle range of the string, which means that the string can be rotated slightly within an angular range centered on the main direction.

Parameters:

angle_range – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRStringTemplate the reference of this object.

const RegularExpression &get_regular_expression() const#

Get Regular Expression.

Regular expression matching parameters.

Returns:

const RegularExpression & Regular Expression

OCRStringTemplate &set_regular_expression(RegularExpression regular_expression)#

Set Regular Expression with RegularExpression value.

Regular expression matching parameters.

Parameters:

regular_expression – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRStringTemplate the reference of this object.

RegularExpression &get_regular_expression()#

Get mutable reference of Regular Expression.

Regular expression matching parameters.

Returns:

OCRStringTemplate& the mutable reference of the group.

const RegularExpression &get_string_filter_template() const#

Get String Filter Template.

This parameter serves as a filter for the output strings. The user-defined rules in this template determine the expected character types in the output strings. Any string that does not match the template will be filtered out from the final results.

Returns:

const RegularExpression & String Filter Template

OCRStringTemplate &set_string_filter_template(RegularExpression string_filter_template)#

Set String Filter Template with RegularExpression value.

This parameter serves as a filter for the output strings. The user-defined rules in this template determine the expected character types in the output strings. Any string that does not match the template will be filtered out from the final results.

Parameters:

string_filter_template – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRStringTemplate the reference of this object.

RegularExpression &get_string_filter_template()#

Get mutable reference of String Filter Template.

This parameter serves as a filter for the output strings. The user-defined rules in this template determine the expected character types in the output strings. Any string that does not match the template will be filtered out from the final results.

Returns:

OCRStringTemplate& the mutable reference of the group.

const RegularExpression &get_string_fix_template() const#

Get String Fix Template.

This parameter is used to correct the output strings based on user-defined rules. It defines the expected character types in the output strings. If the output strings do not match the template, they will be corrected.

Returns:

const RegularExpression & String Fix Template

OCRStringTemplate &set_string_fix_template(RegularExpression string_fix_template)#

Set String Fix Template with RegularExpression value.

This parameter is used to correct the output strings based on user-defined rules. It defines the expected character types in the output strings. If the output strings do not match the template, they will be corrected.

Parameters:

string_fix_template – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRStringTemplate the reference of this object.

RegularExpression &get_string_fix_template()#

Get mutable reference of String Fix Template.

This parameter is used to correct the output strings based on user-defined rules. It defines the expected character types in the output strings. If the output strings do not match the template, they will be corrected.

Returns:

OCRStringTemplate& the mutable reference of the group.

const TemplateMode &get_template_mode() const#

Get Template Mode.

Set the value type of the central coordinates of the region and the width and height of the area. When the template mode is set to kValueByPixel, X-Value Y-Value W-Value H-Value should be set using pixel value. When the template mode is set to kValueByRatio, X-Value Y-Value W-Value H-Value should be set using ratio value. When the template mode is modified, X-Value Y-Value W-Value H-Value needs to be modified.

Returns:

const TemplateMode & Template Mode

OCRStringTemplate &set_template_mode(TemplateMode template_mode)#

Set Template Mode with TemplateMode value.

Set the value type of the central coordinates of the region and the width and height of the area. When the template mode is set to kValueByPixel, X-Value Y-Value W-Value H-Value should be set using pixel value. When the template mode is set to kValueByRatio, X-Value Y-Value W-Value H-Value should be set using ratio value. When the template mode is modified, X-Value Y-Value W-Value H-Value needs to be modified.

Parameters:

template_mode – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRStringTemplate the reference of this object.

const std::map<std::string, OCRArea> &get_areas() const#

Get Areas.

The areas inside the template. The key of the map is the name of area. The value of the map is the parameter of area.

See also

set_areas()

Returns:

const std::map<std::string, OCRArea> & Areas

OCRStringTemplate &set_areas(std::map<std::string, OCRArea> areas)#

Set Areas with std::map<std::string, OCRArea> value.

The areas inside the template. The key of the map is the name of area. The value of the map is the parameter of area.

See also

get_areas()

Parameters:

areas – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRStringTemplate the reference of this object.

const OCRArea &get_areas(const std::string &key) const#

Get value in Areas with key.

Warning

The key must be exist in Areas. otherwise, the behavior is undefined and will cause segmentation fault.

Returns:

const std::map<std::string, OCRArea> & value in Areas at key.

OCRStringTemplate &set_areas(const std::string &key, OCRArea value)#

Set value in Areas with key.

Parameters:
  • key – the key to set.

  • value – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRStringTemplate the reference of this object.

bool areas_contains(const std::string &key) const#

Check if the key is exist in Areas.

Returns:

bool true if the key is exist in Areas, otherwise false.

size_t get_areas_size() const#

Get the size of Areas.

Returns:

size_t the size of Areas

OCRArea &get_areas(const std::string &key)#

Get mutable reference of value in Areas with key. A new key and default value will be created if the key does not exist.

Returns:

OCRArea& the mutable reference of value in Areas at key.

const std::map<std::string, OCRStringTemplateArea> &get_string_template_areas() const#

Get Areas.

A dictionary mapping unique identifiers to OCRStringTemplateArea objects. Each key-value pair defines an ‘area’ and its matching rules for string template matching. The matching operation is strictly applied within these specified areas.

Returns:

const std::map<std::string, OCRStringTemplateArea> & Areas

OCRStringTemplate &set_string_template_areas(std::map<std::string, OCRStringTemplateArea> string_template_areas)#

Set Areas with std::map<std::string, OCRStringTemplateArea> value.

A dictionary mapping unique identifiers to OCRStringTemplateArea objects. Each key-value pair defines an ‘area’ and its matching rules for string template matching. The matching operation is strictly applied within these specified areas.

Parameters:

string_template_areas – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRStringTemplate the reference of this object.

const OCRStringTemplateArea &get_string_template_areas(const std::string &key) const#

Get value in Areas with key.

Warning

The key must be exist in Areas. otherwise, the behavior is undefined and will cause segmentation fault.

Returns:

const std::map<std::string, OCRStringTemplateArea> & value in Areas at key.

OCRStringTemplate &set_string_template_areas(const std::string &key, OCRStringTemplateArea value)#

Set value in Areas with key.

Parameters:
  • key – the key to set.

  • value – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRStringTemplate the reference of this object.

bool string_template_areas_contains(const std::string &key) const#

Check if the key is exist in Areas.

Returns:

bool true if the key is exist in Areas, otherwise false.

size_t get_string_template_areas_size() const#

Get the size of Areas.

Returns:

size_t the size of Areas

OCRStringTemplateArea &get_string_template_areas(const std::string &key)#

Get mutable reference of value in Areas with key. A new key and default value will be created if the key does not exist.

Returns:

OCRStringTemplateArea& the mutable reference of value in Areas at key.

class OCRInferParameters : public visionflow::param::SchemableParameter#

OCRInferParameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

double get_target_feat_width() const#

Get Target Character Width.

The target character width in inference data.

Returns:

double Target Character Width

OCRInferParameters &set_target_feat_width(double target_feat_width)#

Set Target Character Width with double value.

The target character width in inference data.

Parameters:

target_feat_width – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRInferParameters the reference of this object.

double get_target_feat_height() const#

Get Target Character Height.

The target character height in inference data.

Returns:

double Target Character Height

OCRInferParameters &set_target_feat_height(double target_feat_height)#

Set Target Character Height with double value.

The target character height in inference data.

Parameters:

target_feat_height – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRInferParameters the reference of this object.

double get_threshold() const#

Get Confidence Threshold.

Greater than this threshold will be determined as a target.

See also

set_threshold()

Returns:

double Confidence Threshold

OCRInferParameters &set_threshold(double threshold)#

Set Confidence Threshold with double value.

Greater than this threshold will be determined as a target.

See also

get_threshold()

Parameters:

threshold – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRInferParameters the reference of this object.

double get_density() const#

Get Search Density.

Filter out duplicate results using NMS. A higher value will retain fewer results.

See also

set_density()

Returns:

double Search Density

OCRInferParameters &set_density(double density)#

Set Search Density with double value.

Filter out duplicate results using NMS. A higher value will retain fewer results.

See also

get_density()

Parameters:

density – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRInferParameters the reference of this object.

const std::vector<std::string> &get_allowed_chars() const#

Get Character Set To allowed.

All characters in the inference result belong to the character set.

Returns:

const std::vector<std::string> & Character Set To allowed

OCRInferParameters &set_allowed_chars(std::vector<std::string> allowed_chars)#

Set Character Set To allowed with std::vector<std::string> value.

All characters in the inference result belong to the character set.

Parameters:

allowed_chars – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRInferParameters the reference of this object.

const std::string &get_allowed_chars(size_t index) const#

Get value in Character Set To allowed with index.

Warning

The index must be less than get_allowed_chars_size(). otherwise, the behavior is undefined and will cause segmentation fault.

Returns:

const std::string & value in Character Set To allowed at index.

size_t get_allowed_chars_size() const#

Get the size of Character Set To allowed.

Returns:

size_t the size of Character Set To allowed

class OCRUniversalModelParameters : public visionflow::param::SchemableParameter#

OCRUniversalModelParameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

const OCRAnnulusParameters &get_annulus_recognition() const#

Get Annulus Character Recognition.

Annulus Character Recognition Parameters

Returns:

const OCRAnnulusParameters & Annulus Character Recognition

OCRUniversalModelParameters &set_annulus_recognition(OCRAnnulusParameters annulus_recognition)#

Set Annulus Character Recognition with OCRAnnulusParameters value.

Annulus Character Recognition Parameters

Parameters:

annulus_recognition – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRUniversalModelParameters the reference of this object.

OCRAnnulusParameters &get_annulus_recognition()#

Get mutable reference of Annulus Character Recognition.

Annulus Character Recognition Parameters

Returns:

OCRUniversalModelParameters& the mutable reference of the group.

const PolarityMode &get_polarity() const#

Get Character Polarity.

The polarity of the characters and background in the image. ‘Black On White’ refers to black characters on a white background, ‘White On Black’ refers to white characters on a black background, and ‘Unspecified’ refers to the polarity is not specified or could be either of the former two options.

See also

set_polarity()

Returns:

const PolarityMode & Character Polarity

OCRUniversalModelParameters &set_polarity(PolarityMode polarity)#

Set Character Polarity with PolarityMode value.

The polarity of the characters and background in the image. ‘Black On White’ refers to black characters on a white background, ‘White On Black’ refers to white characters on a black background, and ‘Unspecified’ refers to the polarity is not specified or could be either of the former two options.

See also

get_polarity()

Parameters:

polarity – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRUniversalModelParameters the reference of this object.

class OCRTemplates : public visionflow::param::SchemableParameter#

OCRTemplates Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

const std::map<std::string, OCRStringTemplate> &get_string_templates() const#

Get String Templates.

String templates.

Returns:

const std::map<std::string, OCRStringTemplate> & String Templates

OCRTemplates &set_string_templates(std::map<std::string, OCRStringTemplate> string_templates)#

Set String Templates with std::map<std::string, OCRStringTemplate> value.

String templates.

Parameters:

string_templates – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRTemplates the reference of this object.

const OCRStringTemplate &get_string_templates(const std::string &key) const#

Get value in String Templates with key.

Warning

The key must be exist in String Templates. otherwise, the behavior is undefined and will cause segmentation fault.

Returns:

const std::map<std::string, OCRStringTemplate> & value in String Templates at key.

OCRTemplates &set_string_templates(const std::string &key, OCRStringTemplate value)#

Set value in String Templates with key.

Parameters:
  • key – the key to set.

  • value – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRTemplates the reference of this object.

bool string_templates_contains(const std::string &key) const#

Check if the key is exist in String Templates.

Returns:

bool true if the key is exist in String Templates, otherwise false.

size_t get_string_templates_size() const#

Get the size of String Templates.

Returns:

size_t the size of String Templates

OCRStringTemplate &get_string_templates(const std::string &key)#

Get mutable reference of value in String Templates with key. A new key and default value will be created if the key does not exist.

Returns:

OCRStringTemplate& the mutable reference of value in String Templates at key.

const std::map<std::string, OCRNodeTemplate> &get_node_templates() const#

Get Node Templates.

Node templates.

Returns:

const std::map<std::string, OCRNodeTemplate> & Node Templates

OCRTemplates &set_node_templates(std::map<std::string, OCRNodeTemplate> node_templates)#

Set Node Templates with std::map<std::string, OCRNodeTemplate> value.

Node templates.

Parameters:

node_templates – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRTemplates the reference of this object.

const OCRNodeTemplate &get_node_templates(const std::string &key) const#

Get value in Node Templates with key.

Warning

The key must be exist in Node Templates. otherwise, the behavior is undefined and will cause segmentation fault.

Returns:

const std::map<std::string, OCRNodeTemplate> & value in Node Templates at key.

OCRTemplates &set_node_templates(const std::string &key, OCRNodeTemplate value)#

Set value in Node Templates with key.

Parameters:
  • key – the key to set.

  • value – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRTemplates the reference of this object.

bool node_templates_contains(const std::string &key) const#

Check if the key is exist in Node Templates.

Returns:

bool true if the key is exist in Node Templates, otherwise false.

size_t get_node_templates_size() const#

Get the size of Node Templates.

Returns:

size_t the size of Node Templates

OCRNodeTemplate &get_node_templates(const std::string &key)#

Get mutable reference of value in Node Templates with key. A new key and default value will be created if the key does not exist.

Returns:

OCRNodeTemplate& the mutable reference of value in Node Templates at key.

class OCRAnnulusParameters : public visionflow::param::ISchemable#

OCRAnnulusParameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

bool get_enable() const#

Get Enable.

Enable this parameter group.

See also

set_enable()

Returns:

bool Enable

OCRAnnulusParameters &set_enable(bool enable)#

Set Enable with bool value.

Enable this parameter group.

See also

get_enable()

Parameters:

enable – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRAnnulusParameters the reference of this object.

double get_x() const#

Get Center X.

The x-coordinate of the center of the annulus, set according to the percentage of the view height.

See also

set_x()

Returns:

double Center X

OCRAnnulusParameters &set_x(double x)#

Set Center X with double value.

The x-coordinate of the center of the annulus, set according to the percentage of the view height.

See also

get_x()

Parameters:

x – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRAnnulusParameters the reference of this object.

double get_y() const#

Get Center Y.

The y-coordinate of the center of the annulus, set according to the percentage of the view height.

See also

set_y()

Returns:

double Center Y

OCRAnnulusParameters &set_y(double y)#

Set Center Y with double value.

The y-coordinate of the center of the annulus, set according to the percentage of the view height.

See also

get_y()

Parameters:

y – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRAnnulusParameters the reference of this object.

double get_inner_radius() const#

Get Inner Radius.

The inner radius of the annulus, set according to the percentage of the view height.

Returns:

double Inner Radius

OCRAnnulusParameters &set_inner_radius(double inner_radius)#

Set Inner Radius with double value.

The inner radius of the annulus, set according to the percentage of the view height.

Parameters:

inner_radius – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRAnnulusParameters the reference of this object.

double get_outer_radius() const#

Get Outer Radius.

The outer radius of the annulus, set according to the percentage of the view height.

Returns:

double Outer Radius

OCRAnnulusParameters &set_outer_radius(double outer_radius)#

Set Outer Radius with double value.

The outer radius of the annulus, set according to the percentage of the view height.

Parameters:

outer_radius – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRAnnulusParameters the reference of this object.

double get_start_angle() const#

Get Start Angle.

It is specified that the positive x-axis direction is 0 degrees, positive values representing the direction towards the negative y-axis, negative values indicating the direction towards the positive y-axis.

Returns:

double Start Angle

OCRAnnulusParameters &set_start_angle(double start_angle)#

Set Start Angle with double value.

It is specified that the positive x-axis direction is 0 degrees, positive values representing the direction towards the negative y-axis, negative values indicating the direction towards the positive y-axis.

Parameters:

start_angle – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRAnnulusParameters the reference of this object.

double get_angle_range() const#

Get Angle Range.

The range of angle in which the annulus is unwrapped, if the angle is greater than 360 degrees or less than -360 degrees, the excess part will be unwrapped repeatedly. Positive values representing the direction towards the negative y-axis, negative values indicating the direction towards the positive y-axis.

Returns:

double Angle Range

OCRAnnulusParameters &set_angle_range(double angle_range)#

Set Angle Range with double value.

The range of angle in which the annulus is unwrapped, if the angle is greater than 360 degrees or less than -360 degrees, the excess part will be unwrapped repeatedly. Positive values representing the direction towards the negative y-axis, negative values indicating the direction towards the positive y-axis.

Parameters:

angle_range – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRAnnulusParameters the reference of this object.

class OCRTrainingParameters : public visionflow::param::SchemableParameter#

OCRTrainingParameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

int get_epoch() const#

Get Epochs.

Number of iterations to train. 1 Epoch means all selected images will be trained for 1 time.

See also

set_epoch()

Returns:

int Epochs

OCRTrainingParameters &set_epoch(int epoch)#

Set Epochs with int value.

Number of iterations to train. 1 Epoch means all selected images will be trained for 1 time.

See also

get_epoch()

Parameters:

epoch – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRTrainingParameters the reference of this object.

int get_batch_size() const#

Get Training Batch Size.

The number of images involved in training in each iteration of network training. A suitable batch size can make full use of hardware and improve the convergence speed. Common values are 4, 8, and 16.

See also

set_batch_size()

Returns:

int Training Batch Size

OCRTrainingParameters &set_batch_size(int batch_size)#

Set Training Batch Size with int value.

The number of images involved in training in each iteration of network training. A suitable batch size can make full use of hardware and improve the convergence speed. Common values are 4, 8, and 16.

See also

get_batch_size()

Parameters:

batch_size – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRTrainingParameters the reference of this object.

const TrainingMode &get_training_mode() const#

Get Training Mode.

Normal Train is the default mode for training a new model. Increment Train will retrain on previous model knowledge.

Returns:

const TrainingMode & Training Mode

OCRTrainingParameters &set_training_mode(TrainingMode training_mode)#

Set Training Mode with TrainingMode value.

Normal Train is the default mode for training a new model. Increment Train will retrain on previous model knowledge.

Parameters:

training_mode – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRTrainingParameters the reference of this object.

double get_sampling_ratio() const#

Get Sampling Ratio.

The proportion of new data in incremental training. This parameter is only applicable when the training mode is set to ‘Incremental Train’.

Returns:

double Sampling Ratio

OCRTrainingParameters &set_sampling_ratio(double sampling_ratio)#

Set Sampling Ratio with double value.

The proportion of new data in incremental training. This parameter is only applicable when the training mode is set to ‘Incremental Train’.

Parameters:

sampling_ratio – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRTrainingParameters the reference of this object.

bool get_only_check() const#

Get Only Check.

Default is False. If set to True, the trainer will only check if it is possible to train in the given training mode without actually performing the training.

See also

set_only_check()

Returns:

bool Only Check

OCRTrainingParameters &set_only_check(bool only_check)#

Set Only Check with bool value.

Default is False. If set to True, the trainer will only check if it is possible to train in the given training mode without actually performing the training.

See also

get_only_check()

Parameters:

only_check – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRTrainingParameters the reference of this object.

double get_step_ratio() const#

Get Learning Rate Update Step Ratio.

The ratio of iterations after which the learning rate is decreased.

See also

set_step_ratio()

Returns:

double Learning Rate Update Step Ratio

OCRTrainingParameters &set_step_ratio(double step_ratio)#

Set Learning Rate Update Step Ratio with double value.

The ratio of iterations after which the learning rate is decreased.

See also

get_step_ratio()

Parameters:

step_ratio – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRTrainingParameters the reference of this object.

int get_sigma() const#

Get Gaussian Kernel Size.

Determines the spread of Gaussian distribution used to generate heatmap. A larger value will result in a larger area of distribution, vice versa.

See also

set_sigma()

Returns:

int Gaussian Kernel Size

OCRTrainingParameters &set_sigma(int sigma)#

Set Gaussian Kernel Size with int value.

Determines the spread of Gaussian distribution used to generate heatmap. A larger value will result in a larger area of distribution, vice versa.

See also

get_sigma()

Parameters:

sigma – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRTrainingParameters the reference of this object.

int get_training_feature_size() const#

Get Training Feature Size.

The desired size to which the input features are scaled

Returns:

int Training Feature Size

OCRTrainingParameters &set_training_feature_size(int training_feature_size)#

Set Training Feature Size with int value.

The desired size to which the input features are scaled

Parameters:

training_feature_size – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRTrainingParameters the reference of this object.

const OCRAnnulusParameters &get_annulus_recognition() const#

Get Annulus Character Recognition.

Annulus character recognition parameters for recognizing characters arranged in a circular pattern.

Returns:

const OCRAnnulusParameters & Annulus Character Recognition

OCRTrainingParameters &set_annulus_recognition(OCRAnnulusParameters annulus_recognition)#

Set Annulus Character Recognition with OCRAnnulusParameters value.

Annulus character recognition parameters for recognizing characters arranged in a circular pattern.

Parameters:

annulus_recognition – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRTrainingParameters the reference of this object.

OCRAnnulusParameters &get_annulus_recognition()#

Get mutable reference of Annulus Character Recognition.

Annulus character recognition parameters for recognizing characters arranged in a circular pattern.

Returns:

OCRTrainingParameters& the mutable reference of the group.

const DataAugmentation &get_augmentations() const#

Get Data Augmentation.

Data Augmentation Parameters

Returns:

const DataAugmentation & Data Augmentation

OCRTrainingParameters &set_augmentations(DataAugmentation augmentations)#

Set Data Augmentation with DataAugmentation value.

Data Augmentation Parameters

Parameters:

augmentations – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRTrainingParameters the reference of this object.

DataAugmentation &get_augmentations()#

Get mutable reference of Data Augmentation.

Data Augmentation Parameters

Returns:

OCRTrainingParameters& the mutable reference of the group.

const PolarityMode &get_polarity() const#

Get Character Polarity.

The polarity of the characters and background in the image. ‘Black On White’ refers to black characters on a white background, ‘White On Black’ refers to white characters on a black background, and ‘Unspecified’ refers to the polarity is not specified or could be either of the former two options.

See also

set_polarity()

Returns:

const PolarityMode & Character Polarity

OCRTrainingParameters &set_polarity(PolarityMode polarity)#

Set Character Polarity with PolarityMode value.

The polarity of the characters and background in the image. ‘Black On White’ refers to black characters on a white background, ‘White On Black’ refers to white characters on a black background, and ‘Unspecified’ refers to the polarity is not specified or could be either of the former two options.

See also

get_polarity()

Parameters:

polarity – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

OCRTrainingParameters the reference of this object.

Location Tool Parameters#

class LocationMaxInputSize : public visionflow::param::ISchemable#

LocationMaxInputSize Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

bool get_enable() const#

Get Enable.

Enable this parameter group.

See also

set_enable()

Returns:

bool Enable

LocationMaxInputSize &set_enable(bool enable)#

Set Enable with bool value.

Enable this parameter group.

See also

get_enable()

Parameters:

enable – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

LocationMaxInputSize the reference of this object.

int get_max_side_len() const#

Get Max Input Size.

Scale the long edge of the input image to the maximum side length, and scale the short edge equally, if the algorithm calculates that the required maximum edge length is smaller than this parameter, the maximum edge length will be set automatically

Returns:

int Max Input Size

LocationMaxInputSize &set_max_side_len(int max_side_len)#

Set Max Input Size with int value.

Scale the long edge of the input image to the maximum side length, and scale the short edge equally, if the algorithm calculates that the required maximum edge length is smaller than this parameter, the maximum edge length will be set automatically

Parameters:

max_side_len – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

LocationMaxInputSize the reference of this object.

class LocationModelParameters : public visionflow::param::ISchemable#

LocationModelParameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

const std::string &get_model_arch() const#

Get Model Architecture.

There are two different model architectures: the High-Precision-Location model and Fast-Location model, The high-precision version is suitable for scenarios with positioning accuracy up to 1 pixel, and the fast version is suitable for most scenarios with shorter training, inference time and lower GPU memory requirements.

See also

set_model_arch()

Returns:

const std::string & Model Architecture

LocationModelParameters &set_model_arch(std::string model_arch)#

Set Model Architecture with std::string value.

There are two different model architectures: the High-Precision-Location model and Fast-Location model, The high-precision version is suitable for scenarios with positioning accuracy up to 1 pixel, and the fast version is suitable for most scenarios with shorter training, inference time and lower GPU memory requirements.

See also

get_model_arch()

Parameters:

model_arch – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

LocationModelParameters the reference of this object.

bool get_train_angle() const#

Get Training With Angle.

Enable this option to training the model with the angle information in the label

Returns:

bool Training With Angle

LocationModelParameters &set_train_angle(bool train_angle)#

Set Training With Angle with bool value.

Enable this option to training the model with the angle information in the label

Parameters:

train_angle – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

LocationModelParameters the reference of this object.

bool get_train_rect() const#

Get Training With Rect Size.

Enable this option to training the model with the the rectangle size information of the target box

See also

set_train_rect()

Returns:

bool Training With Rect Size

LocationModelParameters &set_train_rect(bool train_rect)#

Set Training With Rect Size with bool value.

Enable this option to training the model with the the rectangle size information of the target box

See also

get_train_rect()

Parameters:

train_rect – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

LocationModelParameters the reference of this object.

class LocationTargetParameters : public visionflow::param::ISchemable#

LocationTargetParameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

double get_min_target_width() const#

Get Minimum Target Width.

The Minimum target width (Pixel value in X-axis direction)

Returns:

double Minimum Target Width

LocationTargetParameters &set_min_target_width(double min_target_width)#

Set Minimum Target Width with double value.

The Minimum target width (Pixel value in X-axis direction)

Parameters:

min_target_width – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

LocationTargetParameters the reference of this object.

double get_min_target_height() const#

Get Minimum Target Height.

The Minimum target height (Pixel value in Y-axis direction)

Returns:

double Minimum Target Height

LocationTargetParameters &set_min_target_height(double min_target_height)#

Set Minimum Target Height with double value.

The Minimum target height (Pixel value in Y-axis direction)

Parameters:

min_target_height – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

LocationTargetParameters the reference of this object.

class NodeMatchTemplate : public visionflow::param::ISchemable#

NodeMatchTemplate Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

bool get_enable() const#

Get Enable.

Enable this parameter group.

See also

set_enable()

Returns:

bool Enable

NodeMatchTemplate &set_enable(bool enable)#

Set Enable with bool value.

Enable this parameter group.

See also

get_enable()

Parameters:

enable – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

NodeMatchTemplate the reference of this object.

const TemplateMode &get_template_mode() const#

Get Template Mode.

Set the value type of points and offset. When the template mode is set to kValueByPixel, the Coordinates of points and the offset should be set using pixel value. When the template mode is set to kValueByRatio, the Coordinates of points and the offset should be set using ratio value. When the Area Value Type is modified, the Coordinates of points and the offset should be modified.

Returns:

const TemplateMode & Template Mode

NodeMatchTemplate &set_template_mode(TemplateMode template_mode)#

Set Template Mode with TemplateMode value.

Set the value type of points and offset. When the template mode is set to kValueByPixel, the Coordinates of points and the offset should be set using pixel value. When the template mode is set to kValueByRatio, the Coordinates of points and the offset should be set using ratio value. When the Area Value Type is modified, the Coordinates of points and the offset should be modified.

Parameters:

template_mode – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

NodeMatchTemplate the reference of this object.

int get_max_match_results_num() const#

Get Max Match Results Num.

the maximum number of template matching results. When the value is - 1, the maximum number of matching results is not limited.

Returns:

int Max Match Results Num

NodeMatchTemplate &set_max_match_results_num(int max_match_results_num)#

Set Max Match Results Num with int value.

the maximum number of template matching results. When the value is - 1, the maximum number of matching results is not limited.

Parameters:

max_match_results_num – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

NodeMatchTemplate the reference of this object.

int get_max_miss_points_num() const#

Get Max Miss Points Num.

The number of points allowed to be missed during matching

Returns:

int Max Miss Points Num

NodeMatchTemplate &set_max_miss_points_num(int max_miss_points_num)#

Set Max Miss Points Num with int value.

The number of points allowed to be missed during matching

Parameters:

max_miss_points_num – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

NodeMatchTemplate the reference of this object.

const std::vector<KeyPointNode> &get_points() const#

Get Keypoints.

The key points of the template

See also

set_points()

Returns:

const std::vector<KeyPointNode> & Keypoints

NodeMatchTemplate &set_points(std::vector<KeyPointNode> points)#

Set Keypoints with std::vector<KeyPointNode> value.

The key points of the template

See also

get_points()

Parameters:

points – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

NodeMatchTemplate the reference of this object.

const KeyPointNode &get_points(size_t index) const#

Get value in Keypoints with index.

Warning

The index must be less than get_points_size(). otherwise, the behavior is undefined and will cause segmentation fault.

Returns:

const KeyPointNode & value in Keypoints at index.

size_t get_points_size() const#

Get the size of Keypoints.

Returns:

size_t the size of Keypoints

KeyPointNode &get_points(size_t index)#

Get mutable reference of value in Keypoints with index.

Warning

The index must be less than get_points_size(). otherwise, the behavior is undefined and will cause segmentation fault.

Returns:

KeyPointNode& the mutable reference of value in Keypoints at index.

double get_max_distance() const#

Get Max Distance.

The maximum allowed distance between the template keypoints and the keypoints to be matched. Results with a distance greater than this value will be filtered out. The value can be either in absolute pixel or relative to the view height, depending on the template_mode.

Returns:

double Max Distance

NodeMatchTemplate &set_max_distance(double max_distance)#

Set Max Distance with double value.

The maximum allowed distance between the template keypoints and the keypoints to be matched. Results with a distance greater than this value will be filtered out. The value can be either in absolute pixel or relative to the view height, depending on the template_mode.

Parameters:

max_distance – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

NodeMatchTemplate the reference of this object.

bool get_is_scalable() const#

Get Target Scalable.

Enable this option if the scale of target to be matched is not fixed, And you should set the target scale range

Returns:

bool Target Scalable

NodeMatchTemplate &set_is_scalable(bool is_scalable)#

Set Target Scalable with bool value.

Enable this option if the scale of target to be matched is not fixed, And you should set the target scale range

Parameters:

is_scalable – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

NodeMatchTemplate the reference of this object.

const std::vector<double> &get_scale_range() const#

Get Scale Range.

The target scale range

Returns:

const std::vector<double> & Scale Range

NodeMatchTemplate &set_scale_range(std::vector<double> scale_range)#

Set Scale Range with std::vector<double> value.

The target scale range

Parameters:

scale_range – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

NodeMatchTemplate the reference of this object.

bool scale_range_contains(double value) const#

Check if the Scale Range contains the value.

Returns:

bool true if the Scale Range contains the value, otherwise false.

double get_scale_range_left() const#

Get left point value of Scale Range.

Returns:

const std::vector<double> & left point value of Scale Range

double get_scale_range_right() const#

Get the right point value of Scale Range.

Returns:

const std::vector<double> & the right point value of Scale Range

NodeMatchTemplate &set_scale_range_left(double scale_range_left)#

Set left point value of Scale Range with std::vector<double> value.

The target scale range

Parameters:

scale_range_left – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

NodeMatchTemplate the reference of this object.

NodeMatchTemplate &set_scale_range_right(double scale_range_right)#

Set the right point value of Scale Range with std::vector<double> value.

The target scale range

Parameters:

scale_range_right – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

NodeMatchTemplate the reference of this object.

bool get_is_rotatable() const#

Get Target Rotatable.

Enable this option if the angle of target to be matched is not fixed, And you should set the target rotate angle range

Returns:

bool Target Rotatable

NodeMatchTemplate &set_is_rotatable(bool is_rotatable)#

Set Target Rotatable with bool value.

Enable this option if the angle of target to be matched is not fixed, And you should set the target rotate angle range

Parameters:

is_rotatable – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

NodeMatchTemplate the reference of this object.

const std::vector<double> &get_rotate_range() const#

Get Rotate Range (Degree).

The target rotate range

Returns:

const std::vector<double> & Rotate Range (Degree)

NodeMatchTemplate &set_rotate_range(std::vector<double> rotate_range)#

Set Rotate Range (Degree) with std::vector<double> value.

The target rotate range

Parameters:

rotate_range – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

NodeMatchTemplate the reference of this object.

bool rotate_range_contains(double value) const#

Check if the Rotate Range (Degree) contains the value.

Returns:

bool true if the Rotate Range (Degree) contains the value, otherwise false.

double get_rotate_range_left() const#

Get left point value of Rotate Range (Degree).

Returns:

const std::vector<double> & left point value of Rotate Range (Degree)

double get_rotate_range_right() const#

Get the right point value of Rotate Range (Degree).

Returns:

const std::vector<double> & the right point value of Rotate Range (Degree)

NodeMatchTemplate &set_rotate_range_left(double rotate_range_left)#

Set left point value of Rotate Range (Degree) with std::vector<double> value.

The target rotate range

Parameters:

rotate_range_left – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

NodeMatchTemplate the reference of this object.

NodeMatchTemplate &set_rotate_range_right(double rotate_range_right)#

Set the right point value of Rotate Range (Degree) with std::vector<double> value.

The target rotate range

Parameters:

rotate_range_right – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

NodeMatchTemplate the reference of this object.

double get_template_angle() const#

Get Template angle (Degree).

Template angle is calculated and displayed the software in real time

Returns:

double Template angle (Degree)

NodeMatchTemplate &set_template_angle(double template_angle)#

Set Template angle (Degree) with double value.

Template angle is calculated and displayed the software in real time

Parameters:

template_angle – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

NodeMatchTemplate the reference of this object.

class LocationTemplates : public visionflow::param::SchemableParameter#

LocationTemplates Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

const std::map<std::string, NodeMatchTemplate> &get_node_templates() const#

Get Node Templates.

Location node match templates

Returns:

const std::map<std::string, NodeMatchTemplate> & Node Templates

LocationTemplates &set_node_templates(std::map<std::string, NodeMatchTemplate> node_templates)#

Set Node Templates with std::map<std::string, NodeMatchTemplate> value.

Location node match templates

Parameters:

node_templates – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

LocationTemplates the reference of this object.

const NodeMatchTemplate &get_node_templates(const std::string &key) const#

Get value in Node Templates with key.

Warning

The key must be exist in Node Templates. otherwise, the behavior is undefined and will cause segmentation fault.

Returns:

const std::map<std::string, NodeMatchTemplate> & value in Node Templates at key.

LocationTemplates &set_node_templates(const std::string &key, NodeMatchTemplate value)#

Set value in Node Templates with key.

Parameters:
  • key – the key to set.

  • value – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

LocationTemplates the reference of this object.

bool node_templates_contains(const std::string &key) const#

Check if the key is exist in Node Templates.

Returns:

bool true if the key is exist in Node Templates, otherwise false.

size_t get_node_templates_size() const#

Get the size of Node Templates.

Returns:

size_t the size of Node Templates

NodeMatchTemplate &get_node_templates(const std::string &key)#

Get mutable reference of value in Node Templates with key. A new key and default value will be created if the key does not exist.

Returns:

NodeMatchTemplate& the mutable reference of value in Node Templates at key.

class LocationTrainingParameters : public visionflow::param::SchemableParameter#

LocationTrainingParameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

int get_epoch() const#

Get Epochs.

Number of iterations to train. 1 Epoch means all selected images will be trained for 1 time.

See also

set_epoch()

Returns:

int Epochs

LocationTrainingParameters &set_epoch(int epoch)#

Set Epochs with int value.

Number of iterations to train. 1 Epoch means all selected images will be trained for 1 time.

See also

get_epoch()

Parameters:

epoch – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

LocationTrainingParameters the reference of this object.

int get_batch_size() const#

Get Training Batch Size.

The number of images involved in training in each iteration of network training. A suitable batch size can make full use of hardware and improve the convergence speed. Common values are 4, 8, and 16. The classification module needs to be set larger, generally 32, 64

See also

set_batch_size()

Returns:

int Training Batch Size

LocationTrainingParameters &set_batch_size(int batch_size)#

Set Training Batch Size with int value.

The number of images involved in training in each iteration of network training. A suitable batch size can make full use of hardware and improve the convergence speed. Common values are 4, 8, and 16. The classification module needs to be set larger, generally 32, 64

See also

get_batch_size()

Parameters:

batch_size – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

LocationTrainingParameters the reference of this object.

const LocationMaxInputSize &get_input_shape() const#

Get Customize Network Input Shape.

Set the maximum side length of the input image.

Returns:

const LocationMaxInputSize & Customize Network Input Shape

LocationTrainingParameters &set_input_shape(LocationMaxInputSize input_shape)#

Set Customize Network Input Shape with LocationMaxInputSize value.

Set the maximum side length of the input image.

Parameters:

input_shape – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

LocationTrainingParameters the reference of this object.

LocationMaxInputSize &get_input_shape()#

Get mutable reference of Customize Network Input Shape.

Set the maximum side length of the input image.

Returns:

LocationTrainingParameters& the mutable reference of the group.

const LocationModelParameters &get_model_param() const#

Get Model param.

Location model parameters

Returns:

const LocationModelParameters & Model param

LocationTrainingParameters &set_model_param(LocationModelParameters model_param)#

Set Model param with LocationModelParameters value.

Location model parameters

Parameters:

model_param – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

LocationTrainingParameters the reference of this object.

LocationModelParameters &get_model_param()#

Get mutable reference of Model param.

Location model parameters

Returns:

LocationTrainingParameters& the mutable reference of the group.

const LocationTargetParameters &get_target_feature() const#

Get Target Feature.

Location Target Feature Parameters

Returns:

const LocationTargetParameters & Target Feature

LocationTrainingParameters &set_target_feature(LocationTargetParameters target_feature)#

Set Target Feature with LocationTargetParameters value.

Location Target Feature Parameters

Parameters:

target_feature – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

LocationTrainingParameters the reference of this object.

LocationTargetParameters &get_target_feature()#

Get mutable reference of Target Feature.

Location Target Feature Parameters

Returns:

LocationTrainingParameters& the mutable reference of the group.

const DataAugmentation &get_augmentations() const#

Get Data Augmentation.

Data Augmentation Parameters

Returns:

const DataAugmentation & Data Augmentation

LocationTrainingParameters &set_augmentations(DataAugmentation augmentations)#

Set Data Augmentation with DataAugmentation value.

Data Augmentation Parameters

Parameters:

augmentations – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

LocationTrainingParameters the reference of this object.

DataAugmentation &get_augmentations()#

Get mutable reference of Data Augmentation.

Data Augmentation Parameters

Returns:

LocationTrainingParameters& the mutable reference of the group.

class LocationFilterParameters : public visionflow::param::SchemableParameter#

LocationFilterParameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

double get_threshold() const#

Get Confidence Threshold.

Keypoints with confidence greater than this threshold will be determined as a character target.

See also

set_threshold()

Returns:

double Confidence Threshold

LocationFilterParameters &set_threshold(double threshold)#

Set Confidence Threshold with double value.

Keypoints with confidence greater than this threshold will be determined as a character target.

See also

get_threshold()

Parameters:

threshold – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

LocationFilterParameters the reference of this object.

double get_target_overlap_ratio() const#

Get Target Overlap Ratio.

Some redundant points will be removed to ensure that the intersection ratio between points within each category does not exceed this value.target_overlap_ratio = intersection_area/Union_area.

Returns:

double Target Overlap Ratio

LocationFilterParameters &set_target_overlap_ratio(double target_overlap_ratio)#

Set Target Overlap Ratio with double value.

Some redundant points will be removed to ensure that the intersection ratio between points within each category does not exceed this value.target_overlap_ratio = intersection_area/Union_area.

Parameters:

target_overlap_ratio – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

LocationFilterParameters the reference of this object.

AssemblyVerification Tool Parameters#

class AssemblyVerificationMaxInputSize : public visionflow::param::ISchemable#

AssemblyVerificationMaxInputSize Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

bool get_enable() const#

Get Enable.

Enable this parameter group.

See also

set_enable()

Returns:

bool Enable

AssemblyVerificationMaxInputSize &set_enable(bool enable)#

Set Enable with bool value.

Enable this parameter group.

See also

get_enable()

Parameters:

enable – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

AssemblyVerificationMaxInputSize the reference of this object.

int get_max_side_len() const#

Get Max Input Size.

Scale the long edge of the input image to the maximum side length, and scale the short edge equally, if the algorithm calculates that the required maximum edge length is smaller than this parameter, the maximum edge length will be set automatically

Returns:

int Max Input Size

AssemblyVerificationMaxInputSize &set_max_side_len(int max_side_len)#

Set Max Input Size with int value.

Scale the long edge of the input image to the maximum side length, and scale the short edge equally, if the algorithm calculates that the required maximum edge length is smaller than this parameter, the maximum edge length will be set automatically

Parameters:

max_side_len – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

AssemblyVerificationMaxInputSize the reference of this object.

class AssemblyVerificationModelParameters : public visionflow::param::ISchemable#

AssemblyVerificationModelParameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

bool get_train_angle() const#

Get Training With Angle.

Enable this option to training the model with the angle information in the label

Returns:

bool Training With Angle

AssemblyVerificationModelParameters &set_train_angle(bool train_angle)#

Set Training With Angle with bool value.

Enable this option to training the model with the angle information in the label

Parameters:

train_angle – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

AssemblyVerificationModelParameters the reference of this object.

bool get_train_rect() const#

Get Training With Rect Size.

Enable this option to training the model with the the rectangle size information of the target box

See also

set_train_rect()

Returns:

bool Training With Rect Size

AssemblyVerificationModelParameters &set_train_rect(bool train_rect)#

Set Training With Rect Size with bool value.

Enable this option to training the model with the the rectangle size information of the target box

See also

get_train_rect()

Parameters:

train_rect – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

AssemblyVerificationModelParameters the reference of this object.

class AssemblyVerificationTargetParameters : public visionflow::param::ISchemable#

AssemblyVerificationTargetParameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

double get_min_target_width() const#

Get Minimum Target Width.

The Minimum target width (Pixel value in X-axis direction)

Returns:

double Minimum Target Width

AssemblyVerificationTargetParameters &set_min_target_width(double min_target_width)#

Set Minimum Target Width with double value.

The Minimum target width (Pixel value in X-axis direction)

Parameters:

min_target_width – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

AssemblyVerificationTargetParameters the reference of this object.

double get_min_target_height() const#

Get Minimum Target Height.

The Minimum target height (Pixel value in Y-axis direction)

Returns:

double Minimum Target Height

AssemblyVerificationTargetParameters &set_min_target_height(double min_target_height)#

Set Minimum Target Height with double value.

The Minimum target height (Pixel value in Y-axis direction)

Parameters:

min_target_height – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

AssemblyVerificationTargetParameters the reference of this object.

class AssemblyVerificationLayOutArea : public visionflow::param::ISchemable#

AssemblyVerificationLayOutArea Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

double get_x() const#

Get X-Value.

X-direction coordinate value of the center of the area. When the template mode is set to kValueByPixel, X-Value should be set using pixel value. When the template mode is set to kValueByRatio, X-Value should be set using ratio value. When the template mode is modified, X-Value needs to be modified.

See also

set_x()

Returns:

double X-Value

AssemblyVerificationLayOutArea &set_x(double x)#

Set X-Value with double value.

X-direction coordinate value of the center of the area. When the template mode is set to kValueByPixel, X-Value should be set using pixel value. When the template mode is set to kValueByRatio, X-Value should be set using ratio value. When the template mode is modified, X-Value needs to be modified.

See also

get_x()

Parameters:

x – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

AssemblyVerificationLayOutArea the reference of this object.

double get_y() const#

Get Y-Value.

Y-direction coordinate value of the center of the area. When the template mode is set to kValueByPixel, Y-Value should be set using pixel value. When the template mode is set to kValueByRatio, Y-Value should be set using ratio value. When the template mode is modified, Y-Value needs to be modified.

See also

set_y()

Returns:

double Y-Value

AssemblyVerificationLayOutArea &set_y(double y)#

Set Y-Value with double value.

Y-direction coordinate value of the center of the area. When the template mode is set to kValueByPixel, Y-Value should be set using pixel value. When the template mode is set to kValueByRatio, Y-Value should be set using ratio value. When the template mode is modified, Y-Value needs to be modified.

See also

get_y()

Parameters:

y – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

AssemblyVerificationLayOutArea the reference of this object.

double get_w() const#

Get W-Value.

width of the area. When the template mode is set to kValueByPixel, W-Value should be set using pixel value. When the template mode is set to kValueByRatio, W-Value should be set using ratio value. When the template mode is modified, W-Value needs to be modified.

See also

set_w()

Returns:

double W-Value

AssemblyVerificationLayOutArea &set_w(double w)#

Set W-Value with double value.

width of the area. When the template mode is set to kValueByPixel, W-Value should be set using pixel value. When the template mode is set to kValueByRatio, W-Value should be set using ratio value. When the template mode is modified, W-Value needs to be modified.

See also

get_w()

Parameters:

w – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

AssemblyVerificationLayOutArea the reference of this object.

double get_h() const#

Get H-Value.

height of the area. When the template mode is set to kValueByPixel, H-Value should be set using pixel value. When the template mode is set to kValueRatio, H-Value should be set using ratio value. When the template mode is modified, H-Value needs to be modified.

See also

set_h()

Returns:

double H-Value

AssemblyVerificationLayOutArea &set_h(double h)#

Set H-Value with double value.

height of the area. When the template mode is set to kValueByPixel, H-Value should be set using pixel value. When the template mode is set to kValueRatio, H-Value should be set using ratio value. When the template mode is modified, H-Value needs to be modified.

See also

get_h()

Parameters:

h – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

AssemblyVerificationLayOutArea the reference of this object.

const std::vector<std::string> &get_target_category() const#

Get Target Category.

Categories of targets in the area

Returns:

const std::vector<std::string> & Target Category

AssemblyVerificationLayOutArea &set_target_category(std::vector<std::string> target_category)#

Set Target Category with std::vector<std::string> value.

Categories of targets in the area

Parameters:

target_category – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

AssemblyVerificationLayOutArea the reference of this object.

const std::string &get_target_category(size_t index) const#

Get value in Target Category with index.

Warning

The index must be less than get_target_category_size(). otherwise, the behavior is undefined and will cause segmentation fault.

Returns:

const std::string & value in Target Category at index.

size_t get_target_category_size() const#

Get the size of Target Category.

Returns:

size_t the size of Target Category

int get_target_number() const#

Get Target Number.

Number of targets in the region

Returns:

int Target Number

AssemblyVerificationLayOutArea &set_target_number(int target_number)#

Set Target Number with int value.

Number of targets in the region

Parameters:

target_number – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

AssemblyVerificationLayOutArea the reference of this object.

bool get_use_target_angle_range() const#

Get Use Target Angle Range.

Enable this option if the angle of target to be matched needs to belimited, And you should set the target angle range.

Returns:

bool Use Target Angle Range

AssemblyVerificationLayOutArea &set_use_target_angle_range(bool use_target_angle_range)#

Set Use Target Angle Range with bool value.

Enable this option if the angle of target to be matched needs to belimited, And you should set the target angle range.

Parameters:

use_target_angle_range – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

AssemblyVerificationLayOutArea the reference of this object.

const std::vector<double> &get_target_angle_range() const#

Get Target Angle Range (Degree).

The angle range target limited to

Returns:

const std::vector<double> & Target Angle Range (Degree)

AssemblyVerificationLayOutArea &set_target_angle_range(std::vector<double> target_angle_range)#

Set Target Angle Range (Degree) with std::vector<double> value.

The angle range target limited to

Parameters:

target_angle_range – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

AssemblyVerificationLayOutArea the reference of this object.

bool target_angle_range_contains(double value) const#

Check if the Target Angle Range (Degree) contains the value.

Returns:

bool true if the Target Angle Range (Degree) contains the value, otherwise false.

double get_target_angle_range_left() const#

Get left point value of Target Angle Range (Degree).

Returns:

const std::vector<double> & left point value of Target Angle Range (Degree)

double get_target_angle_range_right() const#

Get the right point value of Target Angle Range (Degree).

Returns:

const std::vector<double> & the right point value of Target Angle Range (Degree)

AssemblyVerificationLayOutArea &set_target_angle_range_left(double target_angle_range_left)#

Set left point value of Target Angle Range (Degree) with std::vector<double> value.

The angle range target limited to

Parameters:

target_angle_range_left – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

AssemblyVerificationLayOutArea the reference of this object.

AssemblyVerificationLayOutArea &set_target_angle_range_right(double target_angle_range_right)#

Set the right point value of Target Angle Range (Degree) with std::vector<double> value.

The angle range target limited to

Parameters:

target_angle_range_right – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

AssemblyVerificationLayOutArea the reference of this object.

class AssemblyVerificationTemplates : public visionflow::param::SchemableParameter#

AssemblyVerificationTemplates Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

const TemplateMode &get_template_mode() const#

Get Template Mode.

Set the Value Type of the central coordinates of the region and the width and height of the area. When the template mode is set to kValueByPixel, X-Value Y-Value W-Value H-Value should be set using pixel value. When the template mode is set to kValueByRatio, X-Value Y-Value W-Value H-Value should be set using ratio value. When the template mode is modified, X-Value Y-Value W-Value H-Value needs to be modified.

Returns:

const TemplateMode & Template Mode

AssemblyVerificationTemplates &set_template_mode(TemplateMode template_mode)#

Set Template Mode with TemplateMode value.

Set the Value Type of the central coordinates of the region and the width and height of the area. When the template mode is set to kValueByPixel, X-Value Y-Value W-Value H-Value should be set using pixel value. When the template mode is set to kValueByRatio, X-Value Y-Value W-Value H-Value should be set using ratio value. When the template mode is modified, X-Value Y-Value W-Value H-Value needs to be modified.

Parameters:

template_mode – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

AssemblyVerificationTemplates the reference of this object.

const std::map<std::string, AssemblyVerificationLayOutArea> &get_areas() const#

Get Areas.

The areas inside the template. The key of the map is the name of area. The value of the map is the parameter of area.

See also

set_areas()

Returns:

const std::map<std::string, AssemblyVerificationLayOutArea> & Areas

AssemblyVerificationTemplates &set_areas(std::map<std::string, AssemblyVerificationLayOutArea> areas)#

Set Areas with std::map<std::string, AssemblyVerificationLayOutArea> value.

The areas inside the template. The key of the map is the name of area. The value of the map is the parameter of area.

See also

get_areas()

Parameters:

areas – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

AssemblyVerificationTemplates the reference of this object.

const AssemblyVerificationLayOutArea &get_areas(const std::string &key) const#

Get value in Areas with key.

Warning

The key must be exist in Areas. otherwise, the behavior is undefined and will cause segmentation fault.

Returns:

const std::map<std::string, AssemblyVerificationLayOutArea> & value in Areas at key.

AssemblyVerificationTemplates &set_areas(const std::string &key, AssemblyVerificationLayOutArea value)#

Set value in Areas with key.

Parameters:
  • key – the key to set.

  • value – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

AssemblyVerificationTemplates the reference of this object.

bool areas_contains(const std::string &key) const#

Check if the key is exist in Areas.

Returns:

bool true if the key is exist in Areas, otherwise false.

size_t get_areas_size() const#

Get the size of Areas.

Returns:

size_t the size of Areas

AssemblyVerificationLayOutArea &get_areas(const std::string &key)#

Get mutable reference of value in Areas with key. A new key and default value will be created if the key does not exist.

Returns:

AssemblyVerificationLayOutArea& the mutable reference of value in Areas at key.

class AssemblyVerificationTrainingParameters : public visionflow::param::SchemableParameter#

AssemblyVerificationTrainingParameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

int get_epoch() const#

Get Epochs.

Number of iterations to train. 1 Epoch means all selected images will be trained for 1 time.

See also

set_epoch()

Returns:

int Epochs

AssemblyVerificationTrainingParameters &set_epoch(int epoch)#

Set Epochs with int value.

Number of iterations to train. 1 Epoch means all selected images will be trained for 1 time.

See also

get_epoch()

Parameters:

epoch – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

AssemblyVerificationTrainingParameters the reference of this object.

int get_batch_size() const#

Get Training Batch Size.

The number of images involved in training in each iteration of network training. A suitable batch size can make full use of hardware and improve the convergence speed. Common values are 4, 8, and 16. The classification module needs to be set larger, generally 32, 64

See also

set_batch_size()

Returns:

int Training Batch Size

AssemblyVerificationTrainingParameters &set_batch_size(int batch_size)#

Set Training Batch Size with int value.

The number of images involved in training in each iteration of network training. A suitable batch size can make full use of hardware and improve the convergence speed. Common values are 4, 8, and 16. The classification module needs to be set larger, generally 32, 64

See also

get_batch_size()

Parameters:

batch_size – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

AssemblyVerificationTrainingParameters the reference of this object.

const AssemblyVerificationMaxInputSize &get_input_shape() const#

Get Customize Network Input Shape.

Set the maximum side length of the input image.

Returns:

const AssemblyVerificationMaxInputSize & Customize Network Input Shape

AssemblyVerificationTrainingParameters &set_input_shape(AssemblyVerificationMaxInputSize input_shape)#

Set Customize Network Input Shape with AssemblyVerificationMaxInputSize value.

Set the maximum side length of the input image.

Parameters:

input_shape – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

AssemblyVerificationTrainingParameters the reference of this object.

AssemblyVerificationMaxInputSize &get_input_shape()#

Get mutable reference of Customize Network Input Shape.

Set the maximum side length of the input image.

Returns:

AssemblyVerificationTrainingParameters& the mutable reference of the group.

const AssemblyVerificationModelParameters &get_model_param() const#

Get Model param.

AssemblyVerification model parameters

Returns:

const AssemblyVerificationModelParameters & Model param

AssemblyVerificationTrainingParameters &set_model_param(AssemblyVerificationModelParameters model_param)#

Set Model param with AssemblyVerificationModelParameters value.

AssemblyVerification model parameters

Parameters:

model_param – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

AssemblyVerificationTrainingParameters the reference of this object.

AssemblyVerificationModelParameters &get_model_param()#

Get mutable reference of Model param.

AssemblyVerification model parameters

Returns:

AssemblyVerificationTrainingParameters& the mutable reference of the group.

const AssemblyVerificationTargetParameters &get_target_feature() const#

Get Target Feature.

AssemblyVerification Target Feature Parameters

Returns:

const AssemblyVerificationTargetParameters & Target Feature

AssemblyVerificationTrainingParameters &set_target_feature(AssemblyVerificationTargetParameters target_feature)#

Set Target Feature with AssemblyVerificationTargetParameters value.

AssemblyVerification Target Feature Parameters

Parameters:

target_feature – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

AssemblyVerificationTrainingParameters the reference of this object.

AssemblyVerificationTargetParameters &get_target_feature()#

Get mutable reference of Target Feature.

AssemblyVerification Target Feature Parameters

Returns:

AssemblyVerificationTrainingParameters& the mutable reference of the group.

const DataAugmentation &get_augmentations() const#

Get Data Augmentation.

Data Augmentation Parameters

Returns:

const DataAugmentation & Data Augmentation

AssemblyVerificationTrainingParameters &set_augmentations(DataAugmentation augmentations)#

Set Data Augmentation with DataAugmentation value.

Data Augmentation Parameters

Parameters:

augmentations – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

AssemblyVerificationTrainingParameters the reference of this object.

DataAugmentation &get_augmentations()#

Get mutable reference of Data Augmentation.

Data Augmentation Parameters

Returns:

AssemblyVerificationTrainingParameters& the mutable reference of the group.

class AssemblyVerificationFilterParameters : public visionflow::param::SchemableParameter#

AssemblyVerificationFilterParameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

double get_threshold() const#

Get Confidence Threshold.

Keypoints with confidence greater than this threshold will be determined as a character target.

See also

set_threshold()

Returns:

double Confidence Threshold

AssemblyVerificationFilterParameters &set_threshold(double threshold)#

Set Confidence Threshold with double value.

Keypoints with confidence greater than this threshold will be determined as a character target.

See also

get_threshold()

Parameters:

threshold – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

AssemblyVerificationFilterParameters the reference of this object.

double get_density() const#

Get Search Density.

Keep only one result within the radius of target size * density

See also

set_density()

Returns:

double Search Density

AssemblyVerificationFilterParameters &set_density(double density)#

Set Search Density with double value.

Keep only one result within the radius of target size * density

See also

get_density()

Parameters:

density – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

AssemblyVerificationFilterParameters the reference of this object.

Classification Tool Parameters#

class ClassificationInputShape : public visionflow::param::ISchemable#

ClassificationInputShape Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

bool get_enable() const#

Get Enable.

Enable this parameter group.

See also

set_enable()

Returns:

bool Enable

ClassificationInputShape &set_enable(bool enable)#

Set Enable with bool value.

Enable this parameter group.

See also

get_enable()

Parameters:

enable – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ClassificationInputShape the reference of this object.

int get_base_input_width() const#

Get Input Image Width.

Base Input Width

Returns:

int Input Image Width

ClassificationInputShape &set_base_input_width(int base_input_width)#

Set Input Image Width with int value.

Base Input Width

Parameters:

base_input_width – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ClassificationInputShape the reference of this object.

int get_base_input_height() const#

Get Input Image Height.

Base Input Height

Returns:

int Input Image Height

ClassificationInputShape &set_base_input_height(int base_input_height)#

Set Input Image Height with int value.

Base Input Height

Parameters:

base_input_height – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ClassificationInputShape the reference of this object.

class ClassificationTrainingParameters : public visionflow::param::SchemableParameter#

ClassificationTrainingParameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

int get_epoch() const#

Get Epochs.

Number of iterations to train. 1 Epoch means all selected images will be trained for 1 time.

See also

set_epoch()

Returns:

int Epochs

ClassificationTrainingParameters &set_epoch(int epoch)#

Set Epochs with int value.

Number of iterations to train. 1 Epoch means all selected images will be trained for 1 time.

See also

get_epoch()

Parameters:

epoch – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ClassificationTrainingParameters the reference of this object.

int get_batch_size() const#

Get Training Batch Size.

The number of images involved in training in each iteration of network training. A suitable batch size can make full use of hardware and improve the convergence speed. Common values are 4, 8, and 16. The classification module needs to be set larger, generally 32, 64

See also

set_batch_size()

Returns:

int Training Batch Size

ClassificationTrainingParameters &set_batch_size(int batch_size)#

Set Training Batch Size with int value.

The number of images involved in training in each iteration of network training. A suitable batch size can make full use of hardware and improve the convergence speed. Common values are 4, 8, and 16. The classification module needs to be set larger, generally 32, 64

See also

get_batch_size()

Parameters:

batch_size – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ClassificationTrainingParameters the reference of this object.

const ClassificationInputShape &get_input_shape() const#

Get Customize Network Input Shape.

Customize the model input shape. With this parameter group enabled, the input image will be resized into the customized shape before training.

Returns:

const ClassificationInputShape & Customize Network Input Shape

ClassificationTrainingParameters &set_input_shape(ClassificationInputShape input_shape)#

Set Customize Network Input Shape with ClassificationInputShape value.

Customize the model input shape. With this parameter group enabled, the input image will be resized into the customized shape before training.

Parameters:

input_shape – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ClassificationTrainingParameters the reference of this object.

ClassificationInputShape &get_input_shape()#

Get mutable reference of Customize Network Input Shape.

Customize the model input shape. With this parameter group enabled, the input image will be resized into the customized shape before training.

Returns:

ClassificationTrainingParameters& the mutable reference of the group.

const TrainingMode &get_training_mode() const#

Get Training Mode.

Normal Train is the default mode for training a new model. Increment Train will retrain on previous model knowledge.

Returns:

const TrainingMode & Training Mode

ClassificationTrainingParameters &set_training_mode(TrainingMode training_mode)#

Set Training Mode with TrainingMode value.

Normal Train is the default mode for training a new model. Increment Train will retrain on previous model knowledge.

Parameters:

training_mode – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ClassificationTrainingParameters the reference of this object.

bool get_only_check() const#

Get Only Check.

Default is False. If set to True, the trainer will only check if it is possible to train in the given training mode without actually performing the training.

See also

set_only_check()

Returns:

bool Only Check

ClassificationTrainingParameters &set_only_check(bool only_check)#

Set Only Check with bool value.

Default is False. If set to True, the trainer will only check if it is possible to train in the given training mode without actually performing the training.

See also

get_only_check()

Parameters:

only_check – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ClassificationTrainingParameters the reference of this object.

const std::string &get_model_arch() const#

Get Model Architecture.

The Fast-Model is suitable for most scenarios, but the classification accuracy may be reduced in scenarios with more categories (more than 10 categories) and lower differentiation between categories, in which you can use the High-Precision-Model, although this will result in a slightly longer training and inference time.

See also

set_model_arch()

Returns:

const std::string & Model Architecture

ClassificationTrainingParameters &set_model_arch(std::string model_arch)#

Set Model Architecture with std::string value.

The Fast-Model is suitable for most scenarios, but the classification accuracy may be reduced in scenarios with more categories (more than 10 categories) and lower differentiation between categories, in which you can use the High-Precision-Model, although this will result in a slightly longer training and inference time.

See also

get_model_arch()

Parameters:

model_arch – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ClassificationTrainingParameters the reference of this object.

const DataAugmentation &get_augmentations() const#

Get Data Augmentation.

Data Augmentation Parameters

Returns:

const DataAugmentation & Data Augmentation

ClassificationTrainingParameters &set_augmentations(DataAugmentation augmentations)#

Set Data Augmentation with DataAugmentation value.

Data Augmentation Parameters

Parameters:

augmentations – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ClassificationTrainingParameters the reference of this object.

DataAugmentation &get_augmentations()#

Get mutable reference of Data Augmentation.

Data Augmentation Parameters

Returns:

ClassificationTrainingParameters& the mutable reference of the group.

bool get_with_contrastive() const#

Get With Contrastive Learning.

With this option enabled, The algorithm will try to improve the model performance by comparing the difference between sample and defective image. This mode is only applicable to the mixed images composed of a sample image and a defective image, it’s not applicable to single-image-samples or mixed images composed of different photos of the same defect.

Returns:

bool With Contrastive Learning

ClassificationTrainingParameters &set_with_contrastive(bool with_contrastive)#

Set With Contrastive Learning with bool value.

With this option enabled, The algorithm will try to improve the model performance by comparing the difference between sample and defective image. This mode is only applicable to the mixed images composed of a sample image and a defective image, it’s not applicable to single-image-samples or mixed images composed of different photos of the same defect.

Parameters:

with_contrastive – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ClassificationTrainingParameters the reference of this object.

EL Classification Tool Parameters#

class ELClassificationTrainingParameters : public visionflow::param::SchemableParameter#

ELClassificationTrainingParameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

int get_epoch() const#

Get Epochs.

Number of iterations to train. 1 Epoch means all selected images will be trained for 1 time.

See also

set_epoch()

Returns:

int Epochs

ELClassificationTrainingParameters &set_epoch(int epoch)#

Set Epochs with int value.

Number of iterations to train. 1 Epoch means all selected images will be trained for 1 time.

See also

get_epoch()

Parameters:

epoch – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ELClassificationTrainingParameters the reference of this object.

EL Unsuper Classification Tool Parameters#

class ELUnsuperClassificationTrainingParameters : public visionflow::param::SchemableParameter#

ELUnsuperClassificationTrainingParameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

int get_epoch() const#

Get Epochs.

Number of iterations to train. 1 Epoch means all selected images will be trained for 1 time.

See also

set_epoch()

Returns:

int Epochs

ELUnsuperClassificationTrainingParameters &set_epoch(int epoch)#

Set Epochs with int value.

Number of iterations to train. 1 Epoch means all selected images will be trained for 1 time.

See also

get_epoch()

Parameters:

epoch – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ELUnsuperClassificationTrainingParameters the reference of this object.

class ELUnsuperClassificationInferenceParameters : public visionflow::param::SchemableParameter#

ELUnsuperClassificationInferenceParameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

double get_ng_thresh() const#

Get NG Threshold.

Image will be set to ok when score < NG Threshold, and set to ng when score > NG Threshold

See also

set_ng_thresh()

Returns:

double NG Threshold

ELUnsuperClassificationInferenceParameters &set_ng_thresh(double ng_thresh)#

Set NG Threshold with double value.

Image will be set to ok when score < NG Threshold, and set to ng when score > NG Threshold

See also

get_ng_thresh()

Parameters:

ng_thresh – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ELUnsuperClassificationInferenceParameters the reference of this object.

Detection Tool Parameters#

class DetectionTrainingParameters : public visionflow::param::SchemableParameter#

DetectionTrainingParameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

int get_epoch() const#

Get Epochs.

Number of iterations to train. 1 Epoch means all selected images will be trained for 1 time.

See also

set_epoch()

Returns:

int Epochs

DetectionTrainingParameters &set_epoch(int epoch)#

Set Epochs with int value.

Number of iterations to train. 1 Epoch means all selected images will be trained for 1 time.

See also

get_epoch()

Parameters:

epoch – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

DetectionTrainingParameters the reference of this object.

int get_batch_size() const#

Get Training Batch Size.

The number of images involved in training in each iteration of network training. A suitable batch size can make full use of hardware and improve the convergence speed. Common values are 4, 8, and 16.

See also

set_batch_size()

Returns:

int Training Batch Size

DetectionTrainingParameters &set_batch_size(int batch_size)#

Set Training Batch Size with int value.

The number of images involved in training in each iteration of network training. A suitable batch size can make full use of hardware and improve the convergence speed. Common values are 4, 8, and 16.

See also

get_batch_size()

Parameters:

batch_size – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

DetectionTrainingParameters the reference of this object.

double get_lr_decay() const#

Get Learning Rate Decay.

The learning rate is multiplied by this value every epoch. The larger the value, the faster the learning rate decreases

See also

set_lr_decay()

Returns:

double Learning Rate Decay

DetectionTrainingParameters &set_lr_decay(double lr_decay)#

Set Learning Rate Decay with double value.

The learning rate is multiplied by this value every epoch. The larger the value, the faster the learning rate decreases

See also

get_lr_decay()

Parameters:

lr_decay – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

DetectionTrainingParameters the reference of this object.

const std::string &get_model_arch() const#

Get Model Architecture.

There are two different detection models, both of which support multi-class detection.

See also

set_model_arch()

Returns:

const std::string & Model Architecture

DetectionTrainingParameters &set_model_arch(std::string model_arch)#

Set Model Architecture with std::string value.

There are two different detection models, both of which support multi-class detection.

See also

get_model_arch()

Parameters:

model_arch – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

DetectionTrainingParameters the reference of this object.

int get_max_size() const#

Get Max Length.

To resize input images, the longer side is scaled down to match the maximum edge length while the shorter side is scaled proportionally. If the calculated maximum edge length is smaller than the given parameter, the algorithm will automatically adjust the maximum edge length. Setting a larger maximum edge length can improve detection accuracy, but it also requires longer training and inference time and higher GPU memory usage.

See also

set_max_size()

Returns:

int Max Length

DetectionTrainingParameters &set_max_size(int max_size)#

Set Max Length with int value.

To resize input images, the longer side is scaled down to match the maximum edge length while the shorter side is scaled proportionally. If the calculated maximum edge length is smaller than the given parameter, the algorithm will automatically adjust the maximum edge length. Setting a larger maximum edge length can improve detection accuracy, but it also requires longer training and inference time and higher GPU memory usage.

See also

get_max_size()

Parameters:

max_size – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

DetectionTrainingParameters the reference of this object.

const DetectionInputShape &get_input_shape() const#

Get Customize Network Input Shape.

Customize Network Input Shape

Returns:

const DetectionInputShape & Customize Network Input Shape

DetectionTrainingParameters &set_input_shape(DetectionInputShape input_shape)#

Set Customize Network Input Shape with DetectionInputShape value.

Customize Network Input Shape

Parameters:

input_shape – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

DetectionTrainingParameters the reference of this object.

DetectionInputShape &get_input_shape()#

Get mutable reference of Customize Network Input Shape.

Customize Network Input Shape

Returns:

DetectionTrainingParameters& the mutable reference of the group.

const DetectionTrainingStrategy &get_train_tricks() const#

Get train tricks.

Detection Strategy Parameters

Returns:

const DetectionTrainingStrategy & train tricks

DetectionTrainingParameters &set_train_tricks(DetectionTrainingStrategy train_tricks)#

Set train tricks with DetectionTrainingStrategy value.

Detection Strategy Parameters

Parameters:

train_tricks – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

DetectionTrainingParameters the reference of this object.

DetectionTrainingStrategy &get_train_tricks()#

Get mutable reference of train tricks.

Detection Strategy Parameters

Returns:

DetectionTrainingParameters& the mutable reference of the group.

const DataAugmentation &get_augmentations() const#

Get Data Augmentation.

Data Augmentation Parameters

Returns:

const DataAugmentation & Data Augmentation

DetectionTrainingParameters &set_augmentations(DataAugmentation augmentations)#

Set Data Augmentation with DataAugmentation value.

Data Augmentation Parameters

Parameters:

augmentations – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

DetectionTrainingParameters the reference of this object.

DataAugmentation &get_augmentations()#

Get mutable reference of Data Augmentation.

Data Augmentation Parameters

Returns:

DetectionTrainingParameters& the mutable reference of the group.

class DetectionInferParameters : public visionflow::param::SchemableParameter#

DetectionInferParameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

int get_max_target_num() const#

Get Maximum Target Count.

Retain only the top N targets with the highest confidence score

Returns:

int Maximum Target Count

DetectionInferParameters &set_max_target_num(int max_target_num)#

Set Maximum Target Count with int value.

Retain only the top N targets with the highest confidence score

Parameters:

max_target_num – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

DetectionInferParameters the reference of this object.

double get_target_overlap_ratio() const#

Get Target Overlap Ratio.

Some redundant boxes will be removed to ensure that the intersection ratio between boxes does not exceed this value. target_overlap_ratio = intersection_area / Union_area.

Returns:

double Target Overlap Ratio

DetectionInferParameters &set_target_overlap_ratio(double target_overlap_ratio)#

Set Target Overlap Ratio with double value.

Some redundant boxes will be removed to ensure that the intersection ratio between boxes does not exceed this value. target_overlap_ratio = intersection_area / Union_area.

Parameters:

target_overlap_ratio – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

DetectionInferParameters the reference of this object.

class DetectionTrainingStrategy : public visionflow::param::ISchemable#

DetectionTrainingStrategy Parameter class generated by jinja2 automatically.

Detection training tricks

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

bool get_auto_anchor() const#

Get Auto Anchor.

Auto anchor will automatically adjust the preset anchor size based on the image label

Returns:

bool Auto Anchor

DetectionTrainingStrategy &set_auto_anchor(bool auto_anchor)#

Set Auto Anchor with bool value.

Auto anchor will automatically adjust the preset anchor size based on the image label

Parameters:

auto_anchor – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

DetectionTrainingStrategy the reference of this object.

class DetectionInputShape : public visionflow::param::ISchemable#

DetectionInputShape Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

bool get_enable() const#

Get Enable.

Enable this parameter group.

See also

set_enable()

Returns:

bool Enable

DetectionInputShape &set_enable(bool enable)#

Set Enable with bool value.

Enable this parameter group.

See also

get_enable()

Parameters:

enable – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

DetectionInputShape the reference of this object.

int get_base_input_width() const#

Get Base Input Width.

Base Input Width

Returns:

int Base Input Width

DetectionInputShape &set_base_input_width(int base_input_width)#

Set Base Input Width with int value.

Base Input Width

Parameters:

base_input_width – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

DetectionInputShape the reference of this object.

int get_base_input_height() const#

Get Base Input Height.

Base Input Height

Returns:

int Base Input Height

DetectionInputShape &set_base_input_height(int base_input_height)#

Set Base Input Height with int value.

Base Input Height

Parameters:

base_input_height – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

DetectionInputShape the reference of this object.

GeometrySearch Tool Parameters#

class GeometrySearchTrainingParameters : public visionflow::param::SchemableParameter#

GeometrySearchTrainingParameters Parameter class generated by jinja2 automatically.

GeometrySearch Training Parameter Group

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

const SetGeometrySearchGranularityManually &get_granularity() const#

Get Manual Granularity Setting.

Enable manual setting of granularity; if not enabled, parameters will be auto-tuned. Feature chain granularity. Larger granularity will be faster precision.

Returns:

const SetGeometrySearchGranularityManually & Manual Granularity Setting

GeometrySearchTrainingParameters &set_granularity(SetGeometrySearchGranularityManually granularity)#

Set Manual Granularity Setting with SetGeometrySearchGranularityManually value.

Enable manual setting of granularity; if not enabled, parameters will be auto-tuned. Feature chain granularity. Larger granularity will be faster precision.

Parameters:

granularity – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

GeometrySearchTrainingParameters the reference of this object.

SetGeometrySearchGranularityManually &get_granularity()#

Get mutable reference of Manual Granularity Setting.

Enable manual setting of granularity; if not enabled, parameters will be auto-tuned. Feature chain granularity. Larger granularity will be faster precision.

Returns:

GeometrySearchTrainingParameters& the mutable reference of the group.

const SetGeometrySearchNoiseThreshManually &get_noise_thresh() const#

Get Manual Noise Threshold.

Enable manual setting of noise threshold; if not enabled, the threshold will be auto-tuned. Noise threshold of feature point gradient magnitude.

Returns:

const SetGeometrySearchNoiseThreshManually & Manual Noise Threshold

GeometrySearchTrainingParameters &set_noise_thresh(SetGeometrySearchNoiseThreshManually noise_thresh)#

Set Manual Noise Threshold with SetGeometrySearchNoiseThreshManually value.

Enable manual setting of noise threshold; if not enabled, the threshold will be auto-tuned. Noise threshold of feature point gradient magnitude.

Parameters:

noise_thresh – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

GeometrySearchTrainingParameters the reference of this object.

SetGeometrySearchNoiseThreshManually &get_noise_thresh()#

Get mutable reference of Manual Noise Threshold.

Enable manual setting of noise threshold; if not enabled, the threshold will be auto-tuned. Noise threshold of feature point gradient magnitude.

Returns:

GeometrySearchTrainingParameters& the mutable reference of the group.

const SetGeometrySearchFeatChainMagRelativeThreshManually &get_total_magnitude_relative_thresh() const#

Get Manual Magnitude Relative Threshold.

Enable manual setting of the total magnitude relative threshold; if not enabled, the threshold will be auto-tuned. Auto set relative total gradient magnitude threshold for feature chains.

Returns:

const SetGeometrySearchFeatChainMagRelativeThreshManually & Manual Magnitude Relative Threshold

GeometrySearchTrainingParameters &set_total_magnitude_relative_thresh(SetGeometrySearchFeatChainMagRelativeThreshManually total_magnitude_relative_thresh)#

Set Manual Magnitude Relative Threshold with SetGeometrySearchFeatChainMagRelativeThreshManually value.

Enable manual setting of the total magnitude relative threshold; if not enabled, the threshold will be auto-tuned. Auto set relative total gradient magnitude threshold for feature chains.

Parameters:

total_magnitude_relative_thresh – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

GeometrySearchTrainingParameters the reference of this object.

SetGeometrySearchFeatChainMagRelativeThreshManually &get_total_magnitude_relative_thresh()#

Get mutable reference of Manual Magnitude Relative Threshold.

Enable manual setting of the total magnitude relative threshold; if not enabled, the threshold will be auto-tuned. Auto set relative total gradient magnitude threshold for feature chains.

Returns:

GeometrySearchTrainingParameters& the mutable reference of the group.

const SetGeometrySearchDownSampleRatioManually &get_down_sample_ratio() const#

Get Manual Down Sample.

Enable manual setting of the down sample ratio; if not enabled, the ratio will be auto-tuned. Select image down sample ratio to speed up training and inference.

Returns:

const SetGeometrySearchDownSampleRatioManually & Manual Down Sample

GeometrySearchTrainingParameters &set_down_sample_ratio(SetGeometrySearchDownSampleRatioManually down_sample_ratio)#

Set Manual Down Sample with SetGeometrySearchDownSampleRatioManually value.

Enable manual setting of the down sample ratio; if not enabled, the ratio will be auto-tuned. Select image down sample ratio to speed up training and inference.

Parameters:

down_sample_ratio – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

GeometrySearchTrainingParameters the reference of this object.

SetGeometrySearchDownSampleRatioManually &get_down_sample_ratio()#

Get mutable reference of Manual Down Sample.

Enable manual setting of the down sample ratio; if not enabled, the ratio will be auto-tuned. Select image down sample ratio to speed up training and inference.

Returns:

GeometrySearchTrainingParameters& the mutable reference of the group.

class GeometrySearchInferParameters : public visionflow::param::SchemableParameter#

GeometrySearchInferParameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

double get_threshold() const#

Get Confidence Threshold.

Greater than this threshold will be determined as a target.

See also

set_threshold()

Returns:

double Confidence Threshold

GeometrySearchInferParameters &set_threshold(double threshold)#

Set Confidence Threshold with double value.

Greater than this threshold will be determined as a target.

See also

get_threshold()

Parameters:

threshold – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

GeometrySearchInferParameters the reference of this object.

int get_max_match_results_num() const#

Get Max Match Results Num Per View.

The maximum number of searching results per view. When the value is 0, the maximum number of searching results is not limited.

Returns:

int Max Match Results Num Per View

GeometrySearchInferParameters &set_max_match_results_num(int max_match_results_num)#

Set Max Match Results Num Per View with int value.

The maximum number of searching results per view. When the value is 0, the maximum number of searching results is not limited.

Parameters:

max_match_results_num – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

GeometrySearchInferParameters the reference of this object.

const std::vector<double> &get_rotate_range() const#

Get Rotate Range (Degree).

The target rotate range

Returns:

const std::vector<double> & Rotate Range (Degree)

GeometrySearchInferParameters &set_rotate_range(std::vector<double> rotate_range)#

Set Rotate Range (Degree) with std::vector<double> value.

The target rotate range

Parameters:

rotate_range – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

GeometrySearchInferParameters the reference of this object.

bool rotate_range_contains(double value) const#

Check if the Rotate Range (Degree) contains the value.

Returns:

bool true if the Rotate Range (Degree) contains the value, otherwise false.

double get_rotate_range_left() const#

Get left point value of Rotate Range (Degree).

Returns:

const std::vector<double> & left point value of Rotate Range (Degree)

double get_rotate_range_right() const#

Get the right point value of Rotate Range (Degree).

Returns:

const std::vector<double> & the right point value of Rotate Range (Degree)

GeometrySearchInferParameters &set_rotate_range_left(double rotate_range_left)#

Set left point value of Rotate Range (Degree) with std::vector<double> value.

The target rotate range

Parameters:

rotate_range_left – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

GeometrySearchInferParameters the reference of this object.

GeometrySearchInferParameters &set_rotate_range_right(double rotate_range_right)#

Set the right point value of Rotate Range (Degree) with std::vector<double> value.

The target rotate range

Parameters:

rotate_range_right – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

GeometrySearchInferParameters the reference of this object.

const std::vector<double> &get_scale_range() const#

Get Scale Range.

The target rotate range

Returns:

const std::vector<double> & Scale Range

GeometrySearchInferParameters &set_scale_range(std::vector<double> scale_range)#

Set Scale Range with std::vector<double> value.

The target rotate range

Parameters:

scale_range – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

GeometrySearchInferParameters the reference of this object.

bool scale_range_contains(double value) const#

Check if the Scale Range contains the value.

Returns:

bool true if the Scale Range contains the value, otherwise false.

double get_scale_range_left() const#

Get left point value of Scale Range.

Returns:

const std::vector<double> & left point value of Scale Range

double get_scale_range_right() const#

Get the right point value of Scale Range.

Returns:

const std::vector<double> & the right point value of Scale Range

GeometrySearchInferParameters &set_scale_range_left(double scale_range_left)#

Set left point value of Scale Range with std::vector<double> value.

The target rotate range

Parameters:

scale_range_left – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

GeometrySearchInferParameters the reference of this object.

GeometrySearchInferParameters &set_scale_range_right(double scale_range_right)#

Set the right point value of Scale Range with std::vector<double> value.

The target rotate range

Parameters:

scale_range_right – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

GeometrySearchInferParameters the reference of this object.

const GeometrySearchSearchMode &get_search_mode() const#

Get Search Mode.

Search Mode

Returns:

const GeometrySearchSearchMode & Search Mode

GeometrySearchInferParameters &set_search_mode(GeometrySearchSearchMode search_mode)#

Set Search Mode with GeometrySearchSearchMode value.

Search Mode

Parameters:

search_mode – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

GeometrySearchInferParameters the reference of this object.

bool get_ignore_polarity() const#

Get Ignore Polarity.

Ignore polarity will take feature points’ gradient direction with 180 degree difference as same direction.

Returns:

bool Ignore Polarity

GeometrySearchInferParameters &set_ignore_polarity(bool ignore_polarity)#

Set Ignore Polarity with bool value.

Ignore polarity will take feature points’ gradient direction with 180 degree difference as same direction.

Parameters:

ignore_polarity – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

GeometrySearchInferParameters the reference of this object.

int get_time_limit() const#

Get Time Limit.

Tool will quit when it’s execution time exceed given time (in ms). 0 indicates no time limit.

See also

set_time_limit()

Returns:

int Time Limit

GeometrySearchInferParameters &set_time_limit(int time_limit)#

Set Time Limit with int value.

Tool will quit when it’s execution time exceed given time (in ms). 0 indicates no time limit.

See also

get_time_limit()

Parameters:

time_limit – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

GeometrySearchInferParameters the reference of this object.

const GeometrySearchDuplicate &get_overlap_ration() const#

Get Target Overlap.

Parameters to suppress near targets.

Returns:

const GeometrySearchDuplicate & Target Overlap

GeometrySearchInferParameters &set_overlap_ration(GeometrySearchDuplicate overlap_ration)#

Set Target Overlap with GeometrySearchDuplicate value.

Parameters to suppress near targets.

Parameters:

overlap_ration – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

GeometrySearchInferParameters the reference of this object.

GeometrySearchDuplicate &get_overlap_ration()#

Get mutable reference of Target Overlap.

Parameters to suppress near targets.

Returns:

GeometrySearchInferParameters& the mutable reference of the group.

CameraCalibration Tool Parameters#

class CameraCalibrationTrainingParameters : public visionflow::param::IParameter#

Camera calibration training parameters should be set before initialization.

Public Functions

CameraCalibrationTrainingParameters &set_reference_idx(size_t reference_idx)#

The index of reference view in the input image view sequence. The algorithm establishes the coordinate system according to the reference image. The camera pose and calibration board position of the reference image should be consistent with the camera pose and target position in the inference image. A good reference image can improve the correction accuracy.

Parameters:

reference_idx – Reference image index.

Returns:

CameraCalibrationTrainingParameters& the reference of this object.

size_t get_reference_idx() const#

CameraCalibrationTrainingParameters &set_freedom_degree_type(FreedomDegreeType freedom_degree_type)#

Select nonlinear camera or the calibrate type of linear camera, which including TranslationRotationScale transformation, Affine transformation and Perspective transformation.

Parameters:

freedom_degree_type – Freedom degree type.

Returns:

CameraCalibrationTrainingParameters& the reference of this object.

FreedomDegreeType get_freedom_degree_type() const#

CameraCalibrationTrainingParameters &set_calibrate_board_type(CalibrationBoardType calibrate_board_type)#

Set calibrate board type.

Parameters:

calibrate_board_type – Calibrate board type.

Returns:

CameraCalibrationTrainingParameters& the reference of this object.

CalibrationBoardType get_calibrate_board_type() const#

CameraCalibrationTrainingParameters &set_grid_distance(double grid_distance)#

Calibrate board feature points grid distance.

Parameters:

grid_distance – Grid distance.

Returns:

CameraCalibrationTrainingParameters& the reference of this object.

double get_grid_distance() const#

CameraCalibrationTrainingParameters &set_grid_size(geometry::Size2i grid_size)#

Only valid when calibrate board type is AQBoardRect.The width represents the number of grids in the X direction of the calibrate board, and height is the number of grids in Y direction.

Parameters:

grid_size – rows and cols of grid.

Returns:

CameraCalibrationTrainingParameters& the reference of this object.

const geometry::Size2i &get_grid_size() const#

See also

set_grid_size()

CameraCalibrationTrainingParameters &set_scale(double scale)#

Resize the resulting image by the scale.The default is 1.0.

Parameters:

scale – Zoom scale equivalent to the pixel corresponding to the corrected image.

Returns:

CameraCalibrationTrainingParameters& the reference of this object.

double get_scale() const#

See also

set_scale()

CameraCalibrationTrainingParameters &set_image_set(std::vector<visionflow::img::Image> image_set, size_t reference_idx)#

The training image set.

Parameters:
  • image_set – The training image set

  • reference_idx – Image sequence number, the sequence number of the image set is incremented from 0. One image in the training image set is selected as the main reference image.

Returns:

CameraCalibrationTrainingParameters& the reference of this object.

const std::vector<visionflow::img::Image> &get_image_set() const#

See also

set_image_set()

CameraCalibrationTrainingParameters &set_mask_set(std::vector<geometry::MultiPolygon2f> mask_set)#

The mask set to the training image set.

Parameters:

mask_set – The training mask set

Returns:

CameraCalibrationTrainingParameters& the reference of this object.

const std::vector<geometry::MultiPolygon2f> &get_mask_set() const#

See also

set_mask_set()

class CameraCalibrationInferParameters : public visionflow::param::SchemableParameter#

CameraCalibrationInferParameters Parameter class generated by jinja2 automatically.

Camera calibrate Infer Parameter Group

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

const std::vector<int> &get_fill_color() const#

Get Image Fill Color.

Image Fill Color values ordered same as image channels.

See also

set_fill_color()

Returns:

const std::vector<int> & Image Fill Color

CameraCalibrationInferParameters &set_fill_color(std::vector<int> fill_color)#

Set Image Fill Color with std::vector<int> value.

Image Fill Color values ordered same as image channels.

See also

get_fill_color()

Parameters:

fill_color – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

CameraCalibrationInferParameters the reference of this object.

int get_fill_color(size_t index) const#

Get value in Image Fill Color with index.

Warning

The index must be less than get_fill_color_size(). otherwise, the behavior is undefined and will cause segmentation fault.

Returns:

int value in Image Fill Color at index.

size_t get_fill_color_size() const#

Get the size of Image Fill Color.

Returns:

size_t the size of Image Fill Color

View Transformer Parameters#

enum visionflow::param::ViewTransMode#

Values:

enumerator kByPixel = 0#
enumerator kByRatio = 1#
class ViewFilterParameters : public visionflow::param::SchemableParameter#

ViewFilterParameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

bool get_with_ok_view() const#

Get With OK View.

Treating views with no detection results as detection targets

Returns:

bool With OK View

ViewFilterParameters &set_with_ok_view(bool with_ok_view)#

Set With OK View with bool value.

Treating views with no detection results as detection targets

Parameters:

with_ok_view – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ViewFilterParameters the reference of this object.

const std::map<std::string, SingleClassPolygonsFilterParameters> &get_keep_classes() const#

Get Keep Classes.

Polygon thresholds (area, side-length,etc.) named with the label classes according to which to filter the polygons.

Returns:

const std::map<std::string, SingleClassPolygonsFilterParameters> & Keep Classes

ViewFilterParameters &set_keep_classes(std::map<std::string, SingleClassPolygonsFilterParameters> keep_classes)#

Set Keep Classes with std::map<std::string, SingleClassPolygonsFilterParameters> value.

Polygon thresholds (area, side-length,etc.) named with the label classes according to which to filter the polygons.

Parameters:

keep_classes – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ViewFilterParameters the reference of this object.

const SingleClassPolygonsFilterParameters &get_keep_classes(const std::string &key) const#

Get value in Keep Classes with key.

Warning

The key must be exist in Keep Classes. otherwise, the behavior is undefined and will cause segmentation fault.

Returns:

const std::map<std::string, SingleClassPolygonsFilterParameters> & value in Keep Classes at key.

ViewFilterParameters &set_keep_classes(const std::string &key, SingleClassPolygonsFilterParameters value)#

Set value in Keep Classes with key.

Parameters:
  • key – the key to set.

  • value – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ViewFilterParameters the reference of this object.

bool keep_classes_contains(const std::string &key) const#

Check if the key is exist in Keep Classes.

Returns:

bool true if the key is exist in Keep Classes, otherwise false.

size_t get_keep_classes_size() const#

Get the size of Keep Classes.

Returns:

size_t the size of Keep Classes

SingleClassPolygonsFilterParameters &get_keep_classes(const std::string &key)#

Get mutable reference of value in Keep Classes with key. A new key and default value will be created if the key does not exist.

Returns:

SingleClassPolygonsFilterParameters& the mutable reference of value in Keep Classes at key.

class ViewTransAutoMask#

ViewTransAutoMask Parameter class generated by jinja2 automatically.

Public Functions

bool get_enable() const#

Get Anable View Auto Mask.

Enable this option to use the detection result from the previous module as a mask.

See also

set_enable()

Returns:

bool Anable View Auto Mask

ViewTransAutoMask &set_enable(bool enable)#

Set Anable View Auto Mask with bool value.

Enable this option to use the detection result from the previous module as a mask.

See also

get_enable()

Parameters:

enable – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ViewTransAutoMask& the reference of this object.

int get_dilate_pixel() const#

Get Dilate Pixel.

Dilate the detection result from the previous module before mask. A negative value indicate erosion operation.

Returns:

int Dilate Pixel

ViewTransAutoMask &set_dilate_pixel(int dilate_pixel)#

Set Dilate Pixel with int value.

Dilate the detection result from the previous module before mask. A negative value indicate erosion operation.

Parameters:

dilate_pixel – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ViewTransAutoMask& the reference of this object.

bool get_reverse_mask() const#

Get Reverse Mask.

Inverse masking of areas in the view that have no detection results from the previous module. Note that this option works after the dilate option if it’s not zero.

Returns:

bool Reverse Mask

ViewTransAutoMask &set_reverse_mask(bool reverse_mask)#

Set Reverse Mask with bool value.

Inverse masking of areas in the view that have no detection results from the previous module. Note that this option works after the dilate option if it’s not zero.

Parameters:

reverse_mask – the value to set.

Returns:

ViewTransAutoMask& the reference of this object.

class ViewTransformParameter#

ViewTransformParameter Parameter class generated by jinja2 automatically.

Public Functions

ViewTransMode get_mode() const#

Get Offset Mode.

Offset by a fixed number of pixels or by a percentage depending on the size of the defect.

See also

set_mode()

Returns:

ViewTransMode View Mode

ViewTransformParameter &set_mode(ViewTransMode mode)#

Set the view transform mode as ByPixel or ByRatio.

Generate view by a fixed number of pixels or by a percentage depending on the size of the defect.

See also

get_mode()

Parameters:

mode – the The View mode.

Returns:

ViewTransformParameter& the reference of this object.

const geometry::Vector2f &get_offset() const#

Get Offset Vector.

See also

set_offset()

Returns:

The offset vector, Its practical use is determined by the VeiwTransOffsetMode in get_mode()

ViewTransformParameter &set_offset(const geometry::Vector2f &offset)#

Set View offset vector With the centre of the original test result as the reference coordinate system.

See also

get_offset()

Parameters:

offset – the offset value to set.

Returns:

ViewTransformParameter& the reference of this object.

const geometry::Size2f &get_window_size() const#

Get Window Size.

The view window size, The meaning of the options is determined by the Window Size Mode

The View window size mode. “DynamicPixel” mode means get the window size from the detection result from previous module and you can scale it with a fixed number of pixels; “DynamicRatio” mode means get the window size from the detection result from previous module and you can scale it by ratio; “FixedWindow” means set the view windows to a fixed size regardless of the size of the detection result from previous module.

Returns:

Window Size or Window expand size base on the detection result.

ViewTransformParameter &set_window_size(const geometry::Size2f &window_size)#

Set Window size.

The view window size, The meaning of the options is determined by the view mode.

Parameters:

window_size – the value to set.

Returns:

ViewTransformParameter& the reference of this object.

bool get_fixed_window_size() const#

Get If the view windows size is fixed.

Returns:

bool

ViewTransformParameter &set_fixed_window_size(bool fixed_window_size)#

Set this option as true to fix the view window size.

Parameters:

fixed_window_size

Returns:

ViewTransformParameter&

geometry::Radian get_rotate_angle() const#

Get the view rotate angle.

Returns:

geometry::Radian the view rotate angle base on the reference coordinate system.

ViewTransformParameter &set_rotate_angle(const geometry::Radian &angle)#

Set the view rotate angle.

Parameters:

angle – rotate angle.

Returns:

ViewTransformParameter& this parameter object.

const ViewTransAutoMask &get_auto_mask() const#

Get Auto View Mask.

Auto view mask parameters

See also

set_auto_mask()

Returns:

const ViewTransAutoMask & Auto View Mask

ViewTransformParameter &set_auto_mask(const ViewTransAutoMask &auto_mask)#

Set Auto View Mask with ViewTransAutoMask value.

Auto view mask parameters

See also

get_auto_mask()

Parameters:

auto_mask – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ViewTransformParameter& the reference of this object.

ViewTransAutoMask &get_auto_mask()#

Get mutable reference of Auto View Mask.

Auto view mask parameters

Returns:

ViewTransformParameter& the mutable reference of the group.

const geometry::MultiPolygon2f &get_manual_mask() const#

Get the manual mask object.

Returns:

const geometry::MultiPolygon2f& Get the manual view mask.

ViewTransformParameter &set_manual_mask(const geometry::MultiPolygon2f &manual_mask)#

Set the manual mask object. The x-y coordinate value of the points in MultiPolygon2f should be established in the coordinate system with the upper-left corner point of the view after transforming based on the defact region and its angle.

class ViewTransformParameterList : public visionflow::param::IParameter#

Public Functions

size_t size() const#

View transform parameter size.

Returns:

size_t

std::vector<std::string> keys() const#

All view transform parameters’ names.

Returns:

std::vector<std::string> parameter names.

const ViewTransformParameter &at(const std::string &view_param_name) const#

Get view specified by the name.

Parameters:

view_param_name

Returns:

ViewTransformParameter const&

bool contains(const std::string &view_param_name) const#

Check if the list contains parameter specified by the name.

Parameters:

view_param_name

Returns:

bool

void erase(const std::string &view_param_name)#

remove parameter from the list.

std::string add(const ViewTransformParameter &view_param)#

Add a new ViewTransformParameter instance into this list. An new id will be generated for the parameter added.

Parameters:

view_param – The parameter to be added into this list.

Returns:

std::string The parameter id generated by the list.

void update(const std::string &view_param_name, const ViewTransformParameter &view_param)#

Update view parameter specified by view_param_name with the new parameter. If parameter specified by view_param_name does not exist, the new ViewTransformParameter instance will be added into this list with key view_param_name.

Parameters:
  • view_param_name – The key of the parameter to be updated. Note that the param name will be set as the region name of the ViewTransformer’s output views.

  • view_param – The new parameter to be updated.

bool get_enable_script() const#

Whether to use python script or not.

ViewTransformParameterList &set_enable_script(bool enable_script)#

Set whether to enable python scripts.

Parameters:

enable_script – Enable option

Returns:

ViewTransformParameterList&

const std::string &get_script() const#

Get the python script string.

See also

set_script()

Returns:

The python script.

ViewTransformParameterList &set_script(const std::string &manual_script)#

Set the python script with std::string value. We provide a default python script to help you to implement your own script:

See also

get_script()

Note

The python script must contain a function named “view_transform” which parameter represented input and output of opers::ViewTransformer with type param::ViewTransformParameterList, props::IRegionList, props::RawImageInfo and props::ViewList respectively. If script enabled, the opers::ViewTransformer will execute the “view_transform” function.

Parameters:

manual_script – The python script string to be set.

Returns:

ViewTransformParameterList&

const ObjectTypeValue &get_user_vars(const std::string &key) const#

Get value in User Defined Variables with key.

Warning

The key must be exist in User Defined Variables. otherwise, the behavior is undefined and will cause segmentation fault.

Returns:

const std::map<std::string, ObjectTypeValue> & value in User Defined Variables at key.

ObjectTypeValue &get_user_vars(const std::string &key)#

Get mutable reference of value in User Defined Variables with key. A new key and default value will be created if the key does not exist.

Returns:

ObjectTypeValue& the mutable reference of value in User Defined Variables at key.

ViewTransformParameterList &set_user_vars(const std::string &key, const ObjectTypeValue &value)#

Set value in User Defined Variables with key.

Parameters:
  • key – the key to set.

  • value – the type-value pair to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

IntegrationClassifyParameter& the reference of this object.

bool user_vars_contains(const std::string &key) const#

Check if the key is exist in User Defined Variables.

Returns:

bool true if the key is exist in User Defined Variables, otherwise false.

size_t get_user_vars_size() const#

Get the size of User Defined Variables.

Returns:

size_t the size of User Defined Variables

const std::map<std::string, ObjectTypeValue> &get_user_vars() const#

Get User Defined Variables.

The class name string to be used if none of the conditions are met.

See also

set_user_vars()

Returns:

const std::map<std::string, ObjectTypeValue> & User Defined Variables

ViewTransformParameterList &set_user_vars(const std::map<std::string, ObjectTypeValue> &user_vars)#

Set User Defined Variables with std::map<std::string, ObjectTypeValue> value.

The class name string to be used if none of the conditions are met.

See also

get_user_vars()

Parameters:

user_vars – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

IntegrationClassifyParameter& the reference of this object.

Public Static Functions

static std::string GetDefaultScript()#

A default python script to help you to implement your own script:

import visionflow as vf
from visionflow import geometry as geo
from visionflow import param, props

def view_transform(
    params: vf.param.ViewTransformParameterList,
    polys: vf.props.IRegionList,
    img_info: vf.props.RawImageInfo
) -> vf.props.ViewList:

    view_list = vf.opers.view_transform(params, polys, img_info)

    return view_list

Note

The python script must contain a function named “view_transform” which parameter represented input and output of opers::ViewTransformer with type param::ViewTransformParameterList, props::IRegionList, props::RawImageInfo and props::ViewList respectively. If script enabled, the opers::ViewTransformer will execute the “view_transform” function.

Returns:

std::string The default python script.

Sample Recommendation Parameters:#

class SampleRecommendationParameter : public visionflow::param::SchemableParameter#

SampleRecommendationParameter Parameter class generated by jinja2 automatically.

Parameter for the sample recommendation algorithm

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

double get_recommend_budget() const#

Get Recommend Budget.

The ratio of views to recommend

Returns:

double Recommend Budget

SampleRecommendationParameter &set_recommend_budget(double recommend_budget)#

Set Recommend Budget with double value.

The ratio of views to recommend

Parameters:

recommend_budget – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

SampleRecommendationParameter the reference of this object.

const SampleRecommendRange &get_recommend_range() const#

Get Sample Recommend Range.

Allows the user to pick from a selected range, currently supportedby the three type: UnTrainedSet, TestSet, and UnKnown.

Returns:

const SampleRecommendRange & Sample Recommend Range

SampleRecommendationParameter &set_recommend_range(SampleRecommendRange recommend_range)#

Set Sample Recommend Range with SampleRecommendRange value.

Allows the user to pick from a selected range, currently supportedby the three type: UnTrainedSet, TestSet, and UnKnown.

Parameters:

recommend_range – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

SampleRecommendationParameter the reference of this object.

class PropertyObjectId : public visionflow::param::ISchemable#

PropertyObjectId Parameter class generated by jinja2 automatically.

Parameter group for a object IDs in a property.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

int get_property_id() const#

Get Property ID.

ID of the property

Returns:

int Property ID

PropertyObjectId &set_property_id(int property_id)#

Set Property ID with int value.

ID of the property

Parameters:

property_id – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

PropertyObjectId the reference of this object.

const std::vector<std::string> &get_object_ids() const#

Get Object IDs.

IDs of the objects

See also

set_object_ids()

Returns:

const std::vector<std::string> & Object IDs

PropertyObjectId &set_object_ids(std::vector<std::string> object_ids)#

Set Object IDs with std::vector<std::string> value.

IDs of the objects

See also

get_object_ids()

Parameters:

object_ids – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

PropertyObjectId the reference of this object.

const std::string &get_object_ids(size_t index) const#

Get value in Object IDs with index.

Warning

The index must be less than get_object_ids_size(). otherwise, the behavior is undefined and will cause segmentation fault.

Returns:

const std::string & value in Object IDs at index.

size_t get_object_ids_size() const#

Get the size of Object IDs.

Returns:

size_t the size of Object IDs

class PropertyObjectIdSet : public visionflow::param::SchemableParameter#

PropertyObjectIdSet Parameter class generated by jinja2 automatically.

Parameter group for a set of property object IDs.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

const std::vector<PropertyObjectId> &get_object_id_sets() const#

Get Property Object ID Sets.

Sets of object IDs in properties

Returns:

const std::vector<PropertyObjectId> & Property Object ID Sets

PropertyObjectIdSet &set_object_id_sets(std::vector<PropertyObjectId> object_id_sets)#

Set Property Object ID Sets with std::vector<PropertyObjectId> value.

Sets of object IDs in properties

Parameters:

object_id_sets – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

PropertyObjectIdSet the reference of this object.

const PropertyObjectId &get_object_id_sets(size_t index) const#

Get value in Property Object ID Sets with index.

Warning

The index must be less than get_object_id_sets_size(). otherwise, the behavior is undefined and will cause segmentation fault.

Returns:

const PropertyObjectId & value in Property Object ID Sets at index.

size_t get_object_id_sets_size() const#

Get the size of Property Object ID Sets.

Returns:

size_t the size of Property Object ID Sets

PropertyObjectId &get_object_id_sets(size_t index)#

Get mutable reference of value in Property Object ID Sets with index.

Warning

The index must be less than get_object_id_sets_size(). otherwise, the behavior is undefined and will cause segmentation fault.

Returns:

PropertyObjectId& the mutable reference of value in Property Object ID Sets at index.

enum visionflow::param::SampleRecommendRange#

Values:

enumerator kUnTrainedSet = 0#
enumerator kTestSet = 1#
enumerator kUnKnown = 2#

Training Set Recommend Parameters:#

enum visionflow::param::TrainingSetRecommendType#

Values:

enumerator kViewBase = 0#
class TrainingSetRecommendParameter : public visionflow::param::SchemableParameter#

TrainingSetRecommendParameter Parameter class generated by jinja2 automatically.

Parameter for the auto class balance

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

int get_num_to_select() const#

Get Select Number.

The number of views to select

Returns:

int Select Number

TrainingSetRecommendParameter &set_num_to_select(int num_to_select)#

Set Select Number with int value.

The number of views to select

Parameters:

num_to_select – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

TrainingSetRecommendParameter the reference of this object.

const TrainingSetRecommendType &get_algorithm_type() const#

Get Algorithm type.

The Algorithm type to be used training set recommend, currently supports three algorithms: ViewBase, PixelBase, and RegionBase.

Returns:

const TrainingSetRecommendType & Algorithm type

TrainingSetRecommendParameter &set_algorithm_type(TrainingSetRecommendType algorithm_type)#

Set Algorithm type with TrainingSetRecommendType value.

The Algorithm type to be used training set recommend, currently supports three algorithms: ViewBase, PixelBase, and RegionBase.

Parameters:

algorithm_type – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

TrainingSetRecommendParameter the reference of this object.

Integration Tool Parameters:#

class IntegrationClassifyParameter : public visionflow::param::SchemableParameter#

IntegrationClassifyParameter Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

const std::string &get_script() const#

 @brief Get Category Script.

 The list of classes and conditions to be evaluated. Note that the function `integration_classifier` must exist and return a Tuple[str, Dict[str, str]] value. Dict[str, str] can be empty.
And we provide a sample script to help you to implement your own script:
import visionflow as vf
from visionflow import geometry as geo
from typing import Dict, Tuple

def region_covered_by(region, ring):
    output = geo.MultiPolygon2f()
    geo.difference(ring, region.polygon(), output)
    return len(output) == 0

classifier_condition = {
    "Ok": lambda sample: any(
        0 < region.area() < 10000
        and 0 < region.polygon().bounding_box().long_side() < 30000
        and 0 < region.polygon().bounding_box().short_side() < 30000
        and -45 < region.angle().degree() < 45
        and 0.1 < region.score() < 1.0
        and region_covered_by(region, geo.Ring2f([geo.Point2f(0,0), geo.Point2f(0,100), geo.Point2f(100,100), geo.Point2f(100,0)]))
        for id, region in sample["Segmentation/pred"]
    ),
    "Car": lambda sample: any(
        0 < region.area() < 10000
        and 0 < region.polygon().bounding_box().long_side() < 30000
        and 0 < region.polygon().bounding_box().short_side() < 30000
        and -45 < region.angle().degree() < 45
        and 0.1 < region.score() < 1.0
        and region_covered_by(region, geo.Ring2f([geo.Point2f(0,0), geo.Point2f(0,200), geo.Point2f(200,200), geo.Point2f(200,0)]))
        for id, region in sample["Segmentation/pred"]
    )
    or all(
        0 < region.area() < 10000
        and 0 < region.polygon().bounding_box().long_side() < 30000
        and 0 < region.polygon().bounding_box().short_side() < 30000
        and -45 < region.angle().degree() < 45
        and 0.1 < region.score() < 1.0
        and region_covered_by(region, geo.Ring2f([geo.Point2f(0,0), geo.Point2f(0,200), geo.Point2f(200,200), geo.Point2f(200,0)]))
        for id, region in sample["Classification/pred"]
    ),
}


# 综合判定节点的入口函数,不要修改这个函数的名称、参数和返回值类型
def integration_classifier(sample: vf.ISample) -> Tuple[str, Dict[str, str]] :

    # 填入需输出的扩展数据
    extension_data: Dict[str, str] = {}
    extension_data["num_of_cls_pred_region"] = str(sample.get(vf.ToolNodeId("Classification", vf.Classification.pred)).size())
    extension_data["num_of_seg_pred_region"] = str(sample.get(vf.ToolNodeId("Segmentation", vf.Segmentation.pred)).size())

    for category, condition in classifier_condition.items():
        if condition(sample):
            return category, extension_data
    return "Other", extension_data

See also

set_script()

Returns:

const std::string & Category Script

IntegrationClassifyParameter &set_script(std::string script)#

 @brief Set Category Script with std::string value.

 The list of classes and conditions to be evaluated. Note that the function `integration_classifier` must exist and return a Tuple[str, Dict[str, str]] value. Dict[str, str] can be empty.
And we provide a sample script to help you to implement your own script:
import visionflow as vf
from visionflow import geometry as geo
from typing import Dict, Tuple

def region_covered_by(region, ring):
    output = geo.MultiPolygon2f()
    geo.difference(ring, region.polygon(), output)
    return len(output) == 0

classifier_condition = {
    "Ok": lambda sample: any(
        0 < region.area() < 10000
        and 0 < region.polygon().bounding_box().long_side() < 30000
        and 0 < region.polygon().bounding_box().short_side() < 30000
        and -45 < region.angle().degree() < 45
        and 0.1 < region.score() < 1.0
        and region_covered_by(region, geo.Ring2f([geo.Point2f(0,0), geo.Point2f(0,100), geo.Point2f(100,100), geo.Point2f(100,0)]))
        for id, region in sample["Segmentation/pred"]
    ),
    "Car": lambda sample: any(
        0 < region.area() < 10000
        and 0 < region.polygon().bounding_box().long_side() < 30000
        and 0 < region.polygon().bounding_box().short_side() < 30000
        and -45 < region.angle().degree() < 45
        and 0.1 < region.score() < 1.0
        and region_covered_by(region, geo.Ring2f([geo.Point2f(0,0), geo.Point2f(0,200), geo.Point2f(200,200), geo.Point2f(200,0)]))
        for id, region in sample["Segmentation/pred"]
    )
    or all(
        0 < region.area() < 10000
        and 0 < region.polygon().bounding_box().long_side() < 30000
        and 0 < region.polygon().bounding_box().short_side() < 30000
        and -45 < region.angle().degree() < 45
        and 0.1 < region.score() < 1.0
        and region_covered_by(region, geo.Ring2f([geo.Point2f(0,0), geo.Point2f(0,200), geo.Point2f(200,200), geo.Point2f(200,0)]))
        for id, region in sample["Classification/pred"]
    ),
}


# 综合判定节点的入口函数,不要修改这个函数的名称、参数和返回值类型
def integration_classifier(sample: vf.ISample) -> Tuple[str, Dict[str, str]] :

    # 填入需输出的扩展数据
    extension_data: Dict[str, str] = {}
    extension_data["num_of_cls_pred_region"] = str(sample.get(vf.ToolNodeId("Classification", vf.Classification.pred)).size())
    extension_data["num_of_seg_pred_region"] = str(sample.get(vf.ToolNodeId("Segmentation", vf.Segmentation.pred)).size())

    for category, condition in classifier_condition.items():
        if condition(sample):
            return category, extension_data
    return "Other", extension_data

See also

get_script()

Parameters:

script – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

IntegrationClassifyParameter the reference of this object.

const std::string &get_unmatched_name() const#

Get Unmatched Class Name.

The class name string to be used if none of the conditions are met.

Returns:

const std::string & Unmatched Class Name

IntegrationClassifyParameter &set_unmatched_name(std::string unmatched_name)#

Set Unmatched Class Name with std::string value.

The class name string to be used if none of the conditions are met.

Parameters:

unmatched_name – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

IntegrationClassifyParameter the reference of this object.

const std::map<std::string, TypeValuePair> &get_user_vars() const#

Get User Defined Variables.

The key of the map is the name of the python object and the value of the map is a pair of string which means type-value of the python object.

See also

set_user_vars()

Returns:

const std::map<std::string, TypeValuePair> & User Defined Variables

IntegrationClassifyParameter &set_user_vars(std::map<std::string, TypeValuePair> user_vars)#

Set User Defined Variables with std::map<std::string, TypeValuePair> value.

The key of the map is the name of the python object and the value of the map is a pair of string which means type-value of the python object.

See also

get_user_vars()

Parameters:

user_vars – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

IntegrationClassifyParameter the reference of this object.

const TypeValuePair &get_user_vars(const std::string &key) const#

Get value in User Defined Variables with key.

Warning

The key must be exist in User Defined Variables. otherwise, the behavior is undefined and will cause segmentation fault.

Returns:

const std::map<std::string, TypeValuePair> & value in User Defined Variables at key.

IntegrationClassifyParameter &set_user_vars(const std::string &key, TypeValuePair value)#

Set value in User Defined Variables with key.

Parameters:
  • key – the key to set.

  • value – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

IntegrationClassifyParameter the reference of this object.

bool user_vars_contains(const std::string &key) const#

Check if the key is exist in User Defined Variables.

Returns:

bool true if the key is exist in User Defined Variables, otherwise false.

size_t get_user_vars_size() const#

Get the size of User Defined Variables.

Returns:

size_t the size of User Defined Variables

TypeValuePair &get_user_vars(const std::string &key)#

Get mutable reference of value in User Defined Variables with key. A new key and default value will be created if the key does not exist.

Returns:

TypeValuePair& the mutable reference of value in User Defined Variables at key.

RegionCalculation Tool Parameters:#

class RegionCalculationParameter : public visionflow::param::SchemableParameter#

RegionCalculationParameter Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

const std::string &get_script() const#

 @brief Get Script.

 This is an algorithm script which can get a PolygonRegionList property. Note that the function `region_calculate` must exist and return a PolygonRegionList property value.
And we provide a sample script to help you to implement your own script:
import visionflow as vf
from visionflow import props, geometry

def get_regions(operation, multi_polygon1, multi_polygon2, region_name):
    """
    Generic function to create a list of PolygonRegion objects
    from the result of a geometric operation on two multi-polygons.
    """
    result = operation(multi_polygon1, multi_polygon2)
    return [
        vf.PolygonRegion().set_polygon(polygon).set_name(region_name)
        for polygon in result
    ]

def region_calculate(sample: vf.ISample) -> props.PolygonRegionList:
    """
    Calculate and return a PolygonRegionList property representing
    the unions and intersections of segmentation and location polygons in a sample.
    """
    ply_region_list = props.PolygonRegionList()

    seg_polygons = sample.get(vf.ToolNodeId("Segmentation", vf.Segmentation.pred)).to_multi_polygons()
    loc_polygons = sample.get(vf.ToolNodeId("Location", vf.Location.pred_keypoints)).to_multi_polygons()

    unions = get_regions(geometry.union_areal, seg_polygons, loc_polygons, "union")
    intersections = get_regions(geometry.intersection, seg_polygons, loc_polygons, "intersection")

    for region in unions + intersections:
        ply_region_list.add(region)

    return ply_region_list

See also

set_script()

Returns:

const std::string & Script

RegionCalculationParameter &set_script(std::string script)#

 @brief Set Script with std::string value.

 This is an algorithm script which can get a PolygonRegionList property. Note that the function `region_calculate` must exist and return a PolygonRegionList property value.
And we provide a sample script to help you to implement your own script:
import visionflow as vf
from visionflow import props, geometry

def get_regions(operation, multi_polygon1, multi_polygon2, region_name):
    """
    Generic function to create a list of PolygonRegion objects
    from the result of a geometric operation on two multi-polygons.
    """
    result = operation(multi_polygon1, multi_polygon2)
    return [
        vf.PolygonRegion().set_polygon(polygon).set_name(region_name)
        for polygon in result
    ]

def region_calculate(sample: vf.ISample) -> props.PolygonRegionList:
    """
    Calculate and return a PolygonRegionList property representing
    the unions and intersections of segmentation and location polygons in a sample.
    """
    ply_region_list = props.PolygonRegionList()

    seg_polygons = sample.get(vf.ToolNodeId("Segmentation", vf.Segmentation.pred)).to_multi_polygons()
    loc_polygons = sample.get(vf.ToolNodeId("Location", vf.Location.pred_keypoints)).to_multi_polygons()

    unions = get_regions(geometry.union_areal, seg_polygons, loc_polygons, "union")
    intersections = get_regions(geometry.intersection, seg_polygons, loc_polygons, "intersection")

    for region in unions + intersections:
        ply_region_list.add(region)

    return ply_region_list

See also

get_script()

Parameters:

script – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

RegionCalculationParameter the reference of this object.

bool get_check_region_name() const#

Get Check Region Name.

Check if the region name returned by the script matches the parameter of LabelClasses.

Returns:

bool Check Region Name

RegionCalculationParameter &set_check_region_name(bool check_region_name)#

Set Check Region Name with bool value.

Check if the region name returned by the script matches the parameter of LabelClasses.

Parameters:

check_region_name – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

RegionCalculationParameter the reference of this object.

const std::map<std::string, TypeValuePair> &get_user_vars() const#

Get User Defined Variables.

The key of the map is the name of the python object and the value of the map is a pair of string which means type-value of the python object.

See also

set_user_vars()

Returns:

const std::map<std::string, TypeValuePair> & User Defined Variables

RegionCalculationParameter &set_user_vars(std::map<std::string, TypeValuePair> user_vars)#

Set User Defined Variables with std::map<std::string, TypeValuePair> value.

The key of the map is the name of the python object and the value of the map is a pair of string which means type-value of the python object.

See also

get_user_vars()

Parameters:

user_vars – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

RegionCalculationParameter the reference of this object.

const TypeValuePair &get_user_vars(const std::string &key) const#

Get value in User Defined Variables with key.

Warning

The key must be exist in User Defined Variables. otherwise, the behavior is undefined and will cause segmentation fault.

Returns:

const std::map<std::string, TypeValuePair> & value in User Defined Variables at key.

RegionCalculationParameter &set_user_vars(const std::string &key, TypeValuePair value)#

Set value in User Defined Variables with key.

Parameters:
  • key – the key to set.

  • value – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

RegionCalculationParameter the reference of this object.

bool user_vars_contains(const std::string &key) const#

Check if the key is exist in User Defined Variables.

Returns:

bool true if the key is exist in User Defined Variables, otherwise false.

size_t get_user_vars_size() const#

Get the size of User Defined Variables.

Returns:

size_t the size of User Defined Variables

TypeValuePair &get_user_vars(const std::string &key)#

Get mutable reference of value in User Defined Variables with key. A new key and default value will be created if the key does not exist.

Returns:

TypeValuePair& the mutable reference of value in User Defined Variables at key.

GeometrySearchFeatureModel Parameters:#

struct GeometrySearchFeaturePoint#

template match feat point structure

Public Members

geometry::Point2f position#

position

geometry::Radian angle = 0#

angle feature

double magnitude = -1#

gradient magnitude

double weight = 1#

weight

bool is_mod_180 = false#

angle should be modulo with 180 or not

class GeometrySearchFeatureChain#

template match feature chain

Public Functions

size_t size() const#

Interface to get the number of feature points in this chain.

Returns:

size_t The number of feature points in this chain.

inline bool empty() const#

If the feature chain is empty or not.

Returns:

true If the feature chain is empty.

Returns:

false If the feature chain is not empty.

void clear()#

clear current feature chain

void add(const GeometrySearchFeaturePoint &feat_point)#

add a new template feature point in to current chain

Parameters:

feat_point – template match feature point

const GeometrySearchFeaturePoint &at(size_t idx) const#

Interface to get feature point at the given index.

Parameters:

idx – The index of the feature point.

Returns:

const GeometrySearchFeaturePoint& The feature point reference at the given index.

void set_closed(bool closed = true)#

Set the feature chain is closed or not.

Parameters:

closed – closed or not

bool get_closed() const#

whether the feature is closed

Returns:

NO_DISCARD true if feature chain is closed

class GeometrySearchFeatureModel#

template match feature model, which contains multiple template match feature chains. A model correspond to a model generated in a train region

Public Functions

void add(const GeometrySearchFeatureChain &feat_chain)#

add a new template feature chain in to current model

Parameters:

feat_chain – template match feature chain

GeometrySearchFeatureModel &set_name(const std::string &model_name)#

Set the name of this feature model.

Parameters:

model_name – The new name of this feature model.

Returns:

GeometrySearchFeatureModel& This feature model.

std::string name() const#

Interface to get name of this region.

Returns:

std::string

size_t size() const#

Interface to get the number of chain in this model.

Returns:

size_t The number of feature chains in this model.

inline bool empty() const#

If the feature chain model is empty or not.

Returns:

true If the feature model is empty.

Returns:

false If the feature model is not empty.

void clear()#

clear current feature model

const GeometrySearchFeatureChain &at(size_t idx) const#

Interface to get feature chain at the given index.

Parameters:

idx – The index of the feature chain.

Returns:

const GeometrySearchFeatureChain& The feature chain reference at the given index.

class GeometrySearchFeatureModelList : public virtual visionflow::param::IParameter#

template match feature models class, which contains multiple template match feature models(each model represent a train region)

Public Functions

size_t size() const#

Interface to get the number of chain in this list.

Returns:

size_t The number of feature chains in this list.

std::vector<std::string> keys() const#

Get all feature model IDs in this list.

Returns:

std::vector<std::string> The IDs of all feature models in this list.

inline bool empty() const#

If the feature chain list is empty or not.

Returns:

true If the feature chain list is empty.

Returns:

false If the feature chain list is not empty.

void clear()#

clear current feature chain list

void add(const GeometrySearchFeatureModel &feat_model)#

add a new template feature chain in to current list

Parameters:

feat_model – template match feature chain

const GeometrySearchFeatureModel &at(const std::string &model_key) const#

Interface to get feature chain at the given index.

Parameters:

model_key – ID of model

Returns:

const GeometrySearchFeatureModel& The feature chain reference at the given index.

bool contains(const std::string &model_key) const#

Whether the region with the given model ID exists in this list.

void erase(const std::string &model_key)#

Interface to remove the model at the given model ID. Nothing will be done if the model name is not found.

Parameters:

model_key – The model ID to be removed

IDReader Inference Parameters#

class Code128Parameters : public visionflow::param::ISchemable#

Code128Parameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

bool get_enable() const#

Get Enable.

Enable this parameter group.

See also

set_enable()

Returns:

bool Enable

Code128Parameters &set_enable(bool enable)#

Set Enable with bool value.

Enable this parameter group.

See also

get_enable()

Parameters:

enable – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

Code128Parameters the reference of this object.

bool get_quiet_zone() const#

Get Quiet Zone.

Enable quiet zone or not.

See also

set_quiet_zone()

Returns:

bool Quiet Zone

Code128Parameters &set_quiet_zone(bool quiet_zone)#

Set Quiet Zone with bool value.

Enable quiet zone or not.

See also

get_quiet_zone()

Parameters:

quiet_zone – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

Code128Parameters the reference of this object.

enum visionflow::param::IDReader1DCheckSumType#

Values:

enumerator kBarCheckSumTypeCheckNone = 0#
enumerator kBarCheckSumTypeVerify = 1#
enumerator kBarCheckSumTypeVerifyAndTransmit = 2#
class Code39Parameters : public visionflow::param::ISchemable#

Code39Parameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

bool get_enable() const#

Get Enable.

Enable this parameter group.

See also

set_enable()

Returns:

bool Enable

Code39Parameters &set_enable(bool enable)#

Set Enable with bool value.

Enable this parameter group.

See also

get_enable()

Parameters:

enable – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

Code39Parameters the reference of this object.

bool get_quiet_zone() const#

Get Quiet Zone.

Enable quiet zone or not.

See also

set_quiet_zone()

Returns:

bool Quiet Zone

Code39Parameters &set_quiet_zone(bool quiet_zone)#

Set Quiet Zone with bool value.

Enable quiet zone or not.

See also

get_quiet_zone()

Parameters:

quiet_zone – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

Code39Parameters the reference of this object.

bool get_full_ascii() const#

Get Full ASCII.

Enable Full ASCII or not.

See also

set_full_ascii()

Returns:

bool Full ASCII

Code39Parameters &set_full_ascii(bool full_ascii)#

Set Full ASCII with bool value.

Enable Full ASCII or not.

See also

get_full_ascii()

Parameters:

full_ascii – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

Code39Parameters the reference of this object.

const IDReader1DCheckSumType &get_check_sum_type() const#

Get Verification Type.

The check sum type to verify the result.

Returns:

const IDReader1DCheckSumType & Verification Type

Code39Parameters &set_check_sum_type(IDReader1DCheckSumType check_sum_type)#

Set Verification Type with IDReader1DCheckSumType value.

The check sum type to verify the result.

Parameters:

check_sum_type – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

Code39Parameters the reference of this object.

class Code93Parameters : public visionflow::param::ISchemable#

Code93Parameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

bool get_enable() const#

Get Enable.

Enable this parameter group.

See also

set_enable()

Returns:

bool Enable

Code93Parameters &set_enable(bool enable)#

Set Enable with bool value.

Enable this parameter group.

See also

get_enable()

Parameters:

enable – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

Code93Parameters the reference of this object.

bool get_quiet_zone() const#

Get Quiet Zone.

Enable quiet zone or not.

See also

set_quiet_zone()

Returns:

bool Quiet Zone

Code93Parameters &set_quiet_zone(bool quiet_zone)#

Set Quiet Zone with bool value.

Enable quiet zone or not.

See also

get_quiet_zone()

Parameters:

quiet_zone – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

Code93Parameters the reference of this object.

class UpcaParameters : public visionflow::param::ISchemable#

UpcaParameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

bool get_enable() const#

Get Enable.

Enable this parameter group.

See also

set_enable()

Returns:

bool Enable

UpcaParameters &set_enable(bool enable)#

Set Enable with bool value.

Enable this parameter group.

See also

get_enable()

Parameters:

enable – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

UpcaParameters the reference of this object.

bool get_quiet_zone() const#

Get Quiet Zone.

Enable quiet zone or not.

See also

set_quiet_zone()

Returns:

bool Quiet Zone

UpcaParameters &set_quiet_zone(bool quiet_zone)#

Set Quiet Zone with bool value.

Enable quiet zone or not.

See also

get_quiet_zone()

Parameters:

quiet_zone – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

UpcaParameters the reference of this object.

class UpceParameters : public visionflow::param::ISchemable#

UpceParameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

bool get_enable() const#

Get Enable.

Enable this parameter group.

See also

set_enable()

Returns:

bool Enable

UpceParameters &set_enable(bool enable)#

Set Enable with bool value.

Enable this parameter group.

See also

get_enable()

Parameters:

enable – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

UpceParameters the reference of this object.

bool get_quiet_zone() const#

Get Quiet Zone.

Enable quiet zone or not.

See also

set_quiet_zone()

Returns:

bool Quiet Zone

UpceParameters &set_quiet_zone(bool quiet_zone)#

Set Quiet Zone with bool value.

Enable quiet zone or not.

See also

get_quiet_zone()

Parameters:

quiet_zone – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

UpceParameters the reference of this object.

class Ean13Parameters : public visionflow::param::ISchemable#

Ean13Parameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

bool get_enable() const#

Get Enable.

Enable this parameter group.

See also

set_enable()

Returns:

bool Enable

Ean13Parameters &set_enable(bool enable)#

Set Enable with bool value.

Enable this parameter group.

See also

get_enable()

Parameters:

enable – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

Ean13Parameters the reference of this object.

bool get_quiet_zone() const#

Get Quiet Zone.

Enable quiet zone or not.

See also

set_quiet_zone()

Returns:

bool Quiet Zone

Ean13Parameters &set_quiet_zone(bool quiet_zone)#

Set Quiet Zone with bool value.

Enable quiet zone or not.

See also

get_quiet_zone()

Parameters:

quiet_zone – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

Ean13Parameters the reference of this object.

class Ean8Parameters : public visionflow::param::ISchemable#

Ean8Parameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

bool get_enable() const#

Get Enable.

Enable this parameter group.

See also

set_enable()

Returns:

bool Enable

Ean8Parameters &set_enable(bool enable)#

Set Enable with bool value.

Enable this parameter group.

See also

get_enable()

Parameters:

enable – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

Ean8Parameters the reference of this object.

bool get_quiet_zone() const#

Get Quiet Zone.

Enable quiet zone or not.

See also

set_quiet_zone()

Returns:

bool Quiet Zone

Ean8Parameters &set_quiet_zone(bool quiet_zone)#

Set Quiet Zone with bool value.

Enable quiet zone or not.

See also

get_quiet_zone()

Parameters:

quiet_zone – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

Ean8Parameters the reference of this object.

class ChooseIDReader1DTypes : public visionflow::param::ISchemable#

ChooseIDReader1DTypes Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

const Code128Parameters &get_code128() const#

Get Code128.

Enable Code128 and set parameters.

See also

set_code128()

Returns:

const Code128Parameters & Code128

ChooseIDReader1DTypes &set_code128(Code128Parameters code128)#

Set Code128 with Code128Parameters value.

Enable Code128 and set parameters.

See also

get_code128()

Parameters:

code128 – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ChooseIDReader1DTypes the reference of this object.

Code128Parameters &get_code128()#

Get mutable reference of Code128.

Enable Code128 and set parameters.

Returns:

ChooseIDReader1DTypes& the mutable reference of the group.

const Code39Parameters &get_code39() const#

Get Code39.

Enable code39 and set parameters.

See also

set_code39()

Returns:

const Code39Parameters & Code39

ChooseIDReader1DTypes &set_code39(Code39Parameters code39)#

Set Code39 with Code39Parameters value.

Enable code39 and set parameters.

See also

get_code39()

Parameters:

code39 – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ChooseIDReader1DTypes the reference of this object.

Code39Parameters &get_code39()#

Get mutable reference of Code39.

Enable code39 and set parameters.

Returns:

ChooseIDReader1DTypes& the mutable reference of the group.

const Code93Parameters &get_code93() const#

Get Code93.

Enable Code93 and set parameters.

See also

set_code93()

Returns:

const Code93Parameters & Code93

ChooseIDReader1DTypes &set_code93(Code93Parameters code93)#

Set Code93 with Code93Parameters value.

Enable Code93 and set parameters.

See also

get_code93()

Parameters:

code93 – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ChooseIDReader1DTypes the reference of this object.

Code93Parameters &get_code93()#

Get mutable reference of Code93.

Enable Code93 and set parameters.

Returns:

ChooseIDReader1DTypes& the mutable reference of the group.

const UpcaParameters &get_upca() const#

Get UPCA.

Enable UPCA and set parameters.

See also

set_upca()

Returns:

const UpcaParameters & UPCA

ChooseIDReader1DTypes &set_upca(UpcaParameters upca)#

Set UPCA with UpcaParameters value.

Enable UPCA and set parameters.

See also

get_upca()

Parameters:

upca – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ChooseIDReader1DTypes the reference of this object.

UpcaParameters &get_upca()#

Get mutable reference of UPCA.

Enable UPCA and set parameters.

Returns:

ChooseIDReader1DTypes& the mutable reference of the group.

const UpceParameters &get_upce() const#

Get UPCE.

Enable UPCE and set parameters.

See also

set_upce()

Returns:

const UpceParameters & UPCE

ChooseIDReader1DTypes &set_upce(UpceParameters upce)#

Set UPCE with UpceParameters value.

Enable UPCE and set parameters.

See also

get_upce()

Parameters:

upce – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ChooseIDReader1DTypes the reference of this object.

UpceParameters &get_upce()#

Get mutable reference of UPCE.

Enable UPCE and set parameters.

Returns:

ChooseIDReader1DTypes& the mutable reference of the group.

const Ean13Parameters &get_ean13() const#

Get EAN13.

Enable EAN13 and set parameters.

See also

set_ean13()

Returns:

const Ean13Parameters & EAN13

ChooseIDReader1DTypes &set_ean13(Ean13Parameters ean13)#

Set EAN13 with Ean13Parameters value.

Enable EAN13 and set parameters.

See also

get_ean13()

Parameters:

ean13 – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ChooseIDReader1DTypes the reference of this object.

Ean13Parameters &get_ean13()#

Get mutable reference of EAN13.

Enable EAN13 and set parameters.

Returns:

ChooseIDReader1DTypes& the mutable reference of the group.

const Ean8Parameters &get_ean8() const#

Get EAN8.

Enable EAN8 and set parameters.

See also

set_ean8()

Returns:

const Ean8Parameters & EAN8

ChooseIDReader1DTypes &set_ean8(Ean8Parameters ean8)#

Set EAN8 with Ean8Parameters value.

Enable EAN8 and set parameters.

See also

get_ean8()

Parameters:

ean8 – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ChooseIDReader1DTypes the reference of this object.

Ean8Parameters &get_ean8()#

Get mutable reference of EAN8.

Enable EAN8 and set parameters.

Returns:

ChooseIDReader1DTypes& the mutable reference of the group.

class DMECC200Parameters : public visionflow::param::ISchemable#

DMECC200Parameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

bool get_enable() const#

Get Enable.

Enable this parameter group.

See also

set_enable()

Returns:

bool Enable

DMECC200Parameters &set_enable(bool enable)#

Set Enable with bool value.

Enable this parameter group.

See also

get_enable()

Parameters:

enable – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

DMECC200Parameters the reference of this object.

class QRCParameters : public visionflow::param::ISchemable#

QRCParameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

bool get_enable() const#

Get Enable.

Enable this parameter group.

See also

set_enable()

Returns:

bool Enable

QRCParameters &set_enable(bool enable)#

Set Enable with bool value.

Enable this parameter group.

See also

get_enable()

Parameters:

enable – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

QRCParameters the reference of this object.

class QRCM1Parameters : public visionflow::param::ISchemable#

QRCM1Parameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

bool get_enable() const#

Get Enable.

Enable this parameter group.

See also

set_enable()

Returns:

bool Enable

QRCM1Parameters &set_enable(bool enable)#

Set Enable with bool value.

Enable this parameter group.

See also

get_enable()

Parameters:

enable – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

QRCM1Parameters the reference of this object.

class QRCM2Parameters : public visionflow::param::ISchemable#

QRCM2Parameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

bool get_enable() const#

Get Enable.

Enable this parameter group.

See also

set_enable()

Returns:

bool Enable

QRCM2Parameters &set_enable(bool enable)#

Set Enable with bool value.

Enable this parameter group.

See also

get_enable()

Parameters:

enable – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

QRCM2Parameters the reference of this object.

class MicroQRCParameters : public visionflow::param::ISchemable#

MicroQRCParameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

bool get_enable() const#

Get Enable.

Enable this parameter group.

See also

set_enable()

Returns:

bool Enable

MicroQRCParameters &set_enable(bool enable)#

Set Enable with bool value.

Enable this parameter group.

See also

get_enable()

Parameters:

enable – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

MicroQRCParameters the reference of this object.

class ChooseIDReader2DTypes : public visionflow::param::ISchemable#

ChooseIDReader2DTypes Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

const DMECC200Parameters &get_dmecc200() const#

Get DM-ECC200.

Enable DM-ECC200 and set parameters.

See also

set_dmecc200()

Returns:

const DMECC200Parameters & DM-ECC200

ChooseIDReader2DTypes &set_dmecc200(DMECC200Parameters dmecc200)#

Set DM-ECC200 with DMECC200Parameters value.

Enable DM-ECC200 and set parameters.

See also

get_dmecc200()

Parameters:

dmecc200 – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ChooseIDReader2DTypes the reference of this object.

DMECC200Parameters &get_dmecc200()#

Get mutable reference of DM-ECC200.

Enable DM-ECC200 and set parameters.

Returns:

ChooseIDReader2DTypes& the mutable reference of the group.

const QRCParameters &get_qrc() const#

Get QR.

Enable QR and set parameters.

See also

set_qrc()

Returns:

const QRCParameters & QR

ChooseIDReader2DTypes &set_qrc(QRCParameters qrc)#

Set QR with QRCParameters value.

Enable QR and set parameters.

See also

get_qrc()

Parameters:

qrc – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ChooseIDReader2DTypes the reference of this object.

QRCParameters &get_qrc()#

Get mutable reference of QR.

Enable QR and set parameters.

Returns:

ChooseIDReader2DTypes& the mutable reference of the group.

const QRCM1Parameters &get_qrcm1() const#

Get QR-CM1.

Enable QR-CM1 and set parameters.

See also

set_qrcm1()

Returns:

const QRCM1Parameters & QR-CM1

ChooseIDReader2DTypes &set_qrcm1(QRCM1Parameters qrcm1)#

Set QR-CM1 with QRCM1Parameters value.

Enable QR-CM1 and set parameters.

See also

get_qrcm1()

Parameters:

qrcm1 – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ChooseIDReader2DTypes the reference of this object.

QRCM1Parameters &get_qrcm1()#

Get mutable reference of QR-CM1.

Enable QR-CM1 and set parameters.

Returns:

ChooseIDReader2DTypes& the mutable reference of the group.

const QRCM2Parameters &get_qrcm2() const#

Get QR-CM2.

Enable QR-CM2 and set parameters.

See also

set_qrcm2()

Returns:

const QRCM2Parameters & QR-CM2

ChooseIDReader2DTypes &set_qrcm2(QRCM2Parameters qrcm2)#

Set QR-CM2 with QRCM2Parameters value.

Enable QR-CM2 and set parameters.

See also

get_qrcm2()

Parameters:

qrcm2 – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ChooseIDReader2DTypes the reference of this object.

QRCM2Parameters &get_qrcm2()#

Get mutable reference of QR-CM2.

Enable QR-CM2 and set parameters.

Returns:

ChooseIDReader2DTypes& the mutable reference of the group.

const MicroQRCParameters &get_microqrc() const#

Get Micro-QR-C.

Enable Micro-QR-C and set parameters.

See also

set_microqrc()

Returns:

const MicroQRCParameters & Micro-QR-C

ChooseIDReader2DTypes &set_microqrc(MicroQRCParameters microqrc)#

Set Micro-QR-C with MicroQRCParameters value.

Enable Micro-QR-C and set parameters.

See also

get_microqrc()

Parameters:

microqrc – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ChooseIDReader2DTypes the reference of this object.

MicroQRCParameters &get_microqrc()#

Get mutable reference of Micro-QR-C.

Enable Micro-QR-C and set parameters.

Returns:

ChooseIDReader2DTypes& the mutable reference of the group.

class IDReader1DParameters : public visionflow::param::ISchemable#

IDReader1DParameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

int get_num_scanlines() const#

Get Num Scanlines.

The number of scan lines for 1d IDReader decoder.

Returns:

int Num Scanlines

IDReader1DParameters &set_num_scanlines(int num_scanlines)#

Set Num Scanlines with int value.

The number of scan lines for 1d IDReader decoder.

Parameters:

num_scanlines – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

IDReader1DParameters the reference of this object.

const ChooseIDReader1DTypes &get_types_params() const#

Get 1D IDReader Types and Parameters.

Set decode types and parameters of 1d IDReader.

Returns:

const ChooseIDReader1DTypes & 1D IDReader Types and Parameters

IDReader1DParameters &set_types_params(ChooseIDReader1DTypes types_params)#

Set 1D IDReader Types and Parameters with ChooseIDReader1DTypes value.

Set decode types and parameters of 1d IDReader.

Parameters:

types_params – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

IDReader1DParameters the reference of this object.

ChooseIDReader1DTypes &get_types_params()#

Get mutable reference of 1D IDReader Types and Parameters.

Set decode types and parameters of 1d IDReader.

Returns:

IDReader1DParameters& the mutable reference of the group.

class IDReader2DParameters : public visionflow::param::ISchemable#

IDReader2DParameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

const PolarityMode &get_polarity() const#

Get 2D IDReader Polarity.

The polarity of 2D IDReader, include Unspecified, BlackOnWhite and WhiteOnBlack. Polarity refers to the contrast between the dark and light modules within the code. BlackOnWhite means the dark modules represent the encoded data, while the light modules serve as a background. WhiteOnBlack means the light modules represent the encoded data, while the dark modules serve as a background.

See also

set_polarity()

Returns:

const PolarityMode & 2D IDReader Polarity

IDReader2DParameters &set_polarity(PolarityMode polarity)#

Set 2D IDReader Polarity with PolarityMode value.

The polarity of 2D IDReader, include Unspecified, BlackOnWhite and WhiteOnBlack. Polarity refers to the contrast between the dark and light modules within the code. BlackOnWhite means the dark modules represent the encoded data, while the light modules serve as a background. WhiteOnBlack means the light modules represent the encoded data, while the dark modules serve as a background.

See also

get_polarity()

Parameters:

polarity – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

IDReader2DParameters the reference of this object.

const std::vector<int> &get_module_width_range() const#

Get Module Width Range.

Set width scale of DM symbol module. Range: 1 <= min_val <= max_val <= 100.

Returns:

const std::vector<int> & Module Width Range

IDReader2DParameters &set_module_width_range(std::vector<int> module_width_range)#

Set Module Width Range with std::vector<int> value.

Set width scale of DM symbol module. Range: 1 <= min_val <= max_val <= 100.

Parameters:

module_width_range – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

IDReader2DParameters the reference of this object.

bool module_width_range_contains(int value) const#

Check if the Module Width Range contains the value.

Returns:

bool true if the Module Width Range contains the value, otherwise false.

int get_module_width_range_left() const#

Get left point value of Module Width Range.

Returns:

const std::vector<int> & left point value of Module Width Range

int get_module_width_range_right() const#

Get the right point value of Module Width Range.

Returns:

const std::vector<int> & the right point value of Module Width Range

IDReader2DParameters &set_module_width_range_left(int module_width_range_left)#

Set left point value of Module Width Range with std::vector<int> value.

Set width scale of DM symbol module. Range: 1 <= min_val <= max_val <= 100.

Parameters:

module_width_range_left – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

IDReader2DParameters the reference of this object.

IDReader2DParameters &set_module_width_range_right(int module_width_range_right)#

Set the right point value of Module Width Range with std::vector<int> value.

Set width scale of DM symbol module. Range: 1 <= min_val <= max_val <= 100.

Parameters:

module_width_range_right – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

IDReader2DParameters the reference of this object.

int get_time_limit() const#

Get Time Limit.

Time limit as millisecond. When value = 0, this parameter is not enabled.

See also

set_time_limit()

Returns:

int Time Limit

IDReader2DParameters &set_time_limit(int time_limit)#

Set Time Limit with int value.

Time limit as millisecond. When value = 0, this parameter is not enabled.

See also

get_time_limit()

Parameters:

time_limit – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

IDReader2DParameters the reference of this object.

const ChooseIDReader2DTypes &get_types_params() const#

Get 2D IDReader Types and Parameters.

Set decode types and parameters of 2d IDReader.

Returns:

const ChooseIDReader2DTypes & 2D IDReader Types and Parameters

IDReader2DParameters &set_types_params(ChooseIDReader2DTypes types_params)#

Set 2D IDReader Types and Parameters with ChooseIDReader2DTypes value.

Set decode types and parameters of 2d IDReader.

Parameters:

types_params – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

IDReader2DParameters the reference of this object.

ChooseIDReader2DTypes &get_types_params()#

Get mutable reference of 2D IDReader Types and Parameters.

Set decode types and parameters of 2d IDReader.

Returns:

IDReader2DParameters& the mutable reference of the group.

class IDReaderDecoderParameters : public visionflow::param::SchemableParameter#

IDReaderDecoderParameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

bool get_show_all_results() const#

Get Show All Results.

Enable this option to output all location results.

Returns:

bool Show All Results

IDReaderDecoderParameters &set_show_all_results(bool show_all_results)#

Set Show All Results with bool value.

Enable this option to output all location results.

Parameters:

show_all_results – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

IDReaderDecoderParameters the reference of this object.

const IDReader1DParameters &get_idreader_1d_param() const#

Get 1D IDReader Parameters.

Parameters for 1d IDReader.

Returns:

const IDReader1DParameters & 1D IDReader Parameters

IDReaderDecoderParameters &set_idreader_1d_param(IDReader1DParameters idreader_1d_param)#

Set 1D IDReader Parameters with IDReader1DParameters value.

Parameters for 1d IDReader.

Parameters:

idreader_1d_param – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

IDReaderDecoderParameters the reference of this object.

IDReader1DParameters &get_idreader_1d_param()#

Get mutable reference of 1D IDReader Parameters.

Parameters for 1d IDReader.

Returns:

IDReaderDecoderParameters& the mutable reference of the group.

const IDReader2DParameters &get_idreader_2d_param() const#

Get 2D IDReader Parameters.

Parameters for 2d IDReader.

Returns:

const IDReader2DParameters & 2D IDReader Parameters

IDReaderDecoderParameters &set_idreader_2d_param(IDReader2DParameters idreader_2d_param)#

Set 2D IDReader Parameters with IDReader2DParameters value.

Parameters for 2d IDReader.

Parameters:

idreader_2d_param – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

IDReaderDecoderParameters the reference of this object.

IDReader2DParameters &get_idreader_2d_param()#

Get mutable reference of 2D IDReader Parameters.

Parameters for 2d IDReader.

Returns:

IDReaderDecoderParameters& the mutable reference of the group.

class IDReaderLocationModelParameters : public visionflow::param::SchemableParameter#

IDReaderLocationModelParameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

int get_input_width() const#

Get Location Input Width.

The image width for location inference input.

Returns:

int Location Input Width

IDReaderLocationModelParameters &set_input_width(int input_width)#

Set Location Input Width with int value.

The image width for location inference input.

Parameters:

input_width – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

IDReaderLocationModelParameters the reference of this object.

int get_input_height() const#

Get Location Input Height.

The image height for location inference input.

Returns:

int Location Input Height

IDReaderLocationModelParameters &set_input_height(int input_height)#

Set Location Input Height with int value.

The image height for location inference input.

Parameters:

input_height – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

IDReaderLocationModelParameters the reference of this object.

int get_barcode_module_width() const#

Get ID Code Module Width.

Setting the module width of 1D and 2D barcode to an appropriate value can make positioning more accurate.

Returns:

int ID Code Module Width

IDReaderLocationModelParameters &set_barcode_module_width(int barcode_module_width)#

Set ID Code Module Width with int value.

Setting the module width of 1D and 2D barcode to an appropriate value can make positioning more accurate.

Parameters:

barcode_module_width – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

IDReaderLocationModelParameters the reference of this object.

Measure Parameters#

class CaliperSingleEdgeParameters : public visionflow::param::SchemableParameter#

CaliperSingleEdgeParameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

const RotateRectParameters &get_rotate_rect() const#

Get Rotate Rect.

ROI

Returns:

const RotateRectParameters & Rotate Rect

CaliperSingleEdgeParameters &set_rotate_rect(RotateRectParameters rotate_rect)#

Set Rotate Rect with RotateRectParameters value.

ROI

Parameters:

rotate_rect – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

CaliperSingleEdgeParameters the reference of this object.

RotateRectParameters &get_rotate_rect()#

Get mutable reference of Rotate Rect.

ROI

Returns:

CaliperSingleEdgeParameters& the mutable reference of the group.

const EdgePolarityMode &get_edge_polarity_mode() const#

Get Edge Polarity Mode.

Set the type of edge polarity.When the polarity is set to kDarkToLight, Only search for edges from dark to light. When the polarity is set to kLightToDark,Only search for edges from light to dark. When the polarity is set to kBoth,search for edges from light to dark and from light to dark

Returns:

const EdgePolarityMode & Edge Polarity Mode

CaliperSingleEdgeParameters &set_edge_polarity_mode(EdgePolarityMode edge_polarity_mode)#

Set Edge Polarity Mode with EdgePolarityMode value.

Set the type of edge polarity.When the polarity is set to kDarkToLight, Only search for edges from dark to light. When the polarity is set to kLightToDark,Only search for edges from light to dark. When the polarity is set to kBoth,search for edges from light to dark and from light to dark

Parameters:

edge_polarity_mode – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

CaliperSingleEdgeParameters the reference of this object.

const EdgeOrderMode &get_edge_order_mode() const#

Get Edge Order Mode.

Set the type of edge order. When the order is set to kBestScore, the results are sorted in descending order of scores. When the order is set to kFirstEdge, the results are sorted along the detection direction. When the order is set to kLastEdge, the results are sorted in the opposite direction of the detection direction

Returns:

const EdgeOrderMode & Edge Order Mode

CaliperSingleEdgeParameters &set_edge_order_mode(EdgeOrderMode edge_order_mode)#

Set Edge Order Mode with EdgeOrderMode value.

Set the type of edge order. When the order is set to kBestScore, the results are sorted in descending order of scores. When the order is set to kFirstEdge, the results are sorted along the detection direction. When the order is set to kLastEdge, the results are sorted in the opposite direction of the detection direction

Parameters:

edge_order_mode – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

CaliperSingleEdgeParameters the reference of this object.

const EdgeFilterPropertyParameters &get_edge_filter() const#

Get Edge Filter.

Filter results based on size, contrast threshold, and sensitivity threshold

Returns:

const EdgeFilterPropertyParameters & Edge Filter

CaliperSingleEdgeParameters &set_edge_filter(EdgeFilterPropertyParameters edge_filter)#

Set Edge Filter with EdgeFilterPropertyParameters value.

Filter results based on size, contrast threshold, and sensitivity threshold

Parameters:

edge_filter – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

CaliperSingleEdgeParameters the reference of this object.

EdgeFilterPropertyParameters &get_edge_filter()#

Get mutable reference of Edge Filter.

Filter results based on size, contrast threshold, and sensitivity threshold

Returns:

CaliperSingleEdgeParameters& the mutable reference of the group.

int get_max_result_num() const#

Get Max Result Num.

Maximum number of results

Returns:

int Max Result Num

CaliperSingleEdgeParameters &set_max_result_num(int max_result_num)#

Set Max Result Num with int value.

Maximum number of results

Parameters:

max_result_num – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

CaliperSingleEdgeParameters the reference of this object.

const CaliperSingleEdgeFuncParameters &get_score_func() const#

Get Score Func.

Function used to rate results

See also

set_score_func()

Returns:

const CaliperSingleEdgeFuncParameters & Score Func

CaliperSingleEdgeParameters &set_score_func(CaliperSingleEdgeFuncParameters score_func)#

Set Score Func with CaliperSingleEdgeFuncParameters value.

Function used to rate results

See also

get_score_func()

Parameters:

score_func – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

CaliperSingleEdgeParameters the reference of this object.

CaliperSingleEdgeFuncParameters &get_score_func()#

Get mutable reference of Score Func.

Function used to rate results

Returns:

CaliperSingleEdgeParameters& the mutable reference of the group.

class CaliperDualEdgeParameters : public visionflow::param::SchemableParameter#

CaliperDualEdgeParameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

const RotateRectParameters &get_rotate_rect() const#

Get Rotate Rect.

ROI

Returns:

const RotateRectParameters & Rotate Rect

CaliperDualEdgeParameters &set_rotate_rect(RotateRectParameters rotate_rect)#

Set Rotate Rect with RotateRectParameters value.

ROI

Parameters:

rotate_rect – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

CaliperDualEdgeParameters the reference of this object.

RotateRectParameters &get_rotate_rect()#

Get mutable reference of Rotate Rect.

ROI

Returns:

CaliperDualEdgeParameters& the mutable reference of the group.

const EdgePolarityMode &get_edge_polarity_mode1() const#

Get Edge Polarity Mode1.

Set the type of edge polarity.When the polarity is set to kDarkToLight, Only search for edges from dark to light. When the polarity is set to kLightToDark,Only search for edges from light to dark. When the polarity is set to kBoth,search for edges from light to dark and from light to dark

Returns:

const EdgePolarityMode & Edge Polarity Mode1

CaliperDualEdgeParameters &set_edge_polarity_mode1(EdgePolarityMode edge_polarity_mode1)#

Set Edge Polarity Mode1 with EdgePolarityMode value.

Set the type of edge polarity.When the polarity is set to kDarkToLight, Only search for edges from dark to light. When the polarity is set to kLightToDark,Only search for edges from light to dark. When the polarity is set to kBoth,search for edges from light to dark and from light to dark

Parameters:

edge_polarity_mode1 – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

CaliperDualEdgeParameters the reference of this object.

const EdgePolarityMode &get_edge_polarity_mode2() const#

Get Edge Polarity Mode2.

Set the type of edge polarity.When the polarity is set to kDarkToLight, Only search for edges from dark to light. When the polarity is set to kLightToDark,Only search for edges from light to dark. When the polarity is set to kBoth,search for edges from light to dark and from light to dark

Returns:

const EdgePolarityMode & Edge Polarity Mode2

CaliperDualEdgeParameters &set_edge_polarity_mode2(EdgePolarityMode edge_polarity_mode2)#

Set Edge Polarity Mode2 with EdgePolarityMode value.

Set the type of edge polarity.When the polarity is set to kDarkToLight, Only search for edges from dark to light. When the polarity is set to kLightToDark,Only search for edges from light to dark. When the polarity is set to kBoth,search for edges from light to dark and from light to dark

Parameters:

edge_polarity_mode2 – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

CaliperDualEdgeParameters the reference of this object.

const EdgeOrderMode &get_edge_order_mode() const#

Get Edge Order Mode.

Set the type of edge order. When the order is set to kBestScore, the results are sorted in descending order of scores. When the order is set to kFirstEdge, the results are sorted along the detection direction. When the order is set to kLastEdge, the results are sorted in the opposite direction of the detection direction

Returns:

const EdgeOrderMode & Edge Order Mode

CaliperDualEdgeParameters &set_edge_order_mode(EdgeOrderMode edge_order_mode)#

Set Edge Order Mode with EdgeOrderMode value.

Set the type of edge order. When the order is set to kBestScore, the results are sorted in descending order of scores. When the order is set to kFirstEdge, the results are sorted along the detection direction. When the order is set to kLastEdge, the results are sorted in the opposite direction of the detection direction

Parameters:

edge_order_mode – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

CaliperDualEdgeParameters the reference of this object.

const EdgeFilterPropertyParameters &get_edge_filter() const#

Get Edge Filter.

Filter results based on size, contrast threshold, and sensitivity threshold

Returns:

const EdgeFilterPropertyParameters & Edge Filter

CaliperDualEdgeParameters &set_edge_filter(EdgeFilterPropertyParameters edge_filter)#

Set Edge Filter with EdgeFilterPropertyParameters value.

Filter results based on size, contrast threshold, and sensitivity threshold

Parameters:

edge_filter – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

CaliperDualEdgeParameters the reference of this object.

EdgeFilterPropertyParameters &get_edge_filter()#

Get mutable reference of Edge Filter.

Filter results based on size, contrast threshold, and sensitivity threshold

Returns:

CaliperDualEdgeParameters& the mutable reference of the group.

int get_max_result_num() const#

Get Max Result Num.

Maximum number of results

Returns:

int Max Result Num

CaliperDualEdgeParameters &set_max_result_num(int max_result_num)#

Set Max Result Num with int value.

Maximum number of results

Parameters:

max_result_num – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

CaliperDualEdgeParameters the reference of this object.

double get_edge_pair_width() const#

Get Edge Pair Width.

Expected width of edge pairs

Returns:

double Edge Pair Width

CaliperDualEdgeParameters &set_edge_pair_width(double edge_pair_width)#

Set Edge Pair Width with double value.

Expected width of edge pairs

Parameters:

edge_pair_width – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

CaliperDualEdgeParameters the reference of this object.

const CaliperDualEdgeFuncParameters &get_score_func() const#

Get Score Func.

Function used to rate results

See also

set_score_func()

Returns:

const CaliperDualEdgeFuncParameters & Score Func

CaliperDualEdgeParameters &set_score_func(CaliperDualEdgeFuncParameters score_func)#

Set Score Func with CaliperDualEdgeFuncParameters value.

Function used to rate results

See also

get_score_func()

Parameters:

score_func – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

CaliperDualEdgeParameters the reference of this object.

CaliperDualEdgeFuncParameters &get_score_func()#

Get mutable reference of Score Func.

Function used to rate results

Returns:

CaliperDualEdgeParameters& the mutable reference of the group.

class CaliperAnnularEdgeParameters : public visionflow::param::SchemableParameter#

CaliperAnnularEdgeParameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

bool get_enable_angle_normalization() const#

Get Enable.

Enable this parameter group.

Returns:

bool Enable

CaliperAnnularEdgeParameters &set_enable_angle_normalization(bool enable_angle_normalization)#

Set Enable with bool value.

Enable this parameter group.

Parameters:

enable_angle_normalization – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

CaliperAnnularEdgeParameters the reference of this object.

const AnnularSectionParameters &get_annular_section() const#

Get Annular Section.

ROI

Returns:

const AnnularSectionParameters & Annular Section

CaliperAnnularEdgeParameters &set_annular_section(AnnularSectionParameters annular_section)#

Set Annular Section with AnnularSectionParameters value.

ROI

Parameters:

annular_section – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

CaliperAnnularEdgeParameters the reference of this object.

AnnularSectionParameters &get_annular_section()#

Get mutable reference of Annular Section.

ROI

Returns:

CaliperAnnularEdgeParameters& the mutable reference of the group.

const EdgePolarityMode &get_edge_polarity_mode() const#

Get Edge Polarity Mode.

Set the type of edge polarity.When the polarity is set to kDarkToLight, Only search for edges from dark to light. When the polarity is set to kLightToDark,Only search for edges from light to dark. When the polarity is set to kBoth,search for edges from light to dark and from light to dark

Returns:

const EdgePolarityMode & Edge Polarity Mode

CaliperAnnularEdgeParameters &set_edge_polarity_mode(EdgePolarityMode edge_polarity_mode)#

Set Edge Polarity Mode with EdgePolarityMode value.

Set the type of edge polarity.When the polarity is set to kDarkToLight, Only search for edges from dark to light. When the polarity is set to kLightToDark,Only search for edges from light to dark. When the polarity is set to kBoth,search for edges from light to dark and from light to dark

Parameters:

edge_polarity_mode – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

CaliperAnnularEdgeParameters the reference of this object.

const EdgeOrderMode &get_edge_order_mode() const#

Get Edge Order Mode.

Set the type of edge order. When the order is set to kBestScore, the results are sorted in descending order of scores. When the order is set to kFirstEdge, the results are sorted along the detection direction. When the order is set to kLastEdge, the results are sorted in the opposite direction of the detection direction

Returns:

const EdgeOrderMode & Edge Order Mode

CaliperAnnularEdgeParameters &set_edge_order_mode(EdgeOrderMode edge_order_mode)#

Set Edge Order Mode with EdgeOrderMode value.

Set the type of edge order. When the order is set to kBestScore, the results are sorted in descending order of scores. When the order is set to kFirstEdge, the results are sorted along the detection direction. When the order is set to kLastEdge, the results are sorted in the opposite direction of the detection direction

Parameters:

edge_order_mode – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

CaliperAnnularEdgeParameters the reference of this object.

const EdgeFilterPropertyParameters &get_edge_filter() const#

Get Edge Filter.

Filter results based on size, contrast threshold, and sensitivity threshold

Returns:

const EdgeFilterPropertyParameters & Edge Filter

CaliperAnnularEdgeParameters &set_edge_filter(EdgeFilterPropertyParameters edge_filter)#

Set Edge Filter with EdgeFilterPropertyParameters value.

Filter results based on size, contrast threshold, and sensitivity threshold

Parameters:

edge_filter – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

CaliperAnnularEdgeParameters the reference of this object.

EdgeFilterPropertyParameters &get_edge_filter()#

Get mutable reference of Edge Filter.

Filter results based on size, contrast threshold, and sensitivity threshold

Returns:

CaliperAnnularEdgeParameters& the mutable reference of the group.

int get_max_result_num() const#

Get Max Result Num.

Maximum number of results

Returns:

int Max Result Num

CaliperAnnularEdgeParameters &set_max_result_num(int max_result_num)#

Set Max Result Num with int value.

Maximum number of results

Parameters:

max_result_num – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

CaliperAnnularEdgeParameters the reference of this object.

Measure Mode Parameters#

enum visionflow::param::EdgePolarityMode#

Values:

enumerator kDarkToLight = 0#
enumerator kLightToDark = 1#
enumerator kBoth = 2#
enum visionflow::param::EdgeOrderMode#

Values:

enumerator kBestScore = 0#
enumerator kFirstEdge = 1#
enumerator kLastEdge = 2#

Measure Caliper Score Func Parameters#

class ScoreFuncParameters : public visionflow::param::ISchemable#

ScoreFuncParameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

bool get_enable() const#

Get Enable.

Enable this parameter group.

See also

set_enable()

Returns:

bool Enable

ScoreFuncParameters &set_enable(bool enable)#

Set Enable with bool value.

Enable this parameter group.

See also

get_enable()

Parameters:

enable – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ScoreFuncParameters the reference of this object.

double get_x0() const#

Get X0-Value.

Values between x0 and x1 are mapped to a score that is between y0 and y1, while contrast values on the other side of x0 are mapped to a score of y0

See also

set_x0()

Returns:

double X0-Value

ScoreFuncParameters &set_x0(double x0)#

Set X0-Value with double value.

Values between x0 and x1 are mapped to a score that is between y0 and y1, while contrast values on the other side of x0 are mapped to a score of y0

See also

get_x0()

Parameters:

x0 – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ScoreFuncParameters the reference of this object.

double get_x1() const#

Get X1-Value.

Value of x1 must fall between the values of xc and x0. Contrast values between x0 and x1 are mapped to a score that is between y0 and y1, while contrast values between xc and x1 are mapped to a score of y1

See also

set_x1()

Returns:

double X1-Value

ScoreFuncParameters &set_x1(double x1)#

Set X1-Value with double value.

Value of x1 must fall between the values of xc and x0. Contrast values between x0 and x1 are mapped to a score that is between y0 and y1, while contrast values between xc and x1 are mapped to a score of y1

See also

get_x1()

Parameters:

x1 – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ScoreFuncParameters the reference of this object.

double get_xc() const#

Get Xc-Value.

Values between xc and x1 are mapped to a score of y1, while contrast values on the other side of xc are mapped to a score of zero

See also

set_xc()

Returns:

double Xc-Value

ScoreFuncParameters &set_xc(double xc)#

Set Xc-Value with double value.

Values between xc and x1 are mapped to a score of y1, while contrast values on the other side of xc are mapped to a score of zero

See also

get_xc()

Parameters:

xc – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ScoreFuncParameters the reference of this object.

double get_y0() const#

Get Y0-Value.

The maximum score that will be produced by this scoring function. This unitless value is in the range of 0.0 through 1.0, and must be greater than the y1 value

See also

set_y0()

Returns:

double Y0-Value

ScoreFuncParameters &set_y0(double y0)#

Set Y0-Value with double value.

The maximum score that will be produced by this scoring function. This unitless value is in the range of 0.0 through 1.0, and must be greater than the y1 value

See also

get_y0()

Parameters:

y0 – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ScoreFuncParameters the reference of this object.

double get_y1() const#

Get Y1-Value.

The minimum non-zero score that will be produced by this scoring function. This unitless value is in the range of 0.0 through 1.0, and must be less than the y0 value

See also

set_y1()

Returns:

double Y1-Value

ScoreFuncParameters &set_y1(double y1)#

Set Y1-Value with double value.

The minimum non-zero score that will be produced by this scoring function. This unitless value is in the range of 0.0 through 1.0, and must be less than the y0 value

See also

get_y1()

Parameters:

y1 – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ScoreFuncParameters the reference of this object.

class CaliperSingleEdgeFuncParameters : public visionflow::param::ISchemable#

CaliperSingleEdgeFuncParameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

const ScoreFuncParameters &get_contrast() const#

Get Contrast Func.

A function for scoring based on contrast

See also

set_contrast()

Returns:

const ScoreFuncParameters & Contrast Func

CaliperSingleEdgeFuncParameters &set_contrast(ScoreFuncParameters contrast)#

Set Contrast Func with ScoreFuncParameters value.

A function for scoring based on contrast

See also

get_contrast()

Parameters:

contrast – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

CaliperSingleEdgeFuncParameters the reference of this object.

ScoreFuncParameters &get_contrast()#

Get mutable reference of Contrast Func.

A function for scoring based on contrast

Returns:

CaliperSingleEdgeFuncParameters& the mutable reference of the group.

const ScoreFuncParameters &get_center_distance() const#

Get Center Distance Func.

A function for scoring based on distance to the center

Returns:

const ScoreFuncParameters & Center Distance Func

CaliperSingleEdgeFuncParameters &set_center_distance(ScoreFuncParameters center_distance)#

Set Center Distance Func with ScoreFuncParameters value.

A function for scoring based on distance to the center

Parameters:

center_distance – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

CaliperSingleEdgeFuncParameters the reference of this object.

ScoreFuncParameters &get_center_distance()#

Get mutable reference of Center Distance Func.

A function for scoring based on distance to the center

Returns:

CaliperSingleEdgeFuncParameters& the mutable reference of the group.

const ScoreFuncParameters &get_center_offset() const#

Get Center Offset Func.

A function for scoring based on the offset relative to the center

Returns:

const ScoreFuncParameters & Center Offset Func

CaliperSingleEdgeFuncParameters &set_center_offset(ScoreFuncParameters center_offset)#

Set Center Offset Func with ScoreFuncParameters value.

A function for scoring based on the offset relative to the center

Parameters:

center_offset – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

CaliperSingleEdgeFuncParameters the reference of this object.

ScoreFuncParameters &get_center_offset()#

Get mutable reference of Center Offset Func.

A function for scoring based on the offset relative to the center

Returns:

CaliperSingleEdgeFuncParameters& the mutable reference of the group.

const ScoreFuncParameters &get_polarity() const#

Get Polarity Func.

A function for scoring based on polarity

See also

set_polarity()

Returns:

const ScoreFuncParameters & Polarity Func

CaliperSingleEdgeFuncParameters &set_polarity(ScoreFuncParameters polarity)#

Set Polarity Func with ScoreFuncParameters value.

A function for scoring based on polarity

See also

get_polarity()

Parameters:

polarity – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

CaliperSingleEdgeFuncParameters the reference of this object.

ScoreFuncParameters &get_polarity()#

Get mutable reference of Polarity Func.

A function for scoring based on polarity

Returns:

CaliperSingleEdgeFuncParameters& the mutable reference of the group.

const ScoreFuncParameters &get_light_polarity() const#

Get Light Polarity Func.

A function for rating based on lightness polarity

Returns:

const ScoreFuncParameters & Light Polarity Func

CaliperSingleEdgeFuncParameters &set_light_polarity(ScoreFuncParameters light_polarity)#

Set Light Polarity Func with ScoreFuncParameters value.

A function for rating based on lightness polarity

Parameters:

light_polarity – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

CaliperSingleEdgeFuncParameters the reference of this object.

ScoreFuncParameters &get_light_polarity()#

Get mutable reference of Light Polarity Func.

A function for rating based on lightness polarity

Returns:

CaliperSingleEdgeFuncParameters& the mutable reference of the group.

const ScoreFuncParameters &get_dark_polarity() const#

Get Dark Polarity Func.

A function for rating based on darkness polarity

Returns:

const ScoreFuncParameters & Dark Polarity Func

CaliperSingleEdgeFuncParameters &set_dark_polarity(ScoreFuncParameters dark_polarity)#

Set Dark Polarity Func with ScoreFuncParameters value.

A function for rating based on darkness polarity

Parameters:

dark_polarity – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

CaliperSingleEdgeFuncParameters the reference of this object.

ScoreFuncParameters &get_dark_polarity()#

Get mutable reference of Dark Polarity Func.

A function for rating based on darkness polarity

Returns:

CaliperSingleEdgeFuncParameters& the mutable reference of the group.

class WidthDiffNormFuncParameters : public visionflow::param::ISchemable#

WidthDiffNormFuncParameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

bool get_enable() const#

Get Enable.

Enable this parameter group.

See also

set_enable()

Returns:

bool Enable

WidthDiffNormFuncParameters &set_enable(bool enable)#

Set Enable with bool value.

Enable this parameter group.

See also

get_enable()

Parameters:

enable – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

WidthDiffNormFuncParameters the reference of this object.

double get_x0() const#

Get X0-Value.

Values between x0 and x1 are mapped to a score that is between y0 and y1, while contrast values on the other side of x0 are mapped to a score of y0

See also

set_x0()

Returns:

double X0-Value

WidthDiffNormFuncParameters &set_x0(double x0)#

Set X0-Value with double value.

Values between x0 and x1 are mapped to a score that is between y0 and y1, while contrast values on the other side of x0 are mapped to a score of y0

See also

get_x0()

Parameters:

x0 – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

WidthDiffNormFuncParameters the reference of this object.

double get_x1() const#

Get X1-Value.

Value of x1 must fall between the values of xc and x0. Contrast values between x0 and x1 are mapped to a score that is between y0 and y1, while contrast values between xc and x1 are mapped to a score of y1

See also

set_x1()

Returns:

double X1-Value

WidthDiffNormFuncParameters &set_x1(double x1)#

Set X1-Value with double value.

Value of x1 must fall between the values of xc and x0. Contrast values between x0 and x1 are mapped to a score that is between y0 and y1, while contrast values between xc and x1 are mapped to a score of y1

See also

get_x1()

Parameters:

x1 – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

WidthDiffNormFuncParameters the reference of this object.

double get_xc() const#

Get Xc-Value.

Values between xc and x1 are mapped to a score of y1, while contrast values on the other side of xc are mapped to a score of zero

See also

set_xc()

Returns:

double Xc-Value

WidthDiffNormFuncParameters &set_xc(double xc)#

Set Xc-Value with double value.

Values between xc and x1 are mapped to a score of y1, while contrast values on the other side of xc are mapped to a score of zero

See also

get_xc()

Parameters:

xc – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

WidthDiffNormFuncParameters the reference of this object.

double get_y0() const#

Get Y0-Value.

The maximum score that will be produced by this scoring function. This unitless value is in the range of 0.0 through 1.0, and must be greater than the y1 value

See also

set_y0()

Returns:

double Y0-Value

WidthDiffNormFuncParameters &set_y0(double y0)#

Set Y0-Value with double value.

The maximum score that will be produced by this scoring function. This unitless value is in the range of 0.0 through 1.0, and must be greater than the y1 value

See also

get_y0()

Parameters:

y0 – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

WidthDiffNormFuncParameters the reference of this object.

double get_y1() const#

Get Y1-Value.

The minimum non-zero score that will be produced by this scoring function. This unitless value is in the range of 0.0 through 1.0, and must be less than the y0 value

See also

set_y1()

Returns:

double Y1-Value

WidthDiffNormFuncParameters &set_y1(double y1)#

Set Y1-Value with double value.

The minimum non-zero score that will be produced by this scoring function. This unitless value is in the range of 0.0 through 1.0, and must be less than the y0 value

See also

get_y1()

Parameters:

y1 – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

WidthDiffNormFuncParameters the reference of this object.

double get_x0h() const#

Get X0h-Value.

Values between x0h and x1h are mapped to a score that is between y0h and y1h, while contrast values on the other side of x0h are mapped to a score of y0h

See also

set_x0h()

Returns:

double X0h-Value

WidthDiffNormFuncParameters &set_x0h(double x0h)#

Set X0h-Value with double value.

Values between x0h and x1h are mapped to a score that is between y0h and y1h, while contrast values on the other side of x0h are mapped to a score of y0h

See also

get_x0h()

Parameters:

x0h – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

WidthDiffNormFuncParameters the reference of this object.

double get_x1h() const#

Get X1h-Value.

Value of x1h must fall between the values of xch and x0h. Contrast values between x0h and x1h are mapped to a score that is between y0h and y1h, while contrast values between xch and x1h are mapped to a score of y1h

See also

set_x1h()

Returns:

double X1h-Value

WidthDiffNormFuncParameters &set_x1h(double x1h)#

Set X1h-Value with double value.

Value of x1h must fall between the values of xch and x0h. Contrast values between x0h and x1h are mapped to a score that is between y0h and y1h, while contrast values between xch and x1h are mapped to a score of y1h

See also

get_x1h()

Parameters:

x1h – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

WidthDiffNormFuncParameters the reference of this object.

double get_xch() const#

Get Xch-Value.

Values between xch and x1h are mapped to a score of y1h, while contrast values on the other side of xch are mapped to a score of zero

See also

set_xch()

Returns:

double Xch-Value

WidthDiffNormFuncParameters &set_xch(double xch)#

Set Xch-Value with double value.

Values between xch and x1h are mapped to a score of y1h, while contrast values on the other side of xch are mapped to a score of zero

See also

get_xch()

Parameters:

xch – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

WidthDiffNormFuncParameters the reference of this object.

double get_y0h() const#

Get Y0h-Value.

The maximum score that will be produced by this scoring function. This unitless value is in the range of 0.0 through 1.0, and must be greater than the y1h value

See also

set_y0h()

Returns:

double Y0h-Value

WidthDiffNormFuncParameters &set_y0h(double y0h)#

Set Y0h-Value with double value.

The maximum score that will be produced by this scoring function. This unitless value is in the range of 0.0 through 1.0, and must be greater than the y1h value

See also

get_y0h()

Parameters:

y0h – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

WidthDiffNormFuncParameters the reference of this object.

double get_y1h() const#

Get Y1h-Value.

The minimum non-zero score that will be produced by this scoring function. This unitless value is in the range of 0.0 through 1.0, and must be less than the y0h value

See also

set_y1h()

Returns:

double Y1h-Value

WidthDiffNormFuncParameters &set_y1h(double y1h)#

Set Y1h-Value with double value.

The minimum non-zero score that will be produced by this scoring function. This unitless value is in the range of 0.0 through 1.0, and must be less than the y0h value

See also

get_y1h()

Parameters:

y1h – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

WidthDiffNormFuncParameters the reference of this object.

class CaliperDualEdgeFuncParameters : public visionflow::param::ISchemable#

CaliperDualEdgeFuncParameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

const ScoreFuncParameters &get_contrast() const#

Get Contrast Func.

A function for scoring based on contrast

See also

set_contrast()

Returns:

const ScoreFuncParameters & Contrast Func

CaliperDualEdgeFuncParameters &set_contrast(ScoreFuncParameters contrast)#

Set Contrast Func with ScoreFuncParameters value.

A function for scoring based on contrast

See also

get_contrast()

Parameters:

contrast – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

CaliperDualEdgeFuncParameters the reference of this object.

ScoreFuncParameters &get_contrast()#

Get mutable reference of Contrast Func.

A function for scoring based on contrast

Returns:

CaliperDualEdgeFuncParameters& the mutable reference of the group.

const ScoreFuncParameters &get_center_distance() const#

Get Center Distance Func.

A function for scoring based on distance to the center

Returns:

const ScoreFuncParameters & Center Distance Func

CaliperDualEdgeFuncParameters &set_center_distance(ScoreFuncParameters center_distance)#

Set Center Distance Func with ScoreFuncParameters value.

A function for scoring based on distance to the center

Parameters:

center_distance – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

CaliperDualEdgeFuncParameters the reference of this object.

ScoreFuncParameters &get_center_distance()#

Get mutable reference of Center Distance Func.

A function for scoring based on distance to the center

Returns:

CaliperDualEdgeFuncParameters& the mutable reference of the group.

const ScoreFuncParameters &get_center_offset() const#

Get Center Offset Func.

A function for scoring based on the offset relative to the center

Returns:

const ScoreFuncParameters & Center Offset Func

CaliperDualEdgeFuncParameters &set_center_offset(ScoreFuncParameters center_offset)#

Set Center Offset Func with ScoreFuncParameters value.

A function for scoring based on the offset relative to the center

Parameters:

center_offset – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

CaliperDualEdgeFuncParameters the reference of this object.

ScoreFuncParameters &get_center_offset()#

Get mutable reference of Center Offset Func.

A function for scoring based on the offset relative to the center

Returns:

CaliperDualEdgeFuncParameters& the mutable reference of the group.

const ScoreFuncParameters &get_center_distance_norm() const#

Get Center Distance Norm Func.

A function for scoring based on the normalized center distance.The normalized center distance represents the absolute value of the distance between the detected edge position and the center position of the caliper, as well as the width of the edge

Returns:

const ScoreFuncParameters & Center Distance Norm Func

CaliperDualEdgeFuncParameters &set_center_distance_norm(ScoreFuncParameters center_distance_norm)#

Set Center Distance Norm Func with ScoreFuncParameters value.

A function for scoring based on the normalized center distance.The normalized center distance represents the absolute value of the distance between the detected edge position and the center position of the caliper, as well as the width of the edge

Parameters:

center_distance_norm – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

CaliperDualEdgeFuncParameters the reference of this object.

ScoreFuncParameters &get_center_distance_norm()#

Get mutable reference of Center Distance Norm Func.

A function for scoring based on the normalized center distance.The normalized center distance represents the absolute value of the distance between the detected edge position and the center position of the caliper, as well as the width of the edge

Returns:

CaliperDualEdgeFuncParameters& the mutable reference of the group.

const ScoreFuncParameters &get_center_offset_norm() const#

Get Center Offset Norm Func.

A function for scoring based on the normalized center offset.The normalized center offset represents the sum of the distance between the detected edge position and the center position of the caliper and the edge width

Returns:

const ScoreFuncParameters & Center Offset Norm Func

CaliperDualEdgeFuncParameters &set_center_offset_norm(ScoreFuncParameters center_offset_norm)#

Set Center Offset Norm Func with ScoreFuncParameters value.

A function for scoring based on the normalized center offset.The normalized center offset represents the sum of the distance between the detected edge position and the center position of the caliper and the edge width

Parameters:

center_offset_norm – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

CaliperDualEdgeFuncParameters the reference of this object.

ScoreFuncParameters &get_center_offset_norm()#

Get mutable reference of Center Offset Norm Func.

A function for scoring based on the normalized center offset.The normalized center offset represents the sum of the distance between the detected edge position and the center position of the caliper and the edge width

Returns:

CaliperDualEdgeFuncParameters& the mutable reference of the group.

const ScoreFuncParameters &get_width_norm() const#

Get Width Norm Func.

A function for scoring based on the normalized width.The normalized width represents the ratio of the detected edge width to the user set width

See also

set_width_norm()

Returns:

const ScoreFuncParameters & Width Norm Func

CaliperDualEdgeFuncParameters &set_width_norm(ScoreFuncParameters width_norm)#

Set Width Norm Func with ScoreFuncParameters value.

A function for scoring based on the normalized width.The normalized width represents the ratio of the detected edge width to the user set width

See also

get_width_norm()

Parameters:

width_norm – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

CaliperDualEdgeFuncParameters the reference of this object.

ScoreFuncParameters &get_width_norm()#

Get mutable reference of Width Norm Func.

A function for scoring based on the normalized width.The normalized width represents the ratio of the detected edge width to the user set width

Returns:

CaliperDualEdgeFuncParameters& the mutable reference of the group.

const WidthDiffNormFuncParameters &get_width_diff_norm() const#

Get Width Diff Norm Func.

A function for scoring based on the normalized width difference.The normalized width difference represents the sum of the difference between the detected edge width and the user set width, and the user set width

Returns:

const WidthDiffNormFuncParameters & Width Diff Norm Func

CaliperDualEdgeFuncParameters &set_width_diff_norm(WidthDiffNormFuncParameters width_diff_norm)#

Set Width Diff Norm Func with WidthDiffNormFuncParameters value.

A function for scoring based on the normalized width difference.The normalized width difference represents the sum of the difference between the detected edge width and the user set width, and the user set width

Parameters:

width_diff_norm – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

CaliperDualEdgeFuncParameters the reference of this object.

WidthDiffNormFuncParameters &get_width_diff_norm()#

Get mutable reference of Width Diff Norm Func.

A function for scoring based on the normalized width difference.The normalized width difference represents the sum of the difference between the detected edge width and the user set width, and the user set width

Returns:

CaliperDualEdgeFuncParameters& the mutable reference of the group.

const ScoreFuncParameters &get_width_diff_norm_abs() const#

Get Width Diff Norm Abs Func.

A function for scoring based on the absolute normalized width difference.The absolute normalized width difference represents the absolute value of the difference between the detected edge width and the user set width, and the absolute value of the user set width

Returns:

const ScoreFuncParameters & Width Diff Norm Abs Func

CaliperDualEdgeFuncParameters &set_width_diff_norm_abs(ScoreFuncParameters width_diff_norm_abs)#

Set Width Diff Norm Abs Func with ScoreFuncParameters value.

A function for scoring based on the absolute normalized width difference.The absolute normalized width difference represents the absolute value of the difference between the detected edge width and the user set width, and the absolute value of the user set width

Parameters:

width_diff_norm_abs – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

CaliperDualEdgeFuncParameters the reference of this object.

ScoreFuncParameters &get_width_diff_norm_abs()#

Get mutable reference of Width Diff Norm Abs Func.

A function for scoring based on the absolute normalized width difference.The absolute normalized width difference represents the absolute value of the difference between the detected edge width and the user set width, and the absolute value of the user set width

Returns:

CaliperDualEdgeFuncParameters& the mutable reference of the group.

bool get_enable_straddle() const#

Get Enable Straddle Func.

Enable the function for scoring based on whether it straddles centers. If the product of the center deviation of two detection edges is greater than or equal to 0, the score is set to 0. If it is greater than or equal to 0, the score is set to 1

Returns:

bool Enable Straddle Func

CaliperDualEdgeFuncParameters &set_enable_straddle(bool enable_straddle)#

Set Enable Straddle Func with bool value.

Enable the function for scoring based on whether it straddles centers. If the product of the center deviation of two detection edges is greater than or equal to 0, the score is set to 0. If it is greater than or equal to 0, the score is set to 1

Parameters:

enable_straddle – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

CaliperDualEdgeFuncParameters the reference of this object.

const ScoreFuncParameters &get_average_gray() const#

Get Average Gray Func.

A function for scoring based on average gray.The higher the average grayscale of the edges, the higher the edge score.

Returns:

const ScoreFuncParameters & Average Gray Func

CaliperDualEdgeFuncParameters &set_average_gray(ScoreFuncParameters average_gray)#

Set Average Gray Func with ScoreFuncParameters value.

A function for scoring based on average gray.The higher the average grayscale of the edges, the higher the edge score.

Parameters:

average_gray – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

CaliperDualEdgeFuncParameters the reference of this object.

ScoreFuncParameters &get_average_gray()#

Get mutable reference of Average Gray Func.

A function for scoring based on average gray.The higher the average grayscale of the edges, the higher the edge score.

Returns:

CaliperDualEdgeFuncParameters& the mutable reference of the group.

Measure Caliper Properties Parameters#

class EdgeFilterPropertyParameters : public visionflow::param::ISchemable#

EdgeFilterPropertyParameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

int get_filter_half_size() const#

Get Filter Half Size.

Filter radius, used for denoising

Returns:

int Filter Half Size

EdgeFilterPropertyParameters &set_filter_half_size(int filter_half_size)#

Set Filter Half Size with int value.

Filter radius, used for denoising

Parameters:

filter_half_size – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

EdgeFilterPropertyParameters the reference of this object.

double get_contrast_threshold() const#

Get Contrast Threshold.

Contrast Threshold of edge

Returns:

double Contrast Threshold

EdgeFilterPropertyParameters &set_contrast_threshold(double contrast_threshold)#

Set Contrast Threshold with double value.

Contrast Threshold of edge

Parameters:

contrast_threshold – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

EdgeFilterPropertyParameters the reference of this object.

double get_sensitive_threshold() const#

Get Sensitive Threshold.

Sensitive Threshold of edge

Returns:

double Sensitive Threshold

EdgeFilterPropertyParameters &set_sensitive_threshold(double sensitive_threshold)#

Set Sensitive Threshold with double value.

Sensitive Threshold of edge

Parameters:

sensitive_threshold – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

EdgeFilterPropertyParameters the reference of this object.

Measure Basic Graphics Parameters#

class RotateRectParameters : public visionflow::param::ISchemable#

RotateRectParameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

double get_x() const#

Get X-Value.

X-direction coordinate value of the center of the rotate rect

See also

set_x()

Returns:

double X-Value

RotateRectParameters &set_x(double x)#

Set X-Value with double value.

X-direction coordinate value of the center of the rotate rect

See also

get_x()

Parameters:

x – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

RotateRectParameters the reference of this object.

double get_y() const#

Get Y-Value.

Y-direction coordinate value of the center of the rotate rect

See also

set_y()

Returns:

double Y-Value

RotateRectParameters &set_y(double y)#

Set Y-Value with double value.

Y-direction coordinate value of the center of the rotate rect

See also

get_y()

Parameters:

y – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

RotateRectParameters the reference of this object.

double get_w() const#

Get W-Value.

Width of the rotate rect

See also

set_w()

Returns:

double W-Value

RotateRectParameters &set_w(double w)#

Set W-Value with double value.

Width of the rotate rect

See also

get_w()

Parameters:

w – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

RotateRectParameters the reference of this object.

double get_h() const#

Get H-Value.

Height of the rotate rect

See also

set_h()

Returns:

double H-Value

RotateRectParameters &set_h(double h)#

Set H-Value with double value.

Height of the rotate rect

See also

get_h()

Parameters:

h – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

RotateRectParameters the reference of this object.

double get_angle() const#

Get Angle.

Angle (Degree) of the rotate rect

See also

set_angle()

Returns:

double Angle

RotateRectParameters &set_angle(double angle)#

Set Angle with double value.

Angle (Degree) of the rotate rect

See also

get_angle()

Parameters:

angle – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

RotateRectParameters the reference of this object.

class AnnularSectionParameters : public visionflow::param::ISchemable#

AnnularSectionParameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

double get_x() const#

Get X-Value.

X-coordinate of the center point of the annular section

See also

set_x()

Returns:

double X-Value

AnnularSectionParameters &set_x(double x)#

Set X-Value with double value.

X-coordinate of the center point of the annular section

See also

get_x()

Parameters:

x – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

AnnularSectionParameters the reference of this object.

double get_y() const#

Get Y-Value.

Y-coordinate of the center point of the annular section

See also

set_y()

Returns:

double Y-Value

AnnularSectionParameters &set_y(double y)#

Set Y-Value with double value.

Y-coordinate of the center point of the annular section

See also

get_y()

Parameters:

y – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

AnnularSectionParameters the reference of this object.

double get_start_radius() const#

Get Start Radius.

Start radius of the annular section

Returns:

double Start Radius

AnnularSectionParameters &set_start_radius(double start_radius)#

Set Start Radius with double value.

Start radius of the annular section

Parameters:

start_radius – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

AnnularSectionParameters the reference of this object.

double get_end_radius() const#

Get End Radius.

End radius of the annular section

See also

set_end_radius()

Returns:

double End Radius

AnnularSectionParameters &set_end_radius(double end_radius)#

Set End Radius with double value.

End radius of the annular section

See also

get_end_radius()

Parameters:

end_radius – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

AnnularSectionParameters the reference of this object.

double get_start_angle() const#

Get Start Angle.

Start angle (Degree) of the annular section

Returns:

double Start Angle

AnnularSectionParameters &set_start_angle(double start_angle)#

Set Start Angle with double value.

Start angle (Degree) of the annular section

Parameters:

start_angle – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

AnnularSectionParameters the reference of this object.

double get_end_angle() const#

Get End Angle.

End angle (Degree) of the annular section

See also

set_end_angle()

Returns:

double End Angle

AnnularSectionParameters &set_end_angle(double end_angle)#

Set End Angle with double value.

End angle (Degree) of the annular section

See also

get_end_angle()

Parameters:

end_angle – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

AnnularSectionParameters the reference of this object.

CameraCalibrationEvaluation Parameters:#

class CameraCalibrationImageFeaturePoints#

camera calibration feature points contain image coordinate points, world coordinate points, and remapped coordinate points.It is used to show whether the results of the camera calibration training are accurate or not.

Public Functions

CameraCalibrationImageFeaturePoints &set_image_points(std::vector<geometry::Point2f> image_points)#

The position of the markers on the image. This position is the one detected from the image without any processing.

Parameters:

image_points – The position of the markers on the image.

Returns:

CameraCalibrationImageFeaturePoints& the reference of this object.

const std::vector<geometry::Point2f> &get_image_points() const#

See also

set_image_points

CameraCalibrationImageFeaturePoints &set_world_points(std::vector<geometry::Point2f> world_points)#

The positions of the markers on the image correspond to the positions of the world coordinates. The coordinates are mapped once.

Parameters:

world_points – world points to set.Z -axis coordinates remain at 0.*

Returns:

CameraCalibrationImageFeaturePoints& the reference of this object.

const std::vector<geometry::Point2f> &get_world_points() const#

See also

set_world_points

CameraCalibrationImageFeaturePoints &set_reprojection_points(std::vector<geometry::Point2f> reprojection_points)#

The world coordinates are mapped to locations on the image. The coordinates are mapped twice.

Parameters:

reprojection_points – re_projection points to set.

Returns:

CameraCalibrationImageFeaturePoints& the reference of this object.

const std::vector<geometry::Point2f> &get_reprojection_points() const#

See also

set_world_points

class CameraCalibrationEvaluation : public visionflow::param::IParameter#

Evaluation data includes root_mean_square and feature points. root_mean_square is the calibration error evaluation score; the smaller root_mean_square (root_mean_square>=0), the more accurate the calibration. camera calibration feature points contain image coordinate points, world coordinate points, and remapped coordinate points.It is used to show whether the results of the camera calibration training are accurate or not.

Public Functions

CameraCalibrationEvaluation &set_images_feature_points(std::vector<CameraCalibrationImageFeaturePoints> images_feature_points)#

Set feature points for all view image.

Parameters:

images_feature_points – feature points of all train images.

Returns:

CameraCalibrationEvaluation& the reference of this object.

const std::vector<CameraCalibrationImageFeaturePoints> &get_images_feature_points() const#

void clear_images_feature_points()#

clear feature points of all view image.

int images_feature_points_size() const#

The number of images with feature points is recorded.

CameraCalibrationEvaluation &add_image_feature_points(CameraCalibrationImageFeaturePoints image_feature_points)#

add the feature points of an image.

Parameters:

image_feature_points – feature points of a image.

Returns:

CameraCalibrationEvaluation& the reference of this object.

const CameraCalibrationImageFeaturePoints &get_image_feature_points(size_t index) const#

Get the already set feature points according to the image index.

Parameters:

index – Image index.

Returns:

The feature point that is got.

CameraCalibrationEvaluation &set_root_mean_square(double root_mean_square)#

Set the root_mean_square.root_mean_square is the calibration error evaluation score; the smaller root_mean_square (root_mean_square>=0), the more accurate the calibration.

Parameters:

root_mean_square – Set the root_mean_square.

Returns:

CameraCalibrationEvaluation& the reference of this object.

double get_root_mean_square() const#

See also

set_rms();

CameraCalibrationEvaluation &set_calibration_messages(std::string calibration_messages)#

 @brief Set the massage.
 @param calibration_messages Set the massage. The format of the camera
calibration information is[{“type”:” “,”level”:” “,”massage”:” “}]. type is the information type.level is the Severity level of information. massage is the detail.An example is as follows. [ { The reference image cannot be found, it is possible that the reference index is out of range, or the reference image feature point detection fails. “type”:”ReferenceIndexNotFound”, “level”:”Error”, “massage”:{“reference_index”:10,”images_number”:5} }, { The number of image feature points is less than the minimum value. “type”:”ImagePointsNotEnough”, “level”:”Error”, “massage”:{“image_id”:10,”minimum_number”:5,”found_number”,”4”} }, { The image did not find all feature points. “type”:”ImagePointsNotFoundAll”, “level”:”Error”, “massage”:{“image_id”:10,”expected_number”:5,”found_number”,”4”} }, { The image did not find the calibration board, or any feature points. “type”:”BoardNotFound”, “level”:”Error”, “massage”:{“image_id”:10} }, { All images are not available “type”:”NoAvailableImages”, “level”:”Error”, “massage”:{} } ]

Returns:

CameraCalibrationEvaluation& the reference of this object.

const std::string &get_calibration_messages() const#

CameraCalibrationPixelScale Parameters:#

class CameraCalibrationPixelScale : public visionflow::param::SchemableParameter#

CameraCalibrationPixelScale Parameter class generated by jinja2 automatically.

Camera calibrate Pixel Scale

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

double get_pixel_scale() const#

Get Pixel Scale.

Pixel Scale

Returns:

double Pixel Scale

CameraCalibrationPixelScale &set_pixel_scale(double pixel_scale)#

Set Pixel Scale with double value.

Pixel Scale

Parameters:

pixel_scale – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

CameraCalibrationPixelScale the reference of this object.

EL OCR Parameters#

class ELOCRInferParameters : public visionflow::param::SchemableParameter#

ELOCRInferParameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

double get_threshold() const#

Get Confidence Threshold.

Greater than this threshold will be determined as a target.

See also

set_threshold()

Returns:

double Confidence Threshold

ELOCRInferParameters &set_threshold(double threshold)#

Set Confidence Threshold with double value.

Greater than this threshold will be determined as a target.

See also

get_threshold()

Parameters:

threshold – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ELOCRInferParameters the reference of this object.

double get_density() const#

Get Search Density.

Filter out duplicate results using NMS. A higher value will retain fewer results.

See also

set_density()

Returns:

double Search Density

ELOCRInferParameters &set_density(double density)#

Set Search Density with double value.

Filter out duplicate results using NMS. A higher value will retain fewer results.

See also

get_density()

Parameters:

density – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ELOCRInferParameters the reference of this object.

class ELOCRTrainingParameters : public visionflow::param::SchemableParameter#

ELOCRTrainingParameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

double get_target_char_width() const#

Get Target Character Width.

The target character width in data.

Returns:

double Target Character Width

ELOCRTrainingParameters &set_target_char_width(double target_char_width)#

Set Target Character Width with double value.

The target character width in data.

Parameters:

target_char_width – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ELOCRTrainingParameters the reference of this object.

double get_target_char_height() const#

Get Target Character Height.

The target character height in data.

Returns:

double Target Character Height

ELOCRTrainingParameters &set_target_char_height(double target_char_height)#

Set Target Character Height with double value.

The target character height in data.

Parameters:

target_char_height – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ELOCRTrainingParameters the reference of this object.

int get_epoch() const#

Get Epochs.

Number of iterations to train. 1 Epoch means all selected images will be trained for 1 time.

See also

set_epoch()

Returns:

int Epochs

ELOCRTrainingParameters &set_epoch(int epoch)#

Set Epochs with int value.

Number of iterations to train. 1 Epoch means all selected images will be trained for 1 time.

See also

get_epoch()

Parameters:

epoch – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ELOCRTrainingParameters the reference of this object.

EL Unsupervised Segmentation Parameters#

class ELUnsuperSegmentationTrainingParameters : public visionflow::param::SchemableParameter#

ELUnsuperSegmentationTrainingParameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

int get_min_defect_size() const#

Get Minimum Defect Size.

Minimum defect size in pixels.

Returns:

int Minimum Defect Size

ELUnsuperSegmentationTrainingParameters &set_min_defect_size(int min_defect_size)#

Set Minimum Defect Size with int value.

Minimum defect size in pixels.

Parameters:

min_defect_size – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ELUnsuperSegmentationTrainingParameters the reference of this object.

int get_view_shift_range() const#

Get View Shift Range.

The range of movement of the overall content of the view that may be caused by imprecise positioning, etc. We look for detection targets within the range of possible movement of the view. The larger the possible movement of the view, the larger the range the algorithm needs to find and the slower the inference will be.

Returns:

int View Shift Range

ELUnsuperSegmentationTrainingParameters &set_view_shift_range(int view_shift_range)#

Set View Shift Range with int value.

The range of movement of the overall content of the view that may be caused by imprecise positioning, etc. We look for detection targets within the range of possible movement of the view. The larger the possible movement of the view, the larger the range the algorithm needs to find and the slower the inference will be.

Parameters:

view_shift_range – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ELUnsuperSegmentationTrainingParameters the reference of this object.

double get_core_set_percentage() const#

Get Core Set Percentage.

The ratio of the reserved represent vectors. The lower the ratio, the faster the inference, but the less accurate the result of the inference.

Returns:

double Core Set Percentage

ELUnsuperSegmentationTrainingParameters &set_core_set_percentage(double core_set_percentage)#

Set Core Set Percentage with double value.

The ratio of the reserved represent vectors. The lower the ratio, the faster the inference, but the less accurate the result of the inference.

Parameters:

core_set_percentage – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ELUnsuperSegmentationTrainingParameters the reference of this object.

class ELUnsuperSegmentationInferParameters : public visionflow::param::SchemableParameter#

ELUnsuperSegmentationInferParameters Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

double get_distance_scale() const#

Get Distance Zoom Scale.

Scale factor for feature distance. Setting this value to a suitable value makes it easier to adjust the pixel filtering parameters.

Returns:

double Distance Zoom Scale

ELUnsuperSegmentationInferParameters &set_distance_scale(double distance_scale)#

Set Distance Zoom Scale with double value.

Scale factor for feature distance. Setting this value to a suitable value makes it easier to adjust the pixel filtering parameters.

Parameters:

distance_scale – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ELUnsuperSegmentationInferParameters the reference of this object.

Gauge Tool Parameters#

class ScriptPipeline#

Internal class for script pipeline.

Public Functions

ScriptPipeline &set_pre_script(std::string pre_script)#

Set the python pre-script content. The pre-script will be executed before the pipeline, you can define some functions or global variables in the pre-script.

Parameters:

pre_script – The pre-script content.

Returns:

ScriptPipeline& The solving pipeline object.

const std::string &get_pre_script() const#

Get the pre-script object content.

Returns:

const std::string& The pre-script content.

ScriptPipeline &add_item(std::string name, std::string function)#

Add a new solving item with name and script method.

Parameters:
  • name – The solving item name, which can be changed with rename_item. Note that the name should not be empty.

  • function – The solving script. Note that the function should not be empty.

Throws:
Returns:

ScriptPipeline& The solving pipeline object.

void rename_item(const std::string &old_name, const std::string &new_name)#

Rename a solving item with new name.

It will also rename all items that depend on this item.

Parameters:
  • old_name – The old solving item name.

  • new_name – The new solving item name. Note that the name should not be empty.

Throws:
bool remove_item(const std::string &name, bool auto_remove_used_by = true)#

Remove a solving item with name.

Parameters:
  • name – The name of the solving item to be removed.

  • auto_remove_used_by – Determines whether to automatically remove items that depend on this item. If set to true, all dependent items will be recursively removed. If set to false, it will check if ther are any items using this item. If there are, it will output error messages and return false. The default setting is true.

Returns:

bool True if the item is removed successfully. False if the item does not exist or if there are any items using this item.

bool contains_item(const std::string &name) const#

Check if a solving item exists.

Parameters:

name – The name of the solving item.

Returns:

bool True if the solving item exists. False otherwise.

std::vector<std::string> items(bool with_topo_sort = false) const#

List the names of all solving items.

Parameters:

with_topo_sort – Specifies whether to sort the items in topological order. If set to true, the items will be sorted accordingly. If set to false, the items will be sorted in lexicographical order. The default setting is false.

Returns:

std::vector<std::string> The names of all solving items.

std::vector<std::string> deps_on(const std::string &item_name, bool with_indirect = false) const#

List the dependencies of a solving item.

Results are sorted in lexicographical order, excluding the item itself.

Parameters:
  • item_name – The name of the solving item.

  • with_indirect – If true, includes the indirect dependencies. Default is false.

Throws:

excepts::DataNotFound – If an solving item with the name does not exist.

Returns:

std::vector<std::string> A vector of strings containing the names of the dependencies.

std::vector<std::string> used_by(const std::string &item_name, bool with_indirect = false) const#

List the items that use a given solving item.

Results are sorted in lexicographical order, excluding the item itself.

Parameters:
  • item_name – The name of the solving item.

  • with_indirect – If true, includes indirect usages. Default is false.

Throws:

excepts::DataNotFound – If an solving item with the name does not exist.

Returns:

std::vector<std::string> A vector of strings containing the names of the items that use the given item.

ScriptPipeline &set_arg(const std::string &item_name, const std::string &arg_name, const std::string &arg_value, const std::string &ref_item = {})#

Sets an argument for a given item.

When the argument value is empty, it will attempt to add a reference tag. Repeated calls will overwrite the existing content.

Parameters:
  • item_name – The name of the solving item.

  • arg_name – The name of the argument.

  • arg_value – The value of the argument.

  • ref_item – Optional the name of the solving item that the argument refers to. Default is empty.

Throws:
Returns:

ScriptPipeline& A reference to the ScriptPipeline object.

ScriptPipeline &set_condition(const std::string &item_name, const std::string &condition_value, const std::string &ref_item)#

Sets a condition for a given item.

When the condition value is empty, it will attempt to add a reference tag. Repeated calls will overwrite the existing content.

Parameters:
  • item_name – The name of the solving item.

  • condition_value – The value of the condition.

  • ref_item – The name of the solving item that the condition refers to.

Throws:
Returns:

ScriptPipeline& A reference to the ScriptPipeline object.

bool remove_arg(const std::string &item_name, const std::string &arg_name)#

Removes an argument from a given item.

Parameters:
  • item_name – The name of the solving item.

  • arg_name – The name of the argument.

Throws:

excepts::DataNotFound – If an solving item with the name does not exist.

Returns:

bool True if the argument was successfully removed, false otherwise.

const std::string &get_arg_value(const std::string &item_name, const std::string &arg_name) const#

Get the value of an argument for a given item.

Parameters:
  • item_name – The name of the solving item.

  • arg_name – The name of the argument.

Throws:

excepts::DataNotFound – If an solving item with the name does not exist or the argument does not exist.

Returns:

const std::string& The value of the argument.

bool is_variable_arg(const std::string &item_name, const std::string &arg_name) const#

Checks if an argument is variable for a given item.

A variable argument is an argument that refers to another solving item.

Parameters:
  • item_name – The name of the solving item.

  • arg_name – The name of the argument.

Throws:

excepts::DataNotFound – If an solving item with the name does not exist or the argument does not exist.

Returns:

bool True if the argument is variable, false otherwise.

const std::string &get_arg_ref_item(const std::string &item_name, const std::string &arg_name) const#

Get the referenced item of an argument for a given item.

Parameters:
  • item_name – The name of the solving item.

  • arg_name – The name of the argument.

Throws:

excepts::DataNotFound – If an solving item with the name does not exist or the argument does not exist.

Returns:

const std::string& The name of the referenced item.

std::vector<std::string> get_arg_names(const std::string &item_name) const#

Get the names of all arguments for a given item.

Parameters:

item_name – The name of the solving item.

Throws:

excepts::DataNotFound – If an solving item with the name does not exist.

Returns:

std::vector<std::string> A vector of strings containing the names of all arguments in lexicographical order.

bool has_condition(const std::string &item_name) const#

Checks if a given item has a condition.

Parameters:

item_name – The name of the solving item.

Throws:

excepts::DataNotFound – If an solving item with the name does not exist.

Returns:

bool True if the item has a condition, false otherwise.

const std::string &get_condition_value(const std::string &item_name) const#

Get the value of a condition for a given item.

Parameters:

item_name – The name of the solving item.

Throws:

excepts::DataNotFound – If an solving item with the name does not exist.

Returns:

const std::string& The value of the condition.

const std::string &get_condition_ref_item(const std::string &item_name) const#

Get the referenced item of a condition for a given item.

Parameters:

item_name – The name of the solving item.

Throws:

excepts::DataNotFound – If an solving item with the name does not exist.

Returns:

const std::string& The name of the referenced item.

void clear_condition(const std::string &item_name)#

Clears the condition for a given item.

Parameters:

item_name – The name of the solving item.

Throws:

excepts::DataNotFound – If an solving item with the name does not exist.

std::string to_script(const std::string &function_signature) const#

Converts the script pipeline to a python script.

All items will automatically add a check to determine whether the dependency results are empty. Replace reference tags with actual item names. For the expression, an exception will be thrown for missing actual items referred to. Providing extra variables in the expression will not cause an error, but it will result in redundant dependency check and output warning messages.

Warning

The generated script does not guarantee execution success.

Parameters:

function_signature – Python function signature. A function will be generated through the function signature to return all the item results of the script pipeline.

Throws:

excepts::LogicError – If the expression is invalid.

Returns:

std::string A string representation of the python script.

class GaugeParameters : public visionflow::param::IParameter#

Parameter type definition for gauge tool.

Public Functions

GaugeParameters &set_classes_check(bool check)#

Check the output classes names or not. If this option is set to true, the value of the region name item should be one of the output classes, otherwise, an exception will be thrown. If this option is set to false, any string will be accepted as the region name item.

Parameters:

check – The check flag. Default value is true.

Returns:

GaugeParameters& Returns a reference to the current object.

bool get_classes_check() const#

Get the classes check option value.

Returns:

bool Returns the value of the class check option.

GaugeParameters &set_classes(std::vector<std::string> classes)#

Set the output classes names that the output item should be one of.

Parameters:

classes – Output classes names.

Returns:

GaugeParameters& Returns a reference to the current object.

const std::vector<std::string> &get_classes() const#

Get the output classes names set in the parameter.

Returns:

const std::vector<std::string>& Returns a constant reference to the output class names.

GaugeParameters &set_gauge_pipeline(ScriptPipeline pipeline)#

Set the gauge pipeline.

Parameters:

pipeline – The solving pipeline.

Returns:

GaugeParameters& Returns a reference to the current object.

ScriptPipeline &get_gauge_pipeline()#

Get mutable gauge pipeline object.

Returns:

ScriptPipeline& Returns a reference to the mutable gauge pipeline object.

const ScriptPipeline &get_gauge_pipeline() const#

Get the constant reference of the gauge pipeline.

Returns:

const ScriptPipeline& Returns a constant reference to the gauge pipeline.

GaugeParameters &set_out_items(std::vector<std::string> item_names)#

Set the items that need to be saved into the output property. The item is not exist or not created by the gauge pipeline will be ignored.

Parameters:

item_names – the names of the items that need to be saved.

Returns:

GaugeParameters& Returns a reference to the current object.

const std::vector<std::string> &get_out_items() const#

Get the out items that saved into the output property.

Returns:

const std::vector<std::string>& Returns a constant reference to the out items.

GaugeParameters &set_region_name_item(std::string item_name)#

Set the region name item. The region name item should be a string, and must be created by the gauge pipeline, otherwise an error will be thrown by the gauge tool when executing.

The result of the region name item will be set as the region name. If the classes check option is set to true, the result of the region name item should be one of the output classes.

Parameters:

item_name – The name of the region name item, which should be a string object and must be created by the gauge pipeline.

Returns:

GaugeParameters& Returns a reference to the current object.

const std::string &get_region_name_item() const#

Get the item name that the value of which will be set as the region name.

Returns:

const std::string& Returns a constant reference to the name of the region name item.

以下参数项仅为示例#

enum visionflow::param::ExampleAugmentType#

Values:

enumerator kExampleSelect = 0#
enumerator kExampleSecondSelect = 1#
enumerator kExampleOther = 2#
class ExampleAugRotate : public visionflow::param::ISchemable#

ExampleAugRotate Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

bool get_enable() const#

Get Enable.

Enable this parameter group.

See also

set_enable()

Returns:

bool Enable

ExampleAugRotate &set_enable(bool enable)#

Set Enable with bool value.

Enable this parameter group.

See also

get_enable()

Parameters:

enable – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ExampleAugRotate the reference of this object.

double get_rotate_angle() const#

Get Rotate Angle.

Rotate angle

Returns:

double Rotate Angle

ExampleAugRotate &set_rotate_angle(double rotate_angle)#

Set Rotate Angle with double value.

Rotate angle

Parameters:

rotate_angle – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ExampleAugRotate the reference of this object.

bool get_flip_horizontal() const#

Get Flip Horizontal.

Flip horizontal

Returns:

bool Flip Horizontal

ExampleAugRotate &set_flip_horizontal(bool flip_horizontal)#

Set Flip Horizontal with bool value.

Flip horizontal

Parameters:

flip_horizontal – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ExampleAugRotate the reference of this object.

bool get_flip_vertical() const#

Get Flip Vertical.

Flip vertical

Returns:

bool Flip Vertical

ExampleAugRotate &set_flip_vertical(bool flip_vertical)#

Set Flip Vertical with bool value.

Flip vertical

Parameters:

flip_vertical – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ExampleAugRotate the reference of this object.

const ExampleAugShift &get_shift_in_rotate() const#

Get Shift.

Returns:

const ExampleAugShift & Shift

ExampleAugRotate &set_shift_in_rotate(ExampleAugShift shift_in_rotate)#

Set Shift with ExampleAugShift value.

Parameters:

shift_in_rotate – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ExampleAugRotate the reference of this object.

ExampleAugShift &get_shift_in_rotate()#

Get mutable reference of Shift.

Returns:

ExampleAugRotate& the mutable reference of the group.

class ExampleAugShift : public visionflow::param::ISchemable#

ExampleAugShift Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

bool get_enable() const#

Get Enable.

Enable this parameter group.

See also

set_enable()

Returns:

bool Enable

ExampleAugShift &set_enable(bool enable)#

Set Enable with bool value.

Enable this parameter group.

See also

get_enable()

Parameters:

enable – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ExampleAugShift the reference of this object.

double get_shift_width() const#

Get Shift Width.

Shift width

Returns:

double Shift Width

ExampleAugShift &set_shift_width(double shift_width)#

Set Shift Width with double value.

Shift width

Parameters:

shift_width – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ExampleAugShift the reference of this object.

double get_shift_height() const#

Get Shift Height.

Shift height

Returns:

double Shift Height

ExampleAugShift &set_shift_height(double shift_height)#

Set Shift Height with double value.

Shift height

Parameters:

shift_height – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ExampleAugShift the reference of this object.

class ExampleAugments : public visionflow::param::SchemableParameter#

ExampleAugments Parameter class generated by jinja2 automatically.

Public Functions

virtual const std::string &schema_str() const override#

Get the json schema of the class.

Returns:

std::string the json schema string.

virtual const void *schema() const override#

Get nlohmann::json object pointer.

As most user not config the nlohmann::json library, we convert it as void pointer to avoid exposing types from third-party libraries to users.

Note

As this interface is a virtual function, we can not hide it with macro.

Warning

Do not edit return value.

Returns:

void* The nlohmann::json object pointer

bool get_enable() const#

Get Enable.

Enable this parameter group.

See also

set_enable()

Returns:

bool Enable

ExampleAugments &set_enable(bool enable)#

Set Enable with bool value.

Enable this parameter group.

See also

get_enable()

Parameters:

enable – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ExampleAugments the reference of this object.

const ExampleAugmentType &get_example_select() const#

Get Example Select Option.

Example select option

Returns:

const ExampleAugmentType & Example Select Option

ExampleAugments &set_example_select(ExampleAugmentType example_select)#

Set Example Select Option with ExampleAugmentType value.

Example select option

Parameters:

example_select – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ExampleAugments the reference of this object.

const ExampleAugShift &get_shift() const#

Get Shift.

Shift augments

See also

set_shift()

Returns:

const ExampleAugShift & Shift

ExampleAugments &set_shift(ExampleAugShift shift)#

Set Shift with ExampleAugShift value.

Shift augments

See also

get_shift()

Parameters:

shift – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ExampleAugments the reference of this object.

ExampleAugShift &get_shift()#

Get mutable reference of Shift.

Shift augments

Returns:

ExampleAugments& the mutable reference of the group.

const ExampleAugRotate &get_ctm_rotate() const#

Get CustomizeRotate.

Rotate augments

See also

set_ctm_rotate()

Returns:

const ExampleAugRotate & CustomizeRotate

ExampleAugments &set_ctm_rotate(ExampleAugRotate ctm_rotate)#

Set CustomizeRotate with ExampleAugRotate value.

Rotate augments

See also

get_ctm_rotate()

Parameters:

ctm_rotate – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ExampleAugments the reference of this object.

ExampleAugRotate &get_ctm_rotate()#

Get mutable reference of CustomizeRotate.

Rotate augments

Returns:

ExampleAugments& the mutable reference of the group.

const ExampleAugRotate &get_rotate() const#

Get Rotate.

Rotate augments

See also

set_rotate()

Returns:

const ExampleAugRotate & Rotate

ExampleAugments &set_rotate(ExampleAugRotate rotate)#

Set Rotate with ExampleAugRotate value.

Rotate augments

See also

get_rotate()

Parameters:

rotate – the value to set.

Throws:

visionflow::excepts::JsonSchemaValidationError – if validate the value with json schema failed.

Returns:

ExampleAugments the reference of this object.

ExampleAugRotate &get_rotate()#

Get mutable reference of Rotate.

Rotate augments

Returns:

ExampleAugments& the mutable reference of the group.