cv::dnn::TextDetectionModel_EAST Class Reference

This class represents high-level API for text detection DL networks compatible with EAST model. More...

#include <opencv2/dnn/dnn.hpp>

Inheritance diagram for cv::dnn::TextDetectionModel_EAST:

Collaboration diagram for cv::dnn::TextDetectionModel_EAST:

Public Member Functions
	TextDetectionModel_EAST ()
	TextDetectionModel_EAST (const Net &network)
	Create text detection algorithm from deep learning network.
	TextDetectionModel_EAST (CV_WRAP_FILE_PATH const std::string &model, CV_WRAP_FILE_PATH const std::string &config="")
	Create text detection model from network represented in one of the supported formats. An order of model and config arguments does not matter.
float	getConfidenceThreshold () const
	Get the detection confidence threshold.
float	getNMSThreshold () const
	Get the detection confidence threshold.
TextDetectionModel_EAST &	setConfidenceThreshold (float confThreshold)
	Set the detection confidence threshold.
TextDetectionModel_EAST &	setNMSThreshold (float nmsThreshold)
	Set the detection NMS filter threshold.
Public Member Functions inherited from cv::dnn::TextDetectionModel
void	detect (InputArray frame, std::vector< std::vector< Point > > &detections) const
void	detect (InputArray frame, std::vector< std::vector< Point > > &detections, std::vector< float > &confidences) const
	Performs detection.
void	detectTextRectangles (InputArray frame, std::vector< cv::RotatedRect > &detections) const
void	detectTextRectangles (InputArray frame, std::vector< cv::RotatedRect > &detections, std::vector< float > &confidences) const
	Performs detection.
Public Member Functions inherited from cv::dnn::Model
	Model ()
	Model (const Model &)=default
	Model (const Net &network)
	Create model from deep learning network.
	Model (CV_WRAP_FILE_PATH const String &model, CV_WRAP_FILE_PATH const String &config="")
	Create model from deep learning network represented in one of the supported formats. An order of model and config arguments does not matter.
	Model (Model &&)=default
Model &	enableWinograd (bool useWinograd)
Impl *	getImpl () const
Impl &	getImplRef () const
Net &	getNetwork_ ()
Net &	getNetwork_ () const
	operator Net & () const
Model &	operator= (const Model &)=default
Model &	operator= (Model &&)=default
void	predict (InputArray frame, OutputArrayOfArrays outs) const
	Given the input frame, create input blob, run net and return the output blobs.
Model &	setInputCrop (bool crop)
	Set flag crop for frame.
Model &	setInputMean (const Scalar &mean)
	Set mean value for frame.
void	setInputParams (double scale=1.0, const Size &size=Size(), const Scalar &mean=Scalar(), bool swapRB=false, bool crop=false)
	Set preprocessing parameters for frame.
Model &	setInputScale (const Scalar &scale)
	Set scalefactor value for frame.
Model &	setInputSize (const Size &size)
	Set input size for frame.
Model &	setInputSize (int width, int height)
Model &	setInputSwapRB (bool swapRB)
	Set flag swapRB for frame.
Model &	setPreferableBackend (dnn::Backend backendId)
Model &	setPreferableTarget (dnn::Target targetId)

Additional Inherited Members
Protected Member Functions inherited from cv::dnn::TextDetectionModel
	TextDetectionModel ()
Protected Attributes inherited from cv::dnn::Model
Ptr< Impl >	impl

Detailed Description

This class represents high-level API for text detection DL networks compatible with EAST model.

Configurable parameters:

• (float) confThreshold - used to filter boxes by confidences, default: 0.5f
• (float) nmsThreshold - used in non maximum suppression, default: 0.0f

Examples

samples/dnn/text_detection.cpp.

Constructor & Destructor Documentation

TextDetectionModel_EAST() [1/3]

cv::dnn::TextDetectionModel_EAST::TextDetectionModel_EAST

(

)

Python:
	cv.dnn.TextDetectionModel_EAST(	network	) ->	<dnn_TextDetectionModel_EAST object>
	cv.dnn.TextDetectionModel_EAST(	model[, config]	) ->	<dnn_TextDetectionModel_EAST object>

TextDetectionModel_EAST() [2/3]

cv::dnn::TextDetectionModel_EAST::TextDetectionModel_EAST

(

const Net &

network

)

Python:
	cv.dnn.TextDetectionModel_EAST(	network	) ->	<dnn_TextDetectionModel_EAST object>
	cv.dnn.TextDetectionModel_EAST(	model[, config]	) ->	<dnn_TextDetectionModel_EAST object>

Create text detection algorithm from deep learning network.

Parameters

[in]

network

Net object

TextDetectionModel_EAST() [3/3]

cv::dnn::TextDetectionModel_EAST::TextDetectionModel_EAST ( CV_WRAP_FILE_PATH const std::string &  model, CV_WRAP_FILE_PATH const std::string &  config = ""  )

inline

Python:
	cv.dnn.TextDetectionModel_EAST(	network	) ->	<dnn_TextDetectionModel_EAST object>
	cv.dnn.TextDetectionModel_EAST(	model[, config]	) ->	<dnn_TextDetectionModel_EAST object>

Create text detection model from network represented in one of the supported formats. An order of model and config arguments does not matter.

Parameters

[in]	model	Binary file contains trained weights.
[in]	config	Text file contains network configuration.

Here is the call graph for this function:

Member Function Documentation

getConfidenceThreshold()

float cv::dnn::TextDetectionModel_EAST::getConfidenceThreshold

(

)

const

Python:
	cv.dnn.TextDetectionModel_EAST.getConfidenceThreshold(		) ->	retval

Get the detection confidence threshold.

getNMSThreshold()

float cv::dnn::TextDetectionModel_EAST::getNMSThreshold

(

)

const

Python:
	cv.dnn.TextDetectionModel_EAST.getNMSThreshold(		) ->	retval

Get the detection confidence threshold.

setConfidenceThreshold()

TextDetectionModel_EAST & cv::dnn::TextDetectionModel_EAST::setConfidenceThreshold

(

float

confThreshold

)

Python:
	cv.dnn.TextDetectionModel_EAST.setConfidenceThreshold(	confThreshold	) ->	retval

Set the detection confidence threshold.

Parameters

[in]

confThreshold

A threshold used to filter boxes by confidences

setNMSThreshold()

TextDetectionModel_EAST & cv::dnn::TextDetectionModel_EAST::setNMSThreshold

(

float

nmsThreshold

)

Python:
	cv.dnn.TextDetectionModel_EAST.setNMSThreshold(	nmsThreshold	) ->	retval

Set the detection NMS filter threshold.

Parameters

[in]

nmsThreshold

A threshold used in non maximum suppression

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The documentation for this class was generated from the following file:

• opencv2/dnn/dnn.hpp