Class cv::dnn::TextDetectionModel_EAST#

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

#include <opencv2/dnn/dnn.hpp>

Collaboration diagram for cv::dnn::TextDetectionModel_EAST:

Public Member Functions#

Public Member Functions inherited from cv::dnn::TextDetectionModel

Return	Name	Description
`void`	`detect(` `InputArray frame,` `std::vector< std::vector< Point > > & detections )`
`void`	`detect(` `InputArray frame,` `std::vector< std::vector< Point > > & detections,` `std::vector< float > & confidences )`	Performs detection.
`void`	`detectTextRectangles(` `InputArray frame,` `std::vector< cv::RotatedRect > & detections )`
`void`	`detectTextRectangles(` `InputArray frame,` `std::vector< cv::RotatedRect > & detections,` `std::vector< float > & confidences )`	Performs detection.

Public Member Functions inherited from cv::dnn::Model

Return	Name	Description
	`Model()`
	`Model(const Model &)`
	`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 &&)`
`Model &`	`enableWinograd(bool useWinograd)`
`Impl *`	`getImpl()`
`Impl &`	`getImplRef()`
`Net &`	`getNetwork_()`
`Net &`	`getNetwork_()`
	`operator Net &()`
`Model &`	`operator=(const Model &)`
`Model &`	`operator=(Model &&)`
`void`	`predict(` `InputArray frame,` `OutputArrayOfArrays outs )`	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 &`	`setOutputNames(const std::vector< String > & outNames)`	Set output names for frame.
`Model &`	`setPreferableBackend(dnn::Backend backendId)`
`Model &`	`setPreferableTarget(dnn::Target targetId)`

Additional Inherited Members#

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()#

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()#

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

network — Net object

TextDetectionModel_EAST()#

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

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

model — Binary file contains trained weights.
config — Text file contains network configuration.

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Member Function Documentation#

getConfidenceThreshold()#

float cv::dnn::TextDetectionModel_EAST::getConfidenceThreshold()

Python:

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

Get the detection confidence threshold.

getNMSThreshold()#

float cv::dnn::TextDetectionModel_EAST::getNMSThreshold()

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

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

nmsThreshold — A threshold used in non maximum suppression

Source file#

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

opencv2/dnn/dnn.hpp