OpenCV  4.5.2-pre
Open Source Computer Vision
Public Member Functions | List of all members
cv::dnn::TextDetectionModel_DB Class Reference

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

#include <opencv2/dnn/dnn.hpp>

Inheritance diagram for cv::dnn::TextDetectionModel_DB:
cv::dnn::TextDetectionModel cv::dnn::Model

Public Member Functions

 TextDetectionModel_DB ()
 
 TextDetectionModel_DB (const Net &network)
 Create text detection algorithm from deep learning network. More...
 
 TextDetectionModel_DB (const std::string &model, 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. More...
 
float getBinaryThreshold () const
 
int getMaxCandidates () const
 
float getPolygonThreshold () const
 
double getUnclipRatio () const
 
TextDetectionModel_DBsetBinaryThreshold (float binaryThreshold)
 
TextDetectionModel_DBsetMaxCandidates (int maxCandidates)
 
TextDetectionModel_DBsetPolygonThreshold (float polygonThreshold)
 
TextDetectionModel_DBsetUnclipRatio (double unclipRatio)
 
- Public Member Functions inherited from cv::dnn::TextDetectionModel
void detect (InputArray frame, std::vector< std::vector< Point > > &detections, std::vector< float > &confidences) const
 Performs detection. More...
 
void detect (InputArray frame, std::vector< std::vector< Point > > &detections) const
 
void detectTextRectangles (InputArray frame, std::vector< cv::RotatedRect > &detections, std::vector< float > &confidences) const
 Performs detection. More...
 
void detectTextRectangles (InputArray frame, std::vector< cv::RotatedRect > &detections) const
 
- Public Member Functions inherited from cv::dnn::Model
 Model ()
 
 Model (const Model &)=default
 
 Model (Model &&)=default
 
 Model (const String &model, 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. More...
 
 Model (const Net &network)
 Create model from deep learning network. More...
 
Impl * getImpl () const
 
Impl & getImplRef () const
 
NetgetNetwork_ () const
 
NetgetNetwork_ ()
 
 operator Net & () const
 
Modeloperator= (const Model &)=default
 
Modeloperator= (Model &&)=default
 
void predict (InputArray frame, OutputArrayOfArrays outs) const
 Given the input frame, create input blob, run net and return the output blobs. More...
 
ModelsetInputCrop (bool crop)
 Set flag crop for frame. More...
 
ModelsetInputMean (const Scalar &mean)
 Set mean value for frame. More...
 
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. More...
 
ModelsetInputScale (double scale)
 Set scalefactor value for frame. More...
 
ModelsetInputSize (const Size &size)
 Set input size for frame. More...
 
ModelsetInputSize (int width, int height)
 
ModelsetInputSwapRB (bool swapRB)
 Set flag swapRB for frame. More...
 
ModelsetPreferableBackend (dnn::Backend backendId)
 
ModelsetPreferableTarget (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 DB model.

Related publications: [145] Paper: https://arxiv.org/abs/1911.08947 For more information about the hyper-parameters setting, please refer to https://github.com/MhLiao/DB

Configurable parameters:

Constructor & Destructor Documentation

◆ TextDetectionModel_DB() [1/3]

cv::dnn::TextDetectionModel_DB::TextDetectionModel_DB ( )
Python:
<dnn_TextDetectionModel_DB object>=cv.dnn_TextDetectionModel_DB(network)
<dnn_TextDetectionModel_DB object>=cv.dnn_TextDetectionModel_DB(model[, config])

◆ TextDetectionModel_DB() [2/3]

cv::dnn::TextDetectionModel_DB::TextDetectionModel_DB ( const Net network)
Python:
<dnn_TextDetectionModel_DB object>=cv.dnn_TextDetectionModel_DB(network)
<dnn_TextDetectionModel_DB object>=cv.dnn_TextDetectionModel_DB(model[, config])

Create text detection algorithm from deep learning network.

Parameters
[in]networkNet object.

◆ TextDetectionModel_DB() [3/3]

cv::dnn::TextDetectionModel_DB::TextDetectionModel_DB ( const std::string &  model,
const std::string &  config = "" 
)
inline
Python:
<dnn_TextDetectionModel_DB object>=cv.dnn_TextDetectionModel_DB(network)
<dnn_TextDetectionModel_DB object>=cv.dnn_TextDetectionModel_DB(model[, config])

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]modelBinary file contains trained weights.
[in]configText file contains network configuration.

Member Function Documentation

◆ getBinaryThreshold()

float cv::dnn::TextDetectionModel_DB::getBinaryThreshold ( ) const
Python:
retval=cv.dnn_TextDetectionModel_DB.getBinaryThreshold()

◆ getMaxCandidates()

int cv::dnn::TextDetectionModel_DB::getMaxCandidates ( ) const
Python:
retval=cv.dnn_TextDetectionModel_DB.getMaxCandidates()

◆ getPolygonThreshold()

float cv::dnn::TextDetectionModel_DB::getPolygonThreshold ( ) const
Python:
retval=cv.dnn_TextDetectionModel_DB.getPolygonThreshold()

◆ getUnclipRatio()

double cv::dnn::TextDetectionModel_DB::getUnclipRatio ( ) const
Python:
retval=cv.dnn_TextDetectionModel_DB.getUnclipRatio()

◆ setBinaryThreshold()

TextDetectionModel_DB& cv::dnn::TextDetectionModel_DB::setBinaryThreshold ( float  binaryThreshold)
Python:
retval=cv.dnn_TextDetectionModel_DB.setBinaryThreshold(binaryThreshold)

◆ setMaxCandidates()

TextDetectionModel_DB& cv::dnn::TextDetectionModel_DB::setMaxCandidates ( int  maxCandidates)
Python:
retval=cv.dnn_TextDetectionModel_DB.setMaxCandidates(maxCandidates)

◆ setPolygonThreshold()

TextDetectionModel_DB& cv::dnn::TextDetectionModel_DB::setPolygonThreshold ( float  polygonThreshold)
Python:
retval=cv.dnn_TextDetectionModel_DB.setPolygonThreshold(polygonThreshold)

◆ setUnclipRatio()

TextDetectionModel_DB& cv::dnn::TextDetectionModel_DB::setUnclipRatio ( double  unclipRatio)
Python:
retval=cv.dnn_TextDetectionModel_DB.setUnclipRatio(unclipRatio)

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