OpenCV  4.5.1-dev
Open Source Computer Vision
Public Member Functions | List of all members
cv::dnn::KeypointsModel Class Reference

This class represents high-level API for keypoints models. More...

#include <opencv2/dnn/dnn.hpp>

Inheritance diagram for cv::dnn::KeypointsModel:
cv::dnn::Model

Public Member Functions

 KeypointsModel (const String &model, const String &config="")
 Create keypoints model from network represented in one of the supported formats. An order of model and config arguments does not matter. More...
 
 KeypointsModel (const Net &network)
 Create model from deep learning network. More...
 
std::vector< Point2festimate (InputArray frame, float thresh=0.5)
 Given the input frame, create input blob, run net. More...
 
- 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 Attributes inherited from cv::dnn::Model
Ptr< Impl > impl
 

Detailed Description

This class represents high-level API for keypoints models.

KeypointsModel allows to set params for preprocessing input image. KeypointsModel creates net from file with trained weights and config, sets preprocessing input, runs forward pass and returns the x and y coordinates of each detected keypoint

Constructor & Destructor Documentation

◆ KeypointsModel() [1/2]

cv::dnn::KeypointsModel::KeypointsModel ( const String model,
const String config = "" 
)
Python:
<dnn_KeypointsModel object>=cv.dnn_KeypointsModel(model[, config])
<dnn_KeypointsModel object>=cv.dnn_KeypointsModel(network)

Create keypoints 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.

◆ KeypointsModel() [2/2]

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

Create model from deep learning network.

Parameters
[in]networkNet object.

Member Function Documentation

◆ estimate()

std::vector<Point2f> cv::dnn::KeypointsModel::estimate ( InputArray  frame,
float  thresh = 0.5 
)
Python:
retval=cv.dnn_KeypointsModel.estimate(frame[, thresh])

Given the input frame, create input blob, run net.

Parameters
[in]frameThe input image.
threshminimum confidence threshold to select a keypoint
Returns
a vector holding the x and y coordinates of each detected keypoint

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