Package org.opencv.dnn

Class KeypointsModel

java.lang.Object

org.opencv.dnn.Model

org.opencv.dnn.KeypointsModel

public class KeypointsModel
extends Model

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 Summary

Constructors

Constructor	Description
KeypointsModel(String model)	Create keypoints model from network represented in one of the supported formats.
KeypointsModel(String model, String config)	Create keypoints model from network represented in one of the supported formats.
KeypointsModel(Net network)	Create model from deep learning network.

Method Summary

Modifier and Type	Method	Description
static KeypointsModel	__fromPtr__(long addr)
MatOfPoint2f	estimate(Mat frame)	Given the input frame, create input blob, run net
MatOfPoint2f	estimate(Mat frame, float thresh)	Given the input frame, create input blob, run net

Methods inherited from class org.opencv.dnn.Model

enableWinograd, getNativeObjAddr, predict, setInputCrop, setInputMean, setInputParams, setInputParams, setInputParams, setInputParams, setInputParams, setInputParams, setInputScale, setInputSize, setInputSize, setInputSwapRB, setOutputNames, setPreferableBackend, setPreferableTarget

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Details

KeypointsModel

public KeypointsModel(String model,
 String config)

Create keypoints 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.

KeypointsModel

public KeypointsModel(String model)

Create keypoints 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.

KeypointsModel

public KeypointsModel(Net network)

Create model from deep learning network.

Parameters:

network - Net object.

Method Details

__fromPtr__

public static KeypointsModel __fromPtr__(long addr)

estimate

public MatOfPoint2f estimate(Mat frame,
 float thresh)

Given the input frame, create input blob, run net

Parameters:

thresh - minimum confidence threshold to select a keypoint

frame - automatically generated

Returns:

a vector holding the x and y coordinates of each detected keypoint

estimate

public MatOfPoint2f estimate(Mat frame)

Given the input frame, create input blob, run net

Parameters:

frame - automatically generated

Returns:

a vector holding the x and y coordinates of each detected keypoint