public class KeypointsModel extends Model
Modifier | Constructor and Description |
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protected |
KeypointsModel(long addr) |
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KeypointsModel(Net network)
Create model from deep learning network.
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KeypointsModel(String model)
Create keypoints model from network represented in one of the supported formats.
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KeypointsModel(String model,
String config)
Create keypoints model from network represented in one of the supported formats.
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Modifier and Type | Method and Description |
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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 |
protected void |
finalize() |
enableWinograd, getNativeObjAddr, predict, setInputCrop, setInputMean, setInputParams, setInputParams, setInputParams, setInputParams, setInputParams, setInputParams, setInputScale, setInputSize, setInputSize, setInputSwapRB, setPreferableBackend, setPreferableTarget
protected KeypointsModel(long addr)
public KeypointsModel(String model, String config)
model
and config
arguments does not matter.model
- Binary file contains trained weights.config
- Text file contains network configuration.public KeypointsModel(String model)
model
and config
arguments does not matter.model
- Binary file contains trained weights.public KeypointsModel(Net network)
network
- Net object.public static KeypointsModel __fromPtr__(long addr)
public MatOfPoint2f estimate(Mat frame, float thresh)
input
frame, create input blob, run netthresh
- minimum confidence threshold to select a keypointframe
- automatically generatedpublic MatOfPoint2f estimate(Mat frame)
input
frame, create input blob, run netframe
- automatically generatedCopyright © 2024. All rights reserved.