Package org.opencv.dnn
Class ClassificationModel
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- org.opencv.dnn.Model
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- org.opencv.dnn.ClassificationModel
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public class ClassificationModel extends Model
This class represents high-level API for classification models. ClassificationModel allows to set params for preprocessing input image. ClassificationModel creates net from file with trained weights and config, sets preprocessing input, runs forward pass and return top-1 prediction.
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Constructor Summary
Constructors Modifier Constructor Description protected
ClassificationModel(long addr)
ClassificationModel(java.lang.String model)
Create classification model from network represented in one of the supported formats.ClassificationModel(java.lang.String model, java.lang.String config)
Create classification model from network represented in one of the supported formats.ClassificationModel(Net network)
Create model from deep learning network.
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Method Summary
All Methods Static Methods Instance Methods Concrete Methods Modifier and Type Method Description static ClassificationModel
__fromPtr__(long addr)
void
classify(Mat frame, int[] classId, float[] conf)
protected void
finalize()
boolean
getEnableSoftmaxPostProcessing()
Get enable/disable softmax post processing option.ClassificationModel
setEnableSoftmaxPostProcessing(boolean enable)
Set enable/disable softmax post processing option.-
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
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Constructor Detail
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ClassificationModel
protected ClassificationModel(long addr)
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ClassificationModel
public ClassificationModel(java.lang.String model, java.lang.String config)
Create classification model from network represented in one of the supported formats. An order ofmodel
andconfig
arguments does not matter.- Parameters:
model
- Binary file contains trained weights.config
- Text file contains network configuration.
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ClassificationModel
public ClassificationModel(java.lang.String model)
Create classification model from network represented in one of the supported formats. An order ofmodel
andconfig
arguments does not matter.- Parameters:
model
- Binary file contains trained weights.
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ClassificationModel
public ClassificationModel(Net network)
Create model from deep learning network.- Parameters:
network
- Net object.
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Method Detail
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__fromPtr__
public static ClassificationModel __fromPtr__(long addr)
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setEnableSoftmaxPostProcessing
public ClassificationModel setEnableSoftmaxPostProcessing(boolean enable)
Set enable/disable softmax post processing option. If this option is true, softmax is applied after forward inference within the classify() function to convert the confidences range to [0.0-1.0]. This function allows you to toggle this behavior. Please turn true when not contain softmax layer in model.- Parameters:
enable
- Set enable softmax post processing within the classify() function.- Returns:
- automatically generated
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getEnableSoftmaxPostProcessing
public boolean getEnableSoftmaxPostProcessing()
Get enable/disable softmax post processing option. This option defaults to false, softmax post processing is not applied within the classify() function.- Returns:
- automatically generated
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classify
public void classify(Mat frame, int[] classId, float[] conf)
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