org.opencv.dnn

Class ClassificationModel

java.lang.Object

org.opencv.dnn.Model

org.opencv.dnn.ClassificationModel

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.

Constructor Summary

Constructors

Constructor and Description
ClassificationModel(Net network) Create model from deep learning network.
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.

Method Summary

Modifier and Type	Method and Description
static ClassificationModel	__fromPtr__(long addr)
void	classify(Mat frame, int[] classId, float[] conf)
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

Methods inherited from class java.lang.Object

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

Constructor Detail

ClassificationModel

public ClassificationModel(Net network)

Create model from deep learning network.

Parameters:

network - Net object.

ClassificationModel

public ClassificationModel(java.lang.String model)

Create classification 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.

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 of model and config arguments does not matter.

Parameters:

model - Binary file contains trained weights.

config - Text file contains network configuration.

Method Detail

__fromPtr__

public static ClassificationModel __fromPtr__(long addr)

classify

public void classify(Mat frame,
                     int[] classId,
                     float[] conf)

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

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