org.opencv.dnn

Class SegmentationModel

java.lang.Object

org.opencv.dnn.Model

org.opencv.dnn.SegmentationModel

public class SegmentationModel
extends Model

This class represents high-level API for segmentation models SegmentationModel allows to set params for preprocessing input image. SegmentationModel creates net from file with trained weights and config, sets preprocessing input, runs forward pass and returns the class prediction for each pixel.

Constructor Summary

Constructors

Constructor and Description
SegmentationModel(Net network) Create model from deep learning network.
SegmentationModel(java.lang.String model) Create segmentation model from network represented in one of the supported formats.
SegmentationModel(java.lang.String model, java.lang.String config) Create segmentation model from network represented in one of the supported formats.

Method Summary

Modifier and Type	Method and Description
static SegmentationModel	__fromPtr__(long addr)
void	segment(Mat frame, Mat mask) Given the input frame, create input blob, run net

Methods inherited from class org.opencv.dnn.Model

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

Methods inherited from class java.lang.Object

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

Constructor Detail

SegmentationModel

public SegmentationModel(Net network)

Create model from deep learning network.

Parameters:

network - Net object.

SegmentationModel

public SegmentationModel(java.lang.String model)

Create segmentation 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.

SegmentationModel

public SegmentationModel(java.lang.String model,
                         java.lang.String config)

Create segmentation 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 SegmentationModel __fromPtr__(long addr)

segment

public void segment(Mat frame,
                    Mat mask)

Given the input frame, create input blob, run net

Parameters:

mask - Allocated class prediction for each pixel

frame - automatically generated