Package org.opencv.dnn_superres

Class DnnSuperResImpl

java.lang.Object

org.opencv.dnn_superres.DnnSuperResImpl

public class DnnSuperResImpl
extends java.lang.Object

A class to upscale images via convolutional neural networks. The following four models are implemented:

• edsr
• espcn
• fsrcnn
• lapsrn

Field Summary

Fields

Modifier and Type	Field	Description
protected long	nativeObj

Constructor Summary

Constructors

Modifier	Constructor	Description
protected	DnnSuperResImpl(long addr)

Method Summary

Modifier and Type	Method	Description
static DnnSuperResImpl	__fromPtr__(long addr)
static DnnSuperResImpl	create()	Empty constructor for python
protected void	finalize()
java.lang.String	getAlgorithm()	Returns the scale factor of the model:
long	getNativeObjAddr()
int	getScale()	Returns the scale factor of the model:
void	readModel(java.lang.String path)	Read the model from the given path
void	setModel(java.lang.String algo, int scale)	Set desired model
void	setPreferableBackend(int backendId)	Set computation backend
void	setPreferableTarget(int targetId)	Set computation target
void	upsample(Mat img, Mat result)	Upsample via neural network
void	upsampleMultioutput(Mat img, java.util.List<Mat> imgs_new, MatOfInt scale_factors, java.util.List<java.lang.String> node_names)	Upsample via neural network of multiple outputs

Methods inherited from class java.lang.Object

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

Field Detail

nativeObj

protected final long nativeObj

Constructor Detail

DnnSuperResImpl

protected DnnSuperResImpl(long addr)

Method Detail

getNativeObjAddr

public long getNativeObjAddr()

__fromPtr__

public static DnnSuperResImpl __fromPtr__(long addr)

create

public static DnnSuperResImpl create()

Empty constructor for python

Returns:

automatically generated

readModel

public void readModel(java.lang.String path)

Read the model from the given path

Parameters:

path - Path to the model file.

setModel

public void setModel(java.lang.String algo,
                     int scale)

Set desired model

Parameters:

algo - String containing one of the desired models:

• __edsr__
• __espcn__
• __fsrcnn__
• __lapsrn__

scale - Integer specifying the upscale factor

setPreferableBackend

public void setPreferableBackend(int backendId)

Set computation backend

Parameters:

backendId - automatically generated

setPreferableTarget

public void setPreferableTarget(int targetId)

Set computation target

Parameters:

targetId - automatically generated

upsample

public void upsample(Mat img,
                     Mat result)

Upsample via neural network

Parameters:

img - Image to upscale

result - Destination upscaled image

upsampleMultioutput

public void upsampleMultioutput(Mat img,
                                java.util.List<Mat> imgs_new,
                                MatOfInt scale_factors,
                                java.util.List<java.lang.String> node_names)

Upsample via neural network of multiple outputs

Parameters:

img - Image to upscale

imgs_new - Destination upscaled images

scale_factors - Scaling factors of the output nodes

node_names - Names of the output nodes in the neural network

getScale

public int getScale()

Returns the scale factor of the model:

Returns:

Current scale factor.

getAlgorithm

public java.lang.String getAlgorithm()

Returns the scale factor of the model:

Returns:

Current algorithm.

finalize

protected void finalize()
                 throws java.lang.Throwable

Overrides:

finalize in class java.lang.Object

Throws:

java.lang.Throwable