cv::dnn_superres::DnnSuperResImpl Class Reference

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

#include <opencv2/dnn_superres.hpp>

Collaboration diagram for cv::dnn_superres::DnnSuperResImpl:

Public Member Functions
	DnnSuperResImpl ()
	DnnSuperResImpl (const String &algo, int scale)
	Constructor which immediately sets the desired model.
String	getAlgorithm ()
	Returns the scale factor of the model:
int	getScale ()
	Returns the scale factor of the model:
void	readModel (const String &path)
	Read the model from the given path.
void	readModel (const String &weights, const String &definition)
	Read the model from the given path.
void	setModel (const String &algo, int scale)
	Set desired model.
void	setPreferableBackend (int backendId)
	Set computation backend.
void	setPreferableTarget (int targetId)
	Set computation target.
void	upsample (InputArray img, OutputArray result)
	Upsample via neural network.
void	upsampleMultioutput (InputArray img, std::vector< Mat > &imgs_new, const std::vector< int > &scale_factors, const std::vector< String > &node_names)
	Upsample via neural network of multiple outputs.

Static Public Member Functions
static Ptr< DnnSuperResImpl >	create ()
	Empty constructor for python.

Detailed Description

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

• edsr
• espcn
• fsrcnn
• lapsrn

Constructor & Destructor Documentation

DnnSuperResImpl() [1/2]

cv::dnn_superres::DnnSuperResImpl::DnnSuperResImpl

(

)

DnnSuperResImpl() [2/2]

cv::dnn_superres::DnnSuperResImpl::DnnSuperResImpl	(	const String &	algo,
		int	scale
	)

Constructor which immediately sets the desired model.

Parameters

algo	String containing one of the desired models: edsr espcn fsrcnn lapsrn
scale	Integer specifying the upscale factor

Member Function Documentation

create()

static Ptr< DnnSuperResImpl > cv::dnn_superres::DnnSuperResImpl::create ( )

static

Python:
	cv.dnn_superres.DnnSuperResImpl.create(		) ->	retval
	cv.dnn_superres.DnnSuperResImpl_create(		) ->	retval

Empty constructor for python.

getAlgorithm()

String cv::dnn_superres::DnnSuperResImpl::getAlgorithm

(

)

Python:
	cv.dnn_superres.DnnSuperResImpl.getAlgorithm(		) ->	retval

Returns the scale factor of the model:

Returns

Current algorithm.

getScale()

int cv::dnn_superres::DnnSuperResImpl::getScale

(

)

Python:
	cv.dnn_superres.DnnSuperResImpl.getScale(		) ->	retval

Returns the scale factor of the model:

Returns

Current scale factor.

readModel() [1/2]

void cv::dnn_superres::DnnSuperResImpl::readModel

(

const String &

path

)

Python:
	cv.dnn_superres.DnnSuperResImpl.readModel(	path	) ->	None

Read the model from the given path.

Parameters

path	Path to the model file.

readModel() [2/2]

void cv::dnn_superres::DnnSuperResImpl::readModel	(	const String &	weights,
		const String &	definition
	)

Python:
	cv.dnn_superres.DnnSuperResImpl.readModel(	path	) ->	None

Read the model from the given path.

Parameters

weights	Path to the model weights file.
definition	Path to the model definition file.

setModel()

void cv::dnn_superres::DnnSuperResImpl::setModel	(	const String &	algo,
		int	scale
	)

Python:
	cv.dnn_superres.DnnSuperResImpl.setModel(	algo, scale	) ->	None

Set desired model.

Parameters

algo	String containing one of the desired models: edsr espcn fsrcnn lapsrn
scale	Integer specifying the upscale factor

setPreferableBackend()

void cv::dnn_superres::DnnSuperResImpl::setPreferableBackend

(

int

backendId

)

Python:
	cv.dnn_superres.DnnSuperResImpl.setPreferableBackend(	backendId	) ->	None

Set computation backend.

setPreferableTarget()

void cv::dnn_superres::DnnSuperResImpl::setPreferableTarget

(

int

targetId

)

Python:
	cv.dnn_superres.DnnSuperResImpl.setPreferableTarget(	targetId	) ->	None

Set computation target.

upsample()

void cv::dnn_superres::DnnSuperResImpl::upsample	(	InputArray	img,
		OutputArray	result
	)

Python:
	cv.dnn_superres.DnnSuperResImpl.upsample(	img[, result]	) ->	result

Upsample via neural network.

Parameters

img	Image to upscale
result	Destination upscaled image

upsampleMultioutput()

void cv::dnn_superres::DnnSuperResImpl::upsampleMultioutput	(	InputArray	img,
		std::vector< Mat > &	imgs_new,
		const std::vector< int > &	scale_factors,
		const std::vector< String > &	node_names
	)

Python:
	cv.dnn_superres.DnnSuperResImpl.upsampleMultioutput(	img, imgs_new, scale_factors, node_names	) ->	None

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

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The documentation for this class was generated from the following file:

• opencv2/dnn_superres.hpp