OpenCV  5.0.0-pre
Open Source Computer Vision
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Public Member Functions | Static Public Member Functions | List of all members
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< DnnSuperResImplcreate ()
 Empty constructor for python.
 

Detailed Description

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

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
algoString containing one of the desired models:
  • edsr
  • espcn
  • fsrcnn
  • lapsrn
scaleInteger 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
pathPath 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
weightsPath to the model weights file.
definitionPath 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
algoString containing one of the desired models:
  • edsr
  • espcn
  • fsrcnn
  • lapsrn
scaleInteger 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
imgImage to upscale
resultDestination 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
imgImage to upscale
imgs_newDestination upscaled images
scale_factorsScaling factors of the output nodes
node_namesNames of the output nodes in the neural network

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