Package org.opencv.dnn_superres
Class DnnSuperResImpl
- java.lang.Object
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- org.opencv.dnn_superres.DnnSuperResImpl
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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
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Field Summary
Fields Modifier and Type Field Description protected long
nativeObj
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Constructor Summary
Constructors Modifier Constructor Description protected
DnnSuperResImpl(long addr)
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Method Summary
All Methods Static Methods Instance Methods Concrete Methods Modifier and Type Method Description static DnnSuperResImpl
__fromPtr__(long addr)
static DnnSuperResImpl
create()
Empty constructor for pythonprotected 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 pathvoid
setModel(java.lang.String algo, int scale)
Set desired modelvoid
setPreferableBackend(int backendId)
Set computation backendvoid
setPreferableTarget(int targetId)
Set computation targetvoid
upsample(Mat img, Mat result)
Upsample via neural networkvoid
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
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Method Detail
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getNativeObjAddr
public long getNativeObjAddr()
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__fromPtr__
public static DnnSuperResImpl __fromPtr__(long addr)
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create
public static DnnSuperResImpl create()
Empty constructor for python- Returns:
- automatically generated
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readModel
public void readModel(java.lang.String path)
Read the model from the given path- Parameters:
path
- Path to the model file.
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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
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setPreferableBackend
public void setPreferableBackend(int backendId)
Set computation backend- Parameters:
backendId
- automatically generated
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setPreferableTarget
public void setPreferableTarget(int targetId)
Set computation target- Parameters:
targetId
- automatically generated
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upsample
public void upsample(Mat img, Mat result)
Upsample via neural network- Parameters:
img
- Image to upscaleresult
- Destination upscaled image
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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 upscaleimgs_new
- Destination upscaled imagesscale_factors
- Scaling factors of the output nodesnode_names
- Names of the output nodes in the neural network
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getScale
public int getScale()
Returns the scale factor of the model:- Returns:
- Current scale factor.
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getAlgorithm
public java.lang.String getAlgorithm()
Returns the scale factor of the model:- Returns:
- Current algorithm.
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finalize
protected void finalize() throws java.lang.Throwable
- Overrides:
finalize
in classjava.lang.Object
- Throws:
java.lang.Throwable
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