Sparse match interpolation algorithm based on modified locally-weighted affine estimator from [224] and Fast Global Smoother as post-processing filter.
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#include <opencv2/ximgproc/sparse_match_interpolator.hpp>
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virtual float | getFGSLambda ()=0 |
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virtual float | getFGSSigma ()=0 |
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virtual int | getK ()=0 |
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virtual float | getLambda ()=0 |
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virtual float | getSigma ()=0 |
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virtual bool | getUsePostProcessing ()=0 |
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virtual void | setCostMap (const Mat &_costMap)=0 |
| Interface to provide a more elaborated cost map, i.e. edge map, for the edge-aware term. This implementation is based on a rather simple gradient-based edge map estimation. To used more complex edge map estimator (e.g. StructuredEdgeDetection that has been used in the original publication) that may lead to improved accuracies, the internal edge map estimation can be bypassed here.
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virtual void | setFGSLambda (float _lambda)=0 |
| Sets the respective fastGlobalSmootherFilter() parameter.
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virtual void | setFGSSigma (float _sigma)=0 |
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virtual void | setK (int _k)=0 |
| Parameter to tune the approximate size of the superpixel used for oversegmentation.
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virtual void | setLambda (float _lambda)=0 |
| Lambda is a parameter defining the weight of the edge-aware term in geodesic distance, should be in the range of 0 to 1000.
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virtual void | setSigma (float _sigma)=0 |
| Sigma is a parameter defining how fast the weights decrease in the locally-weighted affine fitting. Higher values can help preserve fine details, lower values can help to get rid of noise in the output flow.
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virtual void | setUsePostProcessing (bool _use_post_proc)=0 |
| Sets whether the fastGlobalSmootherFilter() post-processing is employed. It is turned on by default.
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virtual void | interpolate (InputArray from_image, InputArray from_points, InputArray to_image, InputArray to_points, OutputArray dense_flow)=0 |
| Interpolate input sparse matches.
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| Algorithm () |
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virtual | ~Algorithm () |
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virtual void | clear () |
| Clears the algorithm state.
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virtual bool | empty () const |
| Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read.
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virtual String | getDefaultName () const |
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virtual void | read (const FileNode &fn) |
| Reads algorithm parameters from a file storage.
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virtual void | save (const String &filename) const |
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void | write (const Ptr< FileStorage > &fs, const String &name=String()) const |
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virtual void | write (FileStorage &fs) const |
| Stores algorithm parameters in a file storage.
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void | write (FileStorage &fs, const String &name) const |
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Sparse match interpolation algorithm based on modified locally-weighted affine estimator from [224] and Fast Global Smoother as post-processing filter.
◆ getFGSLambda()
virtual float cv::ximgproc::EdgeAwareInterpolator::getFGSLambda |
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pure virtual |
Python: |
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| cv.ximgproc.EdgeAwareInterpolator.getFGSLambda( | | ) -> | retval |
◆ getFGSSigma()
virtual float cv::ximgproc::EdgeAwareInterpolator::getFGSSigma |
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pure virtual |
Python: |
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| cv.ximgproc.EdgeAwareInterpolator.getFGSSigma( | | ) -> | retval |
◆ getK()
virtual int cv::ximgproc::EdgeAwareInterpolator::getK |
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pure virtual |
Python: |
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| cv.ximgproc.EdgeAwareInterpolator.getK( | | ) -> | retval |
◆ getLambda()
virtual float cv::ximgproc::EdgeAwareInterpolator::getLambda |
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pure virtual |
Python: |
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| cv.ximgproc.EdgeAwareInterpolator.getLambda( | | ) -> | retval |
◆ getSigma()
virtual float cv::ximgproc::EdgeAwareInterpolator::getSigma |
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pure virtual |
Python: |
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| cv.ximgproc.EdgeAwareInterpolator.getSigma( | | ) -> | retval |
◆ getUsePostProcessing()
virtual bool cv::ximgproc::EdgeAwareInterpolator::getUsePostProcessing |
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pure virtual |
Python: |
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| cv.ximgproc.EdgeAwareInterpolator.getUsePostProcessing( | | ) -> | retval |
◆ setCostMap()
virtual void cv::ximgproc::EdgeAwareInterpolator::setCostMap |
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const Mat & |
_costMap | ) |
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pure virtual |
Python: |
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| cv.ximgproc.EdgeAwareInterpolator.setCostMap( | _costMap | ) -> | None |
Interface to provide a more elaborated cost map, i.e. edge map, for the edge-aware term. This implementation is based on a rather simple gradient-based edge map estimation. To used more complex edge map estimator (e.g. StructuredEdgeDetection that has been used in the original publication) that may lead to improved accuracies, the internal edge map estimation can be bypassed here.
- Parameters
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_costMap | a type CV_32FC1 Mat is required. |
- See also
- cv::ximgproc::createSuperpixelSLIC
◆ setFGSLambda()
virtual void cv::ximgproc::EdgeAwareInterpolator::setFGSLambda |
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float |
_lambda | ) |
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pure virtual |
Python: |
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| cv.ximgproc.EdgeAwareInterpolator.setFGSLambda( | _lambda | ) -> | None |
◆ setFGSSigma()
virtual void cv::ximgproc::EdgeAwareInterpolator::setFGSSigma |
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float |
_sigma | ) |
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pure virtual |
Python: |
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| cv.ximgproc.EdgeAwareInterpolator.setFGSSigma( | _sigma | ) -> | None |
◆ setK()
virtual void cv::ximgproc::EdgeAwareInterpolator::setK |
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int |
_k | ) |
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pure virtual |
Python: |
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| cv.ximgproc.EdgeAwareInterpolator.setK( | _k | ) -> | None |
Parameter to tune the approximate size of the superpixel used for oversegmentation.
- See also
- cv::ximgproc::createSuperpixelSLIC
K is a number of nearest-neighbor matches considered, when fitting a locally affine model. Usually it should be around 128. However, lower values would make the interpolation noticeably faster.
◆ setLambda()
virtual void cv::ximgproc::EdgeAwareInterpolator::setLambda |
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float |
_lambda | ) |
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pure virtual |
Python: |
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| cv.ximgproc.EdgeAwareInterpolator.setLambda( | _lambda | ) -> | None |
Lambda is a parameter defining the weight of the edge-aware term in geodesic distance, should be in the range of 0 to 1000.
◆ setSigma()
virtual void cv::ximgproc::EdgeAwareInterpolator::setSigma |
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float |
_sigma | ) |
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pure virtual |
Python: |
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| cv.ximgproc.EdgeAwareInterpolator.setSigma( | _sigma | ) -> | None |
Sigma is a parameter defining how fast the weights decrease in the locally-weighted affine fitting. Higher values can help preserve fine details, lower values can help to get rid of noise in the output flow.
◆ setUsePostProcessing()
virtual void cv::ximgproc::EdgeAwareInterpolator::setUsePostProcessing |
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bool |
_use_post_proc | ) |
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pure virtual |
Python: |
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| cv.ximgproc.EdgeAwareInterpolator.setUsePostProcessing( | _use_post_proc | ) -> | None |
The documentation for this class was generated from the following file: