Sparse match interpolation algorithm based on modified locally-weighted affine estimator from [Revaud2015] and Fast Global Smoother as post-processing filter.
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| float | getFGSLambda () |
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| float | getFGSSigma () |
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| int | getK () |
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| float | getLambda () |
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| float | getSigma () |
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| bool | getUsePostProcessing () |
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| void | setCostMap (Mat _costMap) |
| | 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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| void | setFGSLambda (float _lambda) |
| | Sets the respective fastGlobalSmootherFilter() parameter.
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| void | setFGSSigma (float _sigma) |
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| void | setK (int _k) |
| | 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.
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| void | setLambda (float _lambda) |
| | 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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| void | setSigma (float _sigma) |
| | 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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| void | setUsePostProcessing (bool _use_post_proc) |
| | Sets whether the fastGlobalSmootherFilter() post-processing is employed. It is turned on by default.
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| void | interpolate (Mat from_image, Mat from_points, Mat to_image, Mat to_points, Mat dense_flow) |
| | Interpolate input sparse matches.
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| virtual void | clear () |
| | Clears the algorithm state.
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| virtual bool | empty () |
| | Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read.
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| virtual string | getDefaultName () |
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| IntPtr | getNativeObjAddr () |
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| void | save (string filename) |
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| void | Dispose () |
| | Releases resources used by this object.
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| void | ThrowIfDisposed () |
| | Throws ObjectDisposedException if this object has been disposed.
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Sparse match interpolation algorithm based on modified locally-weighted affine estimator from [Revaud2015] and Fast Global Smoother as post-processing filter.
◆ __fromPtr__()
| static new EdgeAwareInterpolator OpenCVForUnity.XimgprocModule.EdgeAwareInterpolator.__fromPtr__ |
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IntPtr | addr | ) |
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◆ Dispose()
| override void OpenCVForUnity.XimgprocModule.EdgeAwareInterpolator.Dispose |
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bool | disposing | ) |
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protectedvirtual |
◆ getFGSLambda()
| float OpenCVForUnity.XimgprocModule.EdgeAwareInterpolator.getFGSLambda |
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◆ getFGSSigma()
| float OpenCVForUnity.XimgprocModule.EdgeAwareInterpolator.getFGSSigma |
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◆ getK()
| int OpenCVForUnity.XimgprocModule.EdgeAwareInterpolator.getK |
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◆ getLambda()
| float OpenCVForUnity.XimgprocModule.EdgeAwareInterpolator.getLambda |
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◆ getSigma()
| float OpenCVForUnity.XimgprocModule.EdgeAwareInterpolator.getSigma |
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◆ getUsePostProcessing()
| bool OpenCVForUnity.XimgprocModule.EdgeAwareInterpolator.getUsePostProcessing |
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◆ setCostMap()
| void OpenCVForUnity.XimgprocModule.EdgeAwareInterpolator.setCostMap |
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Mat | _costMap | ) |
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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. |
cv::ximgproc::createSuperpixelSLIC
◆ setFGSLambda()
| void OpenCVForUnity.XimgprocModule.EdgeAwareInterpolator.setFGSLambda |
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float | _lambda | ) |
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Sets the respective fastGlobalSmootherFilter() parameter.
◆ setFGSSigma()
| void OpenCVForUnity.XimgprocModule.EdgeAwareInterpolator.setFGSSigma |
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float | _sigma | ) |
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◆ setK()
| void OpenCVForUnity.XimgprocModule.EdgeAwareInterpolator.setK |
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int | _k | ) |
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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()
| void OpenCVForUnity.XimgprocModule.EdgeAwareInterpolator.setLambda |
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float | _lambda | ) |
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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()
| void OpenCVForUnity.XimgprocModule.EdgeAwareInterpolator.setSigma |
( |
float | _sigma | ) |
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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()
| void OpenCVForUnity.XimgprocModule.EdgeAwareInterpolator.setUsePostProcessing |
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bool | _use_post_proc | ) |
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Sets whether the fastGlobalSmootherFilter() post-processing is employed. It is turned on by default.
The documentation for this class was generated from the following file: