OpenCV for Unity  2.6.3
Enox Software / Please refer to OpenCV official document ( http://docs.opencv.org/4.10.0/index.html ) for the details of the argument of the method.
Public Member Functions | Static Public Member Functions | Protected Member Functions | List of all members
OpenCVForUnity.XimgprocModule.RICInterpolator Class Reference

Sparse match interpolation algorithm based on modified piecewise locally-weighted affine estimator called Robust Interpolation method of Correspondences or RIC from [Hu2017] and Variational and Fast Global Smoother as post-processing filter. The RICInterpolator is a extension of the EdgeAwareInterpolator. Main concept of this extension is an piece-wise affine model based on over-segmentation via SLIC superpixel estimation. The method contains an efficient propagation mechanism to estimate among the pieces-wise models. More...

Inheritance diagram for OpenCVForUnity.XimgprocModule.RICInterpolator:
OpenCVForUnity.XimgprocModule.SparseMatchInterpolator OpenCVForUnity.CoreModule.Algorithm OpenCVForUnity.DisposableOpenCVObject OpenCVForUnity.DisposableObject

Public Member Functions

void setK (int k)
 K is a number of nearest-neighbor matches considered, when fitting a locally affine model for a superpixel segment. However, lower values would make the interpolation noticeably faster. The original implementation of [Hu2017] uses 32. More...
 
void setK ()
 K is a number of nearest-neighbor matches considered, when fitting a locally affine model for a superpixel segment. However, lower values would make the interpolation noticeably faster. The original implementation of [Hu2017] uses 32. More...
 
int getK ()
 
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. More...
 
void setSuperpixelSize (int spSize)
 Get the internal cost, i.e. edge map, used for estimating the edge-aware term. More...
 
void setSuperpixelSize ()
 Get the internal cost, i.e. edge map, used for estimating the edge-aware term. More...
 
int getSuperpixelSize ()
 
void setSuperpixelNNCnt (int spNN)
 Parameter defines the number of nearest-neighbor matches for each superpixel considered, when fitting a locally affine model. More...
 
void setSuperpixelNNCnt ()
 Parameter defines the number of nearest-neighbor matches for each superpixel considered, when fitting a locally affine model. More...
 
int getSuperpixelNNCnt ()
 
void setSuperpixelRuler (float ruler)
 Parameter to tune enforcement of superpixel smoothness factor used for oversegmentation. More...
 
void setSuperpixelRuler ()
 Parameter to tune enforcement of superpixel smoothness factor used for oversegmentation. More...
 
float getSuperpixelRuler ()
 
void setSuperpixelMode (int mode)
 Parameter to choose superpixel algorithm variant to use: More...
 
void setSuperpixelMode ()
 Parameter to choose superpixel algorithm variant to use: More...
 
int getSuperpixelMode ()
 
void setAlpha (float alpha)
 Alpha is a parameter defining a global weight for transforming geodesic distance into weight. More...
 
void setAlpha ()
 Alpha is a parameter defining a global weight for transforming geodesic distance into weight. More...
 
float getAlpha ()
 
void setModelIter (int modelIter)
 Parameter defining the number of iterations for piece-wise affine model estimation. More...
 
void setModelIter ()
 Parameter defining the number of iterations for piece-wise affine model estimation. More...
 
int getModelIter ()
 
void setRefineModels (bool refineModles)
 Parameter to choose wether additional refinement of the piece-wise affine models is employed. More...
 
void setRefineModels ()
 Parameter to choose wether additional refinement of the piece-wise affine models is employed. More...
 
bool getRefineModels ()
 
void setMaxFlow (float maxFlow)
 MaxFlow is a threshold to validate the predictions using a certain piece-wise affine model. If the prediction exceeds the treshold the translational model will be applied instead. More...
 
void setMaxFlow ()
 MaxFlow is a threshold to validate the predictions using a certain piece-wise affine model. If the prediction exceeds the treshold the translational model will be applied instead. More...
 
float getMaxFlow ()
 
void setUseVariationalRefinement (bool use_variational_refinement)
 Parameter to choose wether the VariationalRefinement post-processing is employed. More...
 
void setUseVariationalRefinement ()
 Parameter to choose wether the VariationalRefinement post-processing is employed. More...
 
bool getUseVariationalRefinement ()
 
void setUseGlobalSmootherFilter (bool use_FGS)
 Sets whether the fastGlobalSmootherFilter() post-processing is employed. More...
 
void setUseGlobalSmootherFilter ()
 Sets whether the fastGlobalSmootherFilter() post-processing is employed. More...
 
bool getUseGlobalSmootherFilter ()
 
void setFGSLambda (float lambda)
 Sets the respective fastGlobalSmootherFilter() parameter. More...
 
void setFGSLambda ()
 Sets the respective fastGlobalSmootherFilter() parameter. More...
 
float getFGSLambda ()
 
void setFGSSigma (float sigma)
 Sets the respective fastGlobalSmootherFilter() parameter. More...
 
void setFGSSigma ()
 Sets the respective fastGlobalSmootherFilter() parameter. More...
 
float getFGSSigma ()
 
- Public Member Functions inherited from OpenCVForUnity.XimgprocModule.SparseMatchInterpolator
void interpolate (Mat from_image, Mat from_points, Mat to_image, Mat to_points, Mat dense_flow)
 Interpolate input sparse matches. More...
 
- Public Member Functions inherited from OpenCVForUnity.CoreModule.Algorithm
IntPtr getNativeObjAddr ()
 
virtual void clear ()
 Clears the algorithm state. More...
 
virtual bool empty ()
 Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read. More...
 
void save (string filename)
 
virtual string getDefaultName ()
 
- Public Member Functions inherited from OpenCVForUnity.DisposableObject
void Dispose ()
 
void ThrowIfDisposed ()
 

Static Public Member Functions

static new RICInterpolator __fromPtr__ (IntPtr addr)
 
- Static Public Member Functions inherited from OpenCVForUnity.XimgprocModule.SparseMatchInterpolator
static new SparseMatchInterpolator __fromPtr__ (IntPtr addr)
 
- Static Public Member Functions inherited from OpenCVForUnity.CoreModule.Algorithm
static Algorithm __fromPtr__ (IntPtr addr)
 
- Static Public Member Functions inherited from OpenCVForUnity.DisposableObject
static IntPtr ThrowIfNullIntPtr (IntPtr ptr)
 

Protected Member Functions

override void Dispose (bool disposing)
 
- Protected Member Functions inherited from OpenCVForUnity.XimgprocModule.SparseMatchInterpolator
override void Dispose (bool disposing)
 
- Protected Member Functions inherited from OpenCVForUnity.DisposableOpenCVObject
 DisposableOpenCVObject ()
 
 DisposableOpenCVObject (IntPtr ptr)
 
 DisposableOpenCVObject (bool isEnabledDispose)
 
 DisposableOpenCVObject (IntPtr ptr, bool isEnabledDispose)
 
- Protected Member Functions inherited from OpenCVForUnity.DisposableObject
 DisposableObject ()
 
 DisposableObject (bool isEnabledDispose)
 

Additional Inherited Members

- Properties inherited from OpenCVForUnity.DisposableObject
bool IsDisposed [get, protected set]
 
bool IsEnabledDispose [get, set]
 

Detailed Description

Sparse match interpolation algorithm based on modified piecewise locally-weighted affine estimator called Robust Interpolation method of Correspondences or RIC from [Hu2017] and Variational and Fast Global Smoother as post-processing filter. The RICInterpolator is a extension of the EdgeAwareInterpolator. Main concept of this extension is an piece-wise affine model based on over-segmentation via SLIC superpixel estimation. The method contains an efficient propagation mechanism to estimate among the pieces-wise models.

Member Function Documentation

◆ __fromPtr__()

static new RICInterpolator OpenCVForUnity.XimgprocModule.RICInterpolator.__fromPtr__ ( IntPtr  addr)
static

◆ Dispose()

override void OpenCVForUnity.XimgprocModule.RICInterpolator.Dispose ( bool  disposing)
protectedvirtual

◆ getAlpha()

float OpenCVForUnity.XimgprocModule.RICInterpolator.getAlpha ( )

Alpha is a parameter defining a global weight for transforming geodesic distance into weight.

See also
setAlpha

◆ getFGSLambda()

float OpenCVForUnity.XimgprocModule.RICInterpolator.getFGSLambda ( )

Sets the respective fastGlobalSmootherFilter() parameter.

See also
setFGSLambda

◆ getFGSSigma()

float OpenCVForUnity.XimgprocModule.RICInterpolator.getFGSSigma ( )

Sets the respective fastGlobalSmootherFilter() parameter.

See also
setFGSSigma

◆ getK()

int OpenCVForUnity.XimgprocModule.RICInterpolator.getK ( )

K is a number of nearest-neighbor matches considered, when fitting a locally affine model for a superpixel segment. However, lower values would make the interpolation noticeably faster. The original implementation of [Hu2017] uses 32.

See also
setK

◆ getMaxFlow()

float OpenCVForUnity.XimgprocModule.RICInterpolator.getMaxFlow ( )

MaxFlow is a threshold to validate the predictions using a certain piece-wise affine model. If the prediction exceeds the treshold the translational model will be applied instead.

See also
setMaxFlow

◆ getModelIter()

int OpenCVForUnity.XimgprocModule.RICInterpolator.getModelIter ( )

Parameter defining the number of iterations for piece-wise affine model estimation.

See also
setModelIter

◆ getRefineModels()

bool OpenCVForUnity.XimgprocModule.RICInterpolator.getRefineModels ( )

Parameter to choose wether additional refinement of the piece-wise affine models is employed.

See also
setRefineModels

◆ getSuperpixelMode()

int OpenCVForUnity.XimgprocModule.RICInterpolator.getSuperpixelMode ( )

Parameter to choose superpixel algorithm variant to use:

See also
setSuperpixelMode

◆ getSuperpixelNNCnt()

int OpenCVForUnity.XimgprocModule.RICInterpolator.getSuperpixelNNCnt ( )

Parameter defines the number of nearest-neighbor matches for each superpixel considered, when fitting a locally affine model.

See also
setSuperpixelNNCnt

◆ getSuperpixelRuler()

float OpenCVForUnity.XimgprocModule.RICInterpolator.getSuperpixelRuler ( )

Parameter to tune enforcement of superpixel smoothness factor used for oversegmentation.

See also
setSuperpixelRuler

◆ getSuperpixelSize()

int OpenCVForUnity.XimgprocModule.RICInterpolator.getSuperpixelSize ( )

Get the internal cost, i.e. edge map, used for estimating the edge-aware term.

See also
setSuperpixelSize

◆ getUseGlobalSmootherFilter()

bool OpenCVForUnity.XimgprocModule.RICInterpolator.getUseGlobalSmootherFilter ( )

Sets whether the fastGlobalSmootherFilter() post-processing is employed.

See also
setUseGlobalSmootherFilter

◆ getUseVariationalRefinement()

bool OpenCVForUnity.XimgprocModule.RICInterpolator.getUseVariationalRefinement ( )

Parameter to choose wether the VariationalRefinement post-processing is employed.

See also
setUseVariationalRefinement

◆ setAlpha() [1/2]

void OpenCVForUnity.XimgprocModule.RICInterpolator.setAlpha ( float  alpha)

Alpha is a parameter defining a global weight for transforming geodesic distance into weight.

◆ setAlpha() [2/2]

void OpenCVForUnity.XimgprocModule.RICInterpolator.setAlpha ( )

Alpha is a parameter defining a global weight for transforming geodesic distance into weight.

◆ setCostMap()

void OpenCVForUnity.XimgprocModule.RICInterpolator.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.

Parameters
costMapa type CV_32FC1 Mat is required.
See also
cv::ximgproc::createSuperpixelSLIC

◆ setFGSLambda() [1/2]

void OpenCVForUnity.XimgprocModule.RICInterpolator.setFGSLambda ( float  lambda)

Sets the respective fastGlobalSmootherFilter() parameter.

◆ setFGSLambda() [2/2]

void OpenCVForUnity.XimgprocModule.RICInterpolator.setFGSLambda ( )

Sets the respective fastGlobalSmootherFilter() parameter.

◆ setFGSSigma() [1/2]

void OpenCVForUnity.XimgprocModule.RICInterpolator.setFGSSigma ( float  sigma)

Sets the respective fastGlobalSmootherFilter() parameter.

◆ setFGSSigma() [2/2]

void OpenCVForUnity.XimgprocModule.RICInterpolator.setFGSSigma ( )

Sets the respective fastGlobalSmootherFilter() parameter.

◆ setK() [1/2]

void OpenCVForUnity.XimgprocModule.RICInterpolator.setK ( int  k)

K is a number of nearest-neighbor matches considered, when fitting a locally affine model for a superpixel segment. However, lower values would make the interpolation noticeably faster. The original implementation of [Hu2017] uses 32.

◆ setK() [2/2]

void OpenCVForUnity.XimgprocModule.RICInterpolator.setK ( )

K is a number of nearest-neighbor matches considered, when fitting a locally affine model for a superpixel segment. However, lower values would make the interpolation noticeably faster. The original implementation of [Hu2017] uses 32.

◆ setMaxFlow() [1/2]

void OpenCVForUnity.XimgprocModule.RICInterpolator.setMaxFlow ( float  maxFlow)

MaxFlow is a threshold to validate the predictions using a certain piece-wise affine model. If the prediction exceeds the treshold the translational model will be applied instead.

◆ setMaxFlow() [2/2]

void OpenCVForUnity.XimgprocModule.RICInterpolator.setMaxFlow ( )

MaxFlow is a threshold to validate the predictions using a certain piece-wise affine model. If the prediction exceeds the treshold the translational model will be applied instead.

◆ setModelIter() [1/2]

void OpenCVForUnity.XimgprocModule.RICInterpolator.setModelIter ( int  modelIter)

Parameter defining the number of iterations for piece-wise affine model estimation.

◆ setModelIter() [2/2]

void OpenCVForUnity.XimgprocModule.RICInterpolator.setModelIter ( )

Parameter defining the number of iterations for piece-wise affine model estimation.

◆ setRefineModels() [1/2]

void OpenCVForUnity.XimgprocModule.RICInterpolator.setRefineModels ( bool  refineModles)

Parameter to choose wether additional refinement of the piece-wise affine models is employed.

◆ setRefineModels() [2/2]

void OpenCVForUnity.XimgprocModule.RICInterpolator.setRefineModels ( )

Parameter to choose wether additional refinement of the piece-wise affine models is employed.

◆ setSuperpixelMode() [1/2]

void OpenCVForUnity.XimgprocModule.RICInterpolator.setSuperpixelMode ( int  mode)

Parameter to choose superpixel algorithm variant to use:

  • cv::ximgproc::SLICType SLIC segments image using a desired region_size (value: 100)
  • cv::ximgproc::SLICType SLICO will optimize using adaptive compactness factor (value: 101)
  • cv::ximgproc::SLICType MSLIC will optimize using manifold methods resulting in more content-sensitive superpixels (value: 102).
    See also
    cv::ximgproc::createSuperpixelSLIC

◆ setSuperpixelMode() [2/2]

void OpenCVForUnity.XimgprocModule.RICInterpolator.setSuperpixelMode ( )

Parameter to choose superpixel algorithm variant to use:

  • cv::ximgproc::SLICType SLIC segments image using a desired region_size (value: 100)
  • cv::ximgproc::SLICType SLICO will optimize using adaptive compactness factor (value: 101)
  • cv::ximgproc::SLICType MSLIC will optimize using manifold methods resulting in more content-sensitive superpixels (value: 102).
    See also
    cv::ximgproc::createSuperpixelSLIC

◆ setSuperpixelNNCnt() [1/2]

void OpenCVForUnity.XimgprocModule.RICInterpolator.setSuperpixelNNCnt ( int  spNN)

Parameter defines the number of nearest-neighbor matches for each superpixel considered, when fitting a locally affine model.

◆ setSuperpixelNNCnt() [2/2]

void OpenCVForUnity.XimgprocModule.RICInterpolator.setSuperpixelNNCnt ( )

Parameter defines the number of nearest-neighbor matches for each superpixel considered, when fitting a locally affine model.

◆ setSuperpixelRuler() [1/2]

void OpenCVForUnity.XimgprocModule.RICInterpolator.setSuperpixelRuler ( float  ruler)

Parameter to tune enforcement of superpixel smoothness factor used for oversegmentation.

See also
cv::ximgproc::createSuperpixelSLIC

◆ setSuperpixelRuler() [2/2]

void OpenCVForUnity.XimgprocModule.RICInterpolator.setSuperpixelRuler ( )

Parameter to tune enforcement of superpixel smoothness factor used for oversegmentation.

See also
cv::ximgproc::createSuperpixelSLIC

◆ setSuperpixelSize() [1/2]

void OpenCVForUnity.XimgprocModule.RICInterpolator.setSuperpixelSize ( int  spSize)

Get the internal cost, i.e. edge map, used for estimating the edge-aware term.

See also
setCostMap

◆ setSuperpixelSize() [2/2]

void OpenCVForUnity.XimgprocModule.RICInterpolator.setSuperpixelSize ( )

Get the internal cost, i.e. edge map, used for estimating the edge-aware term.

See also
setCostMap

◆ setUseGlobalSmootherFilter() [1/2]

void OpenCVForUnity.XimgprocModule.RICInterpolator.setUseGlobalSmootherFilter ( bool  use_FGS)

Sets whether the fastGlobalSmootherFilter() post-processing is employed.

◆ setUseGlobalSmootherFilter() [2/2]

void OpenCVForUnity.XimgprocModule.RICInterpolator.setUseGlobalSmootherFilter ( )

Sets whether the fastGlobalSmootherFilter() post-processing is employed.

◆ setUseVariationalRefinement() [1/2]

void OpenCVForUnity.XimgprocModule.RICInterpolator.setUseVariationalRefinement ( bool  use_variational_refinement)

Parameter to choose wether the VariationalRefinement post-processing is employed.

◆ setUseVariationalRefinement() [2/2]

void OpenCVForUnity.XimgprocModule.RICInterpolator.setUseVariationalRefinement ( )

Parameter to choose wether the VariationalRefinement post-processing is employed.


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