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/*
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* If you do not agree to this license, do not download, install,
* copy or use the software.
*
*
* License Agreement
* For Open Source Computer Vision Library
* (3 - clause BSD License)
*
* Redistribution and use in source and binary forms, with or without modification,
* are permitted provided that the following conditions are met :
*
* * Redistributions of source code must retain the above copyright notice,
* this list of conditions and the following disclaimer.
*
* * Redistributions in binary form must reproduce the above copyright notice,
* this list of conditions and the following disclaimer in the documentation
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* may be used to endorse or promote products derived from this software
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* This software is provided by the copyright holders and contributors "as is" and
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* warranties of merchantability and fitness for a particular purpose are disclaimed.
* In no event shall copyright holders or contributors be liable for any direct,
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*/
#ifndef __OPENCV_SPARSEMATCHINTERPOLATOR_HPP__
#define __OPENCV_SPARSEMATCHINTERPOLATOR_HPP__
#ifdef __cplusplus
#include <opencv2/core.hpp>
namespace cv {
namespace ximgproc {
//! @addtogroup ximgproc_filters
//! @{
/** @brief Main interface for all filters, that take sparse matches as an
input and produce a dense per-pixel matching (optical flow) as an output.
*/
class CV_EXPORTS_W SparseMatchInterpolator : public Algorithm
{
public:
/** @brief Interpolate input sparse matches.
@param from_image first of the two matched images, 8-bit single-channel or three-channel.
@param from_points points of the from_image for which there are correspondences in the
to_image (Point2f vector, size shouldn't exceed 32767)
@param to_image second of the two matched images, 8-bit single-channel or three-channel.
@param to_points points in the to_image corresponding to from_points
(Point2f vector, size shouldn't exceed 32767)
@param dense_flow output dense matching (two-channel CV_32F image)
*/
CV_WRAP virtual void interpolate(InputArray from_image, InputArray from_points,
InputArray to_image , InputArray to_points,
OutputArray dense_flow) = 0;
};
/** @brief Sparse match interpolation algorithm based on modified locally-weighted affine
estimator from @cite Revaud2015 and Fast Global Smoother as post-processing filter.
*/
class CV_EXPORTS_W EdgeAwareInterpolator : public SparseMatchInterpolator
{
public:
/** @brief 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.
*/
CV_WRAP virtual void setK(int _k) = 0;
/** @see setK */
CV_WRAP virtual int getK() = 0;
/** @brief 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.
*/
CV_WRAP virtual void setSigma(float _sigma) = 0;
/** @see setSigma */
CV_WRAP virtual float getSigma() = 0;
/** @brief Lambda is a parameter defining the weight of the edge-aware term in geodesic distance,
should be in the range of 0 to 1000.
*/
CV_WRAP virtual void setLambda(float _lambda) = 0;
/** @see setLambda */
CV_WRAP virtual float getLambda() = 0;
/** @brief Sets whether the fastGlobalSmootherFilter() post-processing is employed. It is turned on by
default.
*/
CV_WRAP virtual void setUsePostProcessing(bool _use_post_proc) = 0;
/** @see setUsePostProcessing */
CV_WRAP virtual bool getUsePostProcessing() = 0;
/** @brief Sets the respective fastGlobalSmootherFilter() parameter.
*/
CV_WRAP virtual void setFGSLambda(float _lambda) = 0;
/** @see setFGSLambda */
CV_WRAP virtual float getFGSLambda() = 0;
/** @see setFGSLambda */
CV_WRAP virtual void setFGSSigma(float _sigma) = 0;
/** @see setFGSLambda */
CV_WRAP virtual float getFGSSigma() = 0;
};
/** @brief Factory method that creates an instance of the
EdgeAwareInterpolator.
*/
CV_EXPORTS_W
Ptr<EdgeAwareInterpolator> createEdgeAwareInterpolator();
//! @}
}
}
#endif
#endif