/*
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* If you do not agree to this license, do not download, install,
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* copy or use the software.
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*
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*
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* License Agreement
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* For Open Source Computer Vision Library
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* (3 - clause BSD License)
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*
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* Redistribution and use in source and binary forms, with or without modification,
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* are permitted provided that the following conditions are met :
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* * Redistributions of source code must retain the above copyright notice,
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* this list of conditions and the following disclaimer.
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* * Redistributions in binary form must reproduce the above copyright notice,
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* this list of conditions and the following disclaimer in the documentation
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* * Neither the names of the copyright holders nor the names of the contributors
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* without specific prior written permission.
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* This software is provided by the copyright holders and contributors "as is" and
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*/
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#ifndef __OPENCV_SPARSEMATCHINTERPOLATOR_HPP__
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#define __OPENCV_SPARSEMATCHINTERPOLATOR_HPP__
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#ifdef __cplusplus
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#include <opencv2/core.hpp>
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namespace cv {
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namespace ximgproc {
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//! @addtogroup ximgproc_filters
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//! @{
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/** @brief Main interface for all filters, that take sparse matches as an
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input and produce a dense per-pixel matching (optical flow) as an output.
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*/
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class CV_EXPORTS_W SparseMatchInterpolator : public Algorithm
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{
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public:
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/** @brief Interpolate input sparse matches.
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@param from_image first of the two matched images, 8-bit single-channel or three-channel.
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@param from_points points of the from_image for which there are correspondences in the
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to_image (Point2f vector, size shouldn't exceed 32767)
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@param to_image second of the two matched images, 8-bit single-channel or three-channel.
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@param to_points points in the to_image corresponding to from_points
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(Point2f vector, size shouldn't exceed 32767)
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@param dense_flow output dense matching (two-channel CV_32F image)
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*/
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CV_WRAP virtual void interpolate(InputArray from_image, InputArray from_points,
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InputArray to_image , InputArray to_points,
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OutputArray dense_flow) = 0;
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};
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/** @brief Sparse match interpolation algorithm based on modified locally-weighted affine
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estimator from @cite Revaud2015 and Fast Global Smoother as post-processing filter.
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*/
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class CV_EXPORTS_W EdgeAwareInterpolator : public SparseMatchInterpolator
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{
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public:
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/** @brief K is a number of nearest-neighbor matches considered, when fitting a locally affine
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model. Usually it should be around 128. However, lower values would make the interpolation
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noticeably faster.
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*/
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CV_WRAP virtual void setK(int _k) = 0;
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/** @see setK */
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CV_WRAP virtual int getK() = 0;
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/** @brief Sigma is a parameter defining how fast the weights decrease in the locally-weighted affine
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fitting. Higher values can help preserve fine details, lower values can help to get rid of noise in the
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output flow.
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*/
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CV_WRAP virtual void setSigma(float _sigma) = 0;
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/** @see setSigma */
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CV_WRAP virtual float getSigma() = 0;
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/** @brief Lambda is a parameter defining the weight of the edge-aware term in geodesic distance,
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should be in the range of 0 to 1000.
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*/
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CV_WRAP virtual void setLambda(float _lambda) = 0;
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/** @see setLambda */
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CV_WRAP virtual float getLambda() = 0;
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/** @brief Sets whether the fastGlobalSmootherFilter() post-processing is employed. It is turned on by
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default.
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*/
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CV_WRAP virtual void setUsePostProcessing(bool _use_post_proc) = 0;
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/** @see setUsePostProcessing */
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CV_WRAP virtual bool getUsePostProcessing() = 0;
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/** @brief Sets the respective fastGlobalSmootherFilter() parameter.
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*/
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CV_WRAP virtual void setFGSLambda(float _lambda) = 0;
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/** @see setFGSLambda */
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CV_WRAP virtual float getFGSLambda() = 0;
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/** @see setFGSLambda */
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CV_WRAP virtual void setFGSSigma(float _sigma) = 0;
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/** @see setFGSLambda */
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CV_WRAP virtual float getFGSSigma() = 0;
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};
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/** @brief Factory method that creates an instance of the
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EdgeAwareInterpolator.
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*/
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CV_EXPORTS_W
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Ptr<EdgeAwareInterpolator> createEdgeAwareInterpolator();
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//! @}
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}
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}
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#endif
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#endif
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