Repository for OpenCV's extra modules
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/*
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For Open Source Computer Vision Library
(3-clause BSD License)
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*/
#ifndef __OPENCV_OPTFLOW_HPP__
#define __OPENCV_OPTFLOW_HPP__
#include "opencv2/core.hpp"
#include "opencv2/video.hpp"
/**
@defgroup optflow Optical Flow Algorithms
Dense optical flow algorithms compute motion for each point:
- cv::optflow::calcOpticalFlowSF
- cv::optflow::createOptFlow_DeepFlow
Motion templates is alternative technique for detecting motion and computing its direction.
See samples/motempl.py.
- cv::motempl::updateMotionHistory
- cv::motempl::calcMotionGradient
- cv::motempl::calcGlobalOrientation
- cv::motempl::segmentMotion
Functions reading and writing .flo files in "Middlebury" format, see: <http://vision.middlebury.edu/flow/code/flow-code/README.txt>
- cv::optflow::readOpticalFlow
- cv::optflow::writeOpticalFlow
*/
namespace cv
{
namespace optflow
{
//! @addtogroup optflow
//! @{
/** @overload */
CV_EXPORTS_W void calcOpticalFlowSF( InputArray from, InputArray to, OutputArray flow,
int layers, int averaging_block_size, int max_flow);
/** @brief Calculate an optical flow using "SimpleFlow" algorithm.
@param from First 8-bit 3-channel image.
@param to Second 8-bit 3-channel image of the same size as prev
@param flow computed flow image that has the same size as prev and type CV_32FC2
@param layers Number of layers
@param averaging_block_size Size of block through which we sum up when calculate cost function
for pixel
@param max_flow maximal flow that we search at each level
@param sigma_dist vector smooth spatial sigma parameter
@param sigma_color vector smooth color sigma parameter
@param postprocess_window window size for postprocess cross bilateral filter
@param sigma_dist_fix spatial sigma for postprocess cross bilateralf filter
@param sigma_color_fix color sigma for postprocess cross bilateral filter
@param occ_thr threshold for detecting occlusions
@param upscale_averaging_radius window size for bilateral upscale operation
@param upscale_sigma_dist spatial sigma for bilateral upscale operation
@param upscale_sigma_color color sigma for bilateral upscale operation
@param speed_up_thr threshold to detect point with irregular flow - where flow should be
recalculated after upscale
See @cite Tao2012 . And site of project - <http://graphics.berkeley.edu/papers/Tao-SAN-2012-05/>.
@note
- An example using the simpleFlow algorithm can be found at samples/simpleflow_demo.cpp
*/
CV_EXPORTS_W void calcOpticalFlowSF( InputArray from, InputArray to, OutputArray flow, int layers,
int averaging_block_size, int max_flow,
double sigma_dist, double sigma_color, int postprocess_window,
double sigma_dist_fix, double sigma_color_fix, double occ_thr,
int upscale_averaging_radius, double upscale_sigma_dist,
double upscale_sigma_color, double speed_up_thr );
/** @brief Fast dense optical flow based on PyrLK sparse matches interpolation.
@param from first 8-bit 3-channel or 1-channel image.
@param to second 8-bit 3-channel or 1-channel image of the same size as from
@param flow computed flow image that has the same size as from and CV_32FC2 type
@param grid_step stride used in sparse match computation. Lower values usually
result in higher quality but slow down the algorithm.
@param k number of nearest-neighbor matches considered, when fitting a locally affine
model. Lower values can make the algorithm noticeably faster at the cost of
some quality degradation.
@param sigma 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 the noise in the output flow.
@param use_post_proc defines whether the ximgproc::fastGlobalSmootherFilter() is used
for post-processing after interpolation
@param fgs_lambda see the respective parameter of the ximgproc::fastGlobalSmootherFilter()
@param fgs_sigma see the respective parameter of the ximgproc::fastGlobalSmootherFilter()
*/
CV_EXPORTS_W void calcOpticalFlowSparseToDense ( InputArray from, InputArray to, OutputArray flow,
int grid_step = 8, int k = 128, float sigma = 0.05f,
bool use_post_proc = true, float fgs_lambda = 500.0f,
float fgs_sigma = 1.5f );
/** @brief Read a .flo file
@param path Path to the file to be loaded
The function readOpticalFlow loads a flow field from a file and returns it as a single matrix.
Resulting Mat has a type CV_32FC2 - floating-point, 2-channel. First channel corresponds to the
flow in the horizontal direction (u), second - vertical (v).
*/
CV_EXPORTS_W Mat readOpticalFlow( const String& path );
/** @brief Write a .flo to disk
@param path Path to the file to be written
@param flow Flow field to be stored
The function stores a flow field in a file, returns true on success, false otherwise.
The flow field must be a 2-channel, floating-point matrix (CV_32FC2). First channel corresponds
to the flow in the horizontal direction (u), second - vertical (v).
*/
CV_EXPORTS_W bool writeOpticalFlow( const String& path, InputArray flow );
/** @brief DeepFlow optical flow algorithm implementation.
The class implements the DeepFlow optical flow algorithm described in @cite Weinzaepfel2013 . See
also <http://lear.inrialpes.fr/src/deepmatching/> .
Parameters - class fields - that may be modified after creating a class instance:
- member float alpha
Smoothness assumption weight
- member float delta
Color constancy assumption weight
- member float gamma
Gradient constancy weight
- member float sigma
Gaussian smoothing parameter
- member int minSize
Minimal dimension of an image in the pyramid (next, smaller images in the pyramid are generated
until one of the dimensions reaches this size)
- member float downscaleFactor
Scaling factor in the image pyramid (must be \< 1)
- member int fixedPointIterations
How many iterations on each level of the pyramid
- member int sorIterations
Iterations of Succesive Over-Relaxation (solver)
- member float omega
Relaxation factor in SOR
*/
CV_EXPORTS_W Ptr<DenseOpticalFlow> createOptFlow_DeepFlow();
//! Additional interface to the SimpleFlow algorithm - calcOpticalFlowSF()
CV_EXPORTS_W Ptr<DenseOpticalFlow> createOptFlow_SimpleFlow();
//! Additional interface to the Farneback's algorithm - calcOpticalFlowFarneback()
CV_EXPORTS_W Ptr<DenseOpticalFlow> createOptFlow_Farneback();
//! Additional interface to the SparseToDenseFlow algorithm - calcOpticalFlowSparseToDense()
CV_EXPORTS_W Ptr<DenseOpticalFlow> createOptFlow_SparseToDense();
//! @}
} //optflow
}
#include "opencv2/optflow/motempl.hpp"
#endif