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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 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();

//! @}

} //optflow
}

#include "opencv2/optflow/motempl.hpp"

#endif