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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// 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
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __OPENCV_PRECOMP_H__
#define __OPENCV_PRECOMP_H__
#include "opencv2/calib3d.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/features2d.hpp"
#include "opencv2/core/utility.hpp"
#include "opencv2/core/private.hpp"
#include "opencv2/core/ocl.hpp"
#ifdef HAVE_TEGRA_OPTIMIZATION
#include "opencv2/calib3d/calib3d_tegra.hpp"
#else
#define GET_OPTIMIZED(func) (func)
#endif
namespace cv
{
/**
* Compute the number of iterations given the confidence, outlier ratio, number
* of model points and the maximum iteration number.
*
* @param p confidence value
* @param ep outlier ratio
* @param modelPoints number of model points required for estimation
* @param maxIters maximum number of iterations
* @return
* \f[
* \frac{\ln(1-p)}{\ln\left(1-(1-ep)^\mathrm{modelPoints}\right)}
* \f]
*
* If the computed number of iterations is larger than maxIters, then maxIters is returned.
*/
int RANSACUpdateNumIters( double p, double ep, int modelPoints, int maxIters );
class CV_EXPORTS LMSolver : public Algorithm
{
public:
class CV_EXPORTS Callback
{
public:
virtual ~Callback() {}
virtual bool compute(InputArray param, OutputArray err, OutputArray J) const = 0;
};
virtual void setCallback(const Ptr<LMSolver::Callback>& cb) = 0;
virtual int run(InputOutputArray _param0) const = 0;
};
CV_EXPORTS Ptr<LMSolver> createLMSolver(const Ptr<LMSolver::Callback>& cb, int maxIters);
class CV_EXPORTS PointSetRegistrator : public Algorithm
{
public:
class CV_EXPORTS Callback
{
public:
virtual ~Callback() {}
virtual int runKernel(InputArray m1, InputArray m2, OutputArray model) const = 0;
virtual void computeError(InputArray m1, InputArray m2, InputArray model, OutputArray err) const = 0;
virtual bool checkSubset(InputArray, InputArray, int) const { return true; }
};
virtual void setCallback(const Ptr<PointSetRegistrator::Callback>& cb) = 0;
virtual bool run(InputArray m1, InputArray m2, OutputArray model, OutputArray mask) const = 0;
};
CV_EXPORTS Ptr<PointSetRegistrator> createRANSACPointSetRegistrator(const Ptr<PointSetRegistrator::Callback>& cb,
int modelPoints, double threshold,
double confidence=0.99, int maxIters=1000 );
CV_EXPORTS Ptr<PointSetRegistrator> createLMeDSPointSetRegistrator(const Ptr<PointSetRegistrator::Callback>& cb,
int modelPoints, double confidence=0.99, int maxIters=1000 );
template<typename T> inline int compressElems( T* ptr, const uchar* mask, int mstep, int count )
{
int i, j;
for( i = j = 0; i < count; i++ )
if( mask[i*mstep] )
{
if( i > j )
ptr[j] = ptr[i];
j++;
}
return j;
}
static inline bool haveCollinearPoints( const Mat& m, int count )
{
int j, k, i = count-1;
const Point2f* ptr = m.ptr<Point2f>();
// check that the i-th selected point does not belong
// to a line connecting some previously selected points
// also checks that points are not too close to each other
for( j = 0; j < i; j++ )
{
double dx1 = ptr[j].x - ptr[i].x;
double dy1 = ptr[j].y - ptr[i].y;
for( k = 0; k < j; k++ )
{
double dx2 = ptr[k].x - ptr[i].x;
double dy2 = ptr[k].y - ptr[i].y;
if( fabs(dx2*dy1 - dy2*dx1) <= FLT_EPSILON*(fabs(dx1) + fabs(dy1) + fabs(dx2) + fabs(dy2)))
return true;
}
}
return false;
}
} // namespace cv
int checkChessboard(const cv::Mat & img, const cv::Size & size);
int checkChessboardBinary(const cv::Mat & img, const cv::Size & size);
#endif