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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) 2013, OpenCV Foundation, 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_TLD_DETECTOR
#define OPENCV_TLD_DETECTOR
#include "precomp.hpp"
#include "opencl_kernels_tracking.hpp"
#include "tldEnsembleClassifier.hpp"
#include "tldUtils.hpp"
namespace cv
{
namespace tld
{
const int STANDARD_PATCH_SIZE = 15;
const int NEG_EXAMPLES_IN_INIT_MODEL = 300;
const int MAX_EXAMPLES_IN_MODEL = 500;
const int MEASURES_PER_CLASSIFIER = 13;
const int GRIDSIZE = 15;
const int DOWNSCALE_MODE = cv::INTER_LINEAR;
const double THETA_NN = 0.50;
const double CORE_THRESHOLD = 0.5;
const double SCALE_STEP = 1.2;
const double ENSEMBLE_THRESHOLD = 0.5;
const double VARIANCE_THRESHOLD = 0.5;
const double NEXPERT_THRESHOLD = 0.2;
static const cv::Size GaussBlurKernelSize(3, 3);
class TLDDetector
{
public:
TLDDetector(){}
~TLDDetector(){}
double ensembleClassifierNum(const uchar* data);
void prepareClassifiers(int rowstep);
double Sr(const Mat_<uchar>& patch);
double Sc(const Mat_<uchar>& patch);
#ifdef HAVE_OPENCL
double ocl_Sr(const Mat_<uchar>& patch);
double ocl_Sc(const Mat_<uchar>& patch);
void ocl_batchSrSc(const Mat_<uchar>& patches, double *resultSr, double *resultSc, int numOfPatches);
#endif
std::vector<TLDEnsembleClassifier> classifiers;
Mat *posExp, *negExp;
int *posNum, *negNum;
std::vector<Mat_<uchar> > *positiveExamples, *negativeExamples;
std::vector<int> *timeStampsPositive, *timeStampsNegative;
double *originalVariancePtr;
static void generateScanGrid(int rows, int cols, Size initBox, std::vector<Rect2d>& res, bool withScaling = false);
struct LabeledPatch
{
Rect2d rect;
bool isObject, shouldBeIntegrated;
};
bool detect(const Mat& img, const Mat& imgBlurred, Rect2d& res, std::vector<LabeledPatch>& patches, Size initSize);
bool ocl_detect(const Mat& img, const Mat& imgBlurred, Rect2d& res, std::vector<LabeledPatch>& patches, Size initSize);
friend class MyMouseCallbackDEBUG;
static void computeIntegralImages(const Mat& img, Mat_<double>& intImgP, Mat_<double>& intImgP2){ integral(img, intImgP, intImgP2, CV_64F); }
static inline bool patchVariance(Mat_<double>& intImgP, Mat_<double>& intImgP2, double *originalVariance, Point pt, Size size);
};
}
}
#endif