/*/////////////////////////////////////////////////////////////////////////////////////// // // 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*/ #include "gtrUtils.hpp" namespace cv { namespace gtr { double generateRandomLaplacian(double b, double m) { double t = (double)rand() / (RAND_MAX); double n = (double)rand() / (RAND_MAX); if (t > 0.5) return m + b*log(n); else return m - b*log(n); } Rect2f anno2rect(std::vector<Point2f> annoBB) { Rect2f rectBB; rectBB.x = min(annoBB[0].x, annoBB[1].x); rectBB.y = min(annoBB[0].y, annoBB[2].y); rectBB.width = fabs(annoBB[0].x - annoBB[1].x); rectBB.height = fabs(annoBB[0].y - annoBB[2].y); return rectBB; } std::vector <TrainingSample> gatherFrameSamples(Mat prevFrame, Mat currFrame, Rect2f prevBB, Rect2f currBB) { std::vector <TrainingSample> trainingSamples; Point2f currCenter, prevCenter; Rect2f targetPatchRect, searchPatchRect; Mat targetPatch, searchPatch; Mat prevFramePadded, currFramePadded; //Crop Target Patch //Padding //Previous frame GTBBs center prevCenter.x = prevBB.x + prevBB.width / 2; prevCenter.y = prevBB.y + prevBB.height / 2; targetPatchRect.width = (float)(prevBB.width*padTarget); targetPatchRect.height = (float)(prevBB.height*padTarget); targetPatchRect.x = (float)(prevCenter.x - prevBB.width*padTarget / 2.0 + targetPatchRect.width); targetPatchRect.y = (float)(prevCenter.y - prevBB.height*padTarget / 2.0 + targetPatchRect.height); copyMakeBorder(prevFrame, prevFramePadded, (int)targetPatchRect.height, (int)targetPatchRect.height, (int)targetPatchRect.width, (int)targetPatchRect.width, BORDER_REPLICATE); targetPatch = prevFramePadded(targetPatchRect); for (int i = 0; i < samplesInFrame; i++) { TrainingSample sample; //Current frame GTBBs center currCenter.x = (float)(currBB.x + currBB.width / 2.0); currCenter.y = (float)(currBB.y + currBB.height / 2.0); //Generate and add random Laplacian distribution (Scaling from target size) double dx, dy, ds; dx = generateRandomLaplacian(bX, 0)*prevBB.width; dy = generateRandomLaplacian(bY, 0)*prevBB.height; ds = generateRandomLaplacian(bS, 1); //Limit coefficients dx = min(dx, (double)prevBB.width); dx = max(dx, (double)-prevBB.width); dy = min(dy, (double)prevBB.height); dy = max(dy, (double)-prevBB.height); ds = min(ds, Ymax); ds = max(ds, Ymin); searchPatchRect.width = (float)(prevBB.width*padSearch*ds); searchPatchRect.height =(float)(prevBB.height*padSearch*ds); searchPatchRect.x = (float)(currCenter.x + dx - searchPatchRect.width / 2.0 + searchPatchRect.width); searchPatchRect.y = (float)(currCenter.y + dy - searchPatchRect.height / 2.0 + searchPatchRect.height); copyMakeBorder(currFrame, currFramePadded, (int)searchPatchRect.height, (int)searchPatchRect.height, (int)searchPatchRect.width, (int)searchPatchRect.width, BORDER_REPLICATE); searchPatch = currFramePadded(searchPatchRect); //Calculate Relative GTBB in search patch Rect2f relGTBB; relGTBB.width = currBB.width; relGTBB.height = currBB.height; relGTBB.x = currBB.x - searchPatchRect.x + searchPatchRect.width; relGTBB.y = currBB.y - searchPatchRect.y + searchPatchRect.height; //Link to the sample struct sample.targetPatch = targetPatch.clone(); sample.searchPatch = searchPatch.clone(); sample.targetBB = relGTBB; trainingSamples.push_back(sample); } return trainingSamples; } } }