/*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. // // // Intel License Agreement // For Open Source Computer Vision Library // // Copyright (C) 2000, Intel Corporation, 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 Intel Corporation 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 "precomp.hpp" #define VARNAME(A) #A using namespace std; using namespace cv; using namespace cv::gpu; using namespace cvtest; //std::string generateVarList(int first,...) //{ // vector varname; // // va_list argp; // string s; // stringstream ss; // va_start(argp,first); // int i=first; // while(i!=-1) // { // ss<get_rng(); return rng.uniform(minVal, maxVal); } double randomDouble(double minVal, double maxVal) { RNG &rng = TS::ptr()->get_rng(); return rng.uniform(minVal, maxVal); } Size randomSize(int minVal, int maxVal) { return cv::Size(randomInt(minVal, maxVal), randomInt(minVal, maxVal)); } Scalar randomScalar(double minVal, double maxVal) { return Scalar(randomDouble(minVal, maxVal), randomDouble(minVal, maxVal), randomDouble(minVal, maxVal), randomDouble(minVal, maxVal)); } Mat randomMat(Size size, int type, double minVal, double maxVal) { return randomMat(TS::ptr()->get_rng(), size, type, minVal, maxVal, false); } /* void showDiff(InputArray gold_, InputArray actual_, double eps) { Mat gold; if (gold_.kind() == _InputArray::MAT) gold = gold_.getMat(); else gold_.getGpuMat().download(gold); Mat actual; if (actual_.kind() == _InputArray::MAT) actual = actual_.getMat(); else actual_.getGpuMat().download(actual); Mat diff; absdiff(gold, actual, diff); threshold(diff, diff, eps, 255.0, cv::THRESH_BINARY); namedWindow("gold", WINDOW_NORMAL); namedWindow("actual", WINDOW_NORMAL); namedWindow("diff", WINDOW_NORMAL); imshow("gold", gold); imshow("actual", actual); imshow("diff", diff); waitKey(); } */ vector types(int depth_start, int depth_end, int cn_start, int cn_end) { vector v; v.reserve((depth_end - depth_start + 1) * (cn_end - cn_start + 1)); for (int depth = depth_start; depth <= depth_end; ++depth) { for (int cn = cn_start; cn <= cn_end; ++cn) { v.push_back(CV_MAKETYPE(depth, cn)); } } return v; } const vector &all_types() { static vector v = types(CV_8U, CV_64F, 1, 4); return v; } Mat readImage(const string &fileName, int flags) { return imread(string(cvtest::TS::ptr()->get_data_path()) + fileName, flags); } Mat readImageType(const string &fname, int type) { Mat src = readImage(fname, CV_MAT_CN(type) == 1 ? IMREAD_GRAYSCALE : IMREAD_COLOR); if (CV_MAT_CN(type) == 4) { Mat temp; cvtColor(src, temp, cv::COLOR_BGR2BGRA); swap(src, temp); } src.convertTo(src, CV_MAT_DEPTH(type)); return src; } double checkNorm(const Mat &m) { return norm(m, NORM_INF); } double checkNorm(const Mat &m1, const Mat &m2) { return norm(m1, m2, NORM_INF); } double checkSimilarity(const Mat &m1, const Mat &m2) { Mat diff; matchTemplate(m1, m2, diff, CV_TM_CCORR_NORMED); return std::abs(diff.at(0, 0) - 1.f); } /* void cv::ocl::PrintTo(const DeviceInfo& info, ostream* os) { (*os) << info.name(); } */ void PrintTo(const Inverse &inverse, std::ostream *os) { if (inverse) (*os) << "inverse"; else (*os) << "direct"; } double checkRectSimilarity(Size sz, std::vector& ob1, std::vector& ob2) { double final_test_result = 0.0; size_t sz1 = ob1.size(); size_t sz2 = ob2.size(); if(sz1 != sz2) { return sz1 > sz2 ? (double)(sz1 - sz2) : (double)(sz2 - sz1); } else { if(sz1==0 && sz2==0) return 0; cv::Mat cpu_result(sz, CV_8UC1); cpu_result.setTo(0); for(vector::const_iterator r = ob1.begin(); r != ob1.end(); r++) { cv::Mat cpu_result_roi(cpu_result, *r); cpu_result_roi.setTo(1); cpu_result.copyTo(cpu_result); } int cpu_area = cv::countNonZero(cpu_result > 0); cv::Mat gpu_result(sz, CV_8UC1); gpu_result.setTo(0); for(vector::const_iterator r2 = ob2.begin(); r2 != ob2.end(); r2++) { cv::Mat gpu_result_roi(gpu_result, *r2); gpu_result_roi.setTo(1); gpu_result.copyTo(gpu_result); } cv::Mat result_; multiply(cpu_result, gpu_result, result_); int result = cv::countNonZero(result_ > 0); if(cpu_area!=0 && result!=0) final_test_result = 1.0 - (double)result/(double)cpu_area; else if(cpu_area==0 && result!=0) final_test_result = -1; } return final_test_result; }