/*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*/ #include "test_precomp.hpp" #include #include #include using namespace cv; using namespace std; void loadImage(string path, Mat &img) { img = imread(path, -1); ASSERT_FALSE(img.empty()) << "Could not load input image " << path; } void checkEqual(Mat img0, Mat img1, double threshold) { double max = 1.0; minMaxLoc(abs(img0 - img1), NULL, &max); ASSERT_FALSE(max > threshold) << max; } static vector DEFAULT_VECTOR; void loadExposureSeq(String path, vector& images, vector& times = DEFAULT_VECTOR) { ifstream list_file((path + "list.txt").c_str()); ASSERT_TRUE(list_file.is_open()); string name; float val; while(list_file >> name >> val) { Mat img = imread(path + name); ASSERT_FALSE(img.empty()) << "Could not load input image " << path + name; images.push_back(img); times.push_back(1 / val); } list_file.close(); } void loadResponseCSV(String path, Mat& response) { response = Mat(256, 1, CV_32FC3); ifstream resp_file(path); for(int i = 0; i < 256; i++) { for(int c = 0; c < 3; c++) { resp_file >> response.at(i)[c]; resp_file.ignore(1); } } resp_file.close(); } TEST(Photo_Tonemap, regression) { string test_path = string(cvtest::TS::ptr()->get_data_path()) + "hdr/tonemap/"; Mat img, expected, result; loadImage(test_path + "image.hdr", img); float gamma = 2.2f; Ptr linear = createTonemap(gamma); linear->process(img, result); loadImage(test_path + "linear.png", expected); result.convertTo(result, CV_8UC3, 255); checkEqual(result, expected, 3); Ptr drago = createTonemapDrago(gamma); drago->process(img, result); loadImage(test_path + "drago.png", expected); result.convertTo(result, CV_8UC3, 255); checkEqual(result, expected, 3); Ptr durand = createTonemapDurand(gamma); durand->process(img, result); loadImage(test_path + "durand.png", expected); result.convertTo(result, CV_8UC3, 255); checkEqual(result, expected, 3); Ptr reinhard_devlin = createTonemapReinhardDevlin(gamma); reinhard_devlin->process(img, result); loadImage(test_path + "reinharddevlin.png", expected); result.convertTo(result, CV_8UC3, 255); checkEqual(result, expected, 3); Ptr mantiuk = createTonemapMantiuk(gamma); mantiuk->process(img, result); loadImage(test_path + "mantiuk.png", expected); result.convertTo(result, CV_8UC3, 255); checkEqual(result, expected, 3); } TEST(Photo_AlignMTB, regression) { const int TESTS_COUNT = 100; string folder = string(cvtest::TS::ptr()->get_data_path()) + "shared/"; string file_name = folder + "lena.png"; Mat img; loadImage(file_name, img); cvtColor(img, img, COLOR_RGB2GRAY); int max_bits = 5; int max_shift = 32; srand(static_cast(time(0))); int errors = 0; Ptr align = createAlignMTB(max_bits); for(int i = 0; i < TESTS_COUNT; i++) { Point shift(rand() % max_shift, rand() % max_shift); Mat res; align->shiftMat(img, res, shift); Point calc; align->calculateShift(img, res, calc); errors += (calc != -shift); } ASSERT_TRUE(errors < 5) << errors << " errors"; } TEST(Photo_MergeMertens, regression) { string test_path = string(cvtest::TS::ptr()->get_data_path()) + "hdr/"; vector images; loadExposureSeq((test_path + "exposures/").c_str() , images); Ptr merge = createMergeMertens(); Mat result, expected; loadImage(test_path + "merge/mertens.png", expected); merge->process(images, result); result.convertTo(result, CV_8UC3, 255); checkEqual(expected, result, 3); } TEST(Photo_MergeDebevec, regression) { string test_path = string(cvtest::TS::ptr()->get_data_path()) + "hdr/"; vector images; vector times; Mat response; loadExposureSeq(test_path + "exposures/", images, times); loadResponseCSV(test_path + "exposures/response.csv", response); Ptr merge = createMergeDebevec(); Mat result, expected; loadImage(test_path + "merge/debevec.exr", expected); merge->process(images, result, times, response); imwrite("test.exr", result); checkEqual(expected, result, 1e-2f); } TEST(Photo_CalibrateDebevec, regression) { string test_path = string(cvtest::TS::ptr()->get_data_path()) + "hdr/"; vector images; vector times; Mat response, expected; loadExposureSeq(test_path + "exposures/", images, times); loadResponseCSV(test_path + "calibrate/debevec.csv", expected); Ptr calibrate = createCalibrateDebevec(); srand(1); calibrate->process(images, response, times); checkEqual(expected, response, 1e-3f); }