/*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*/ #include "test_precomp.hpp" #include "opencv2/highgui/highgui.hpp" using namespace cv; using namespace std; class CV_GrfmtWriteBigImageTest : public cvtest::BaseTest { public: void run(int) { try { ts->printf(cvtest::TS::LOG, "start reading big image\n"); Mat img = imread(string(ts->get_data_path()) + "readwrite/read.png"); ts->printf(cvtest::TS::LOG, "finish reading big image\n"); if (img.empty()) ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_TEST_DATA); ts->printf(cvtest::TS::LOG, "start writing big image\n"); imwrite(string(ts->get_data_path()) + "readwrite/write.png", img); ts->printf(cvtest::TS::LOG, "finish writing big image\n"); } catch(...) { ts->set_failed_test_info(cvtest::TS::FAIL_EXCEPTION); } ts->set_failed_test_info(cvtest::TS::OK); } }; string ext_from_int(int ext) { if (ext == 0) return ".png"; if (ext == 1) return ".bmp"; if (ext == 2) return ".pgm"; if (ext == 3) return ".tiff"; return ""; } class CV_GrfmtWriteSequenceImageTest : public cvtest::BaseTest { public: void run(int) { try { const int img_r = 640; const int img_c = 480; for (int k = 1; k <= 5; ++k) { for (int ext = 0; ext < 4; ++ext) // 0 - png, 1 - bmp, 2 - pgm, 3 - tiff for (int num_channels = 1; num_channels <= 3; num_channels+=2) { ts->printf(ts->LOG, "image type depth:%d channels:%d ext: %s\n", CV_8U, num_channels, ext_from_int(ext).c_str()); Mat img(img_r * k, img_c * k, CV_MAKETYPE(CV_8U, num_channels), Scalar::all(0)); circle(img, Point2i((img_c * k) / 2, (img_r * k) / 2), cv::min((img_r * k), (img_c * k)) / 4 , Scalar::all(255)); ts->printf(ts->LOG, "writing image : %s\n", string(string(ts->get_data_path()) + "readwrite/test" + ext_from_int(ext)).c_str()); imwrite(string(ts->get_data_path()) + "readwrite/test" + ext_from_int(ext), img); ts->printf(ts->LOG, "reading test image : %s\n", string(string(ts->get_data_path()) + "readwrite/test" + ext_from_int(ext)).c_str()); Mat img_test = imread(string(ts->get_data_path()) + "readwrite/test" + ext_from_int(ext), CV_LOAD_IMAGE_UNCHANGED); if (img_test.empty()) ts->set_failed_test_info(ts->FAIL_MISMATCH); CV_Assert(img.size() == img_test.size()); CV_Assert(img.type() == img_test.type()); double n = norm(img, img_test); if ( n > 1.0) { ts->printf(ts->LOG, "norm = %f \n", n); ts->set_failed_test_info(ts->FAIL_MISMATCH); } } for (int num_channels = 1; num_channels <= 3; num_channels+=2) { // jpeg ts->printf(ts->LOG, "image type depth:%d channels:%d ext: %s\n", CV_8U, num_channels, ".jpg"); Mat img(img_r * k, img_c * k, CV_MAKETYPE(CV_8U, num_channels), Scalar::all(0)); circle(img, Point2i((img_c * k) / 2, (img_r * k) / 2), cv::min((img_r * k), (img_c * k)) / 4 , Scalar::all(255)); string filename = string(ts->get_data_path() + "readwrite/test_" + char(k + 48) + "_c" + char(num_channels + 48) + "_.jpg"); imwrite(filename, img); img = imread(filename, CV_LOAD_IMAGE_UNCHANGED); filename = string(ts->get_data_path() + "readwrite/test_" + char(k + 48) + "_c" + char(num_channels + 48) + ".jpg"); ts->printf(ts->LOG, "reading test image : %s\n", filename.c_str()); Mat img_test = imread(filename, CV_LOAD_IMAGE_UNCHANGED); if (img_test.empty()) ts->set_failed_test_info(ts->FAIL_MISMATCH); CV_Assert(img.size() == img_test.size()); CV_Assert(img.type() == img_test.type()); double n = norm(img, img_test); if ( n > 1.0) { ts->printf(ts->LOG, "norm = %f \n", n); ts->set_failed_test_info(ts->FAIL_MISMATCH); } } for (int num_channels = 1; num_channels <= 3; num_channels+=2) { // tiff ts->printf(ts->LOG, "image type depth:%d channels:%d ext: %s\n", CV_16U, num_channels, ".tiff"); Mat img(img_r * k, img_c * k, CV_MAKETYPE(CV_16U, num_channels), Scalar::all(0)); circle(img, Point2i((img_c * k) / 2, (img_r * k) / 2), cv::min((img_r * k), (img_c * k)) / 4 , Scalar::all(255)); string filename = string(ts->get_data_path() + "readwrite/test.tiff"); imwrite(filename, img); ts->printf(ts->LOG, "reading test image : %s\n", filename.c_str()); Mat img_test = imread(filename, CV_LOAD_IMAGE_UNCHANGED); if (img_test.empty()) ts->set_failed_test_info(ts->FAIL_MISMATCH); CV_Assert(img.size() == img_test.size()); ts->printf(ts->LOG, "img : %d ; %d \n", img.channels(), img.depth()); ts->printf(ts->LOG, "img_test : %d ; %d \n", img_test.channels(), img_test.depth()); CV_Assert(img.type() == img_test.type()); double n = norm(img, img_test); if ( n > 1.0) { ts->printf(ts->LOG, "norm = %f \n", n); ts->set_failed_test_info(ts->FAIL_MISMATCH); } } } } catch(const cv::Exception & e) { ts->printf(ts->LOG, "Exception: %s\n" , e.what()); ts->set_failed_test_info(ts->FAIL_MISMATCH); } } }; class CV_GrfmtReadBMPRLE8Test : public cvtest::BaseTest { public: void run(int) { try { Mat rle = imread(string(ts->get_data_path()) + "readwrite/rle8.bmp"); Mat bmp = imread(string(ts->get_data_path()) + "readwrite/ordinary.bmp"); if (norm(rle-bmp)>1.e-10) ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY); } catch(...) { ts->set_failed_test_info(cvtest::TS::FAIL_EXCEPTION); } ts->set_failed_test_info(cvtest::TS::OK); } }; TEST(Highgui_Grfmt_WriteBigImage, regression) { CV_GrfmtWriteBigImageTest test; test.safe_run(); } TEST(Highgui_Grfmt_WriteSequenceImage, regression) { CV_GrfmtWriteSequenceImageTest test; test.safe_run(); } TEST(GrfmtReadBMPRLE8, regression) { CV_GrfmtReadBMPRLE8Test test; test.safe_run(); }