/*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(cv::tempfile(".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) { #ifdef HAVE_PNG if (ext == 0) return ".png"; #endif if (ext == 1) return ".bmp"; if (ext == 2) return ".pgm"; #ifdef HAVE_TIFF if (ext == 3) return ".tiff"; #endif 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 { if(ext_from_int(ext).empty()) continue; 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), std::min((img_r * k), (img_c * k)) / 4 , Scalar::all(255)); string img_path = cv::tempfile(ext_from_int(ext).c_str()); ts->printf(ts->LOG, "writing image : %s\n", img_path.c_str()); imwrite(img_path, img); ts->printf(ts->LOG, "reading test image : %s\n", img_path.c_str()); Mat img_test = imread(img_path, 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); } } } #ifdef HAVE_JPEG 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), std::min((img_r * k), (img_c * k)) / 4 , Scalar::all(255)); string filename = cv::tempfile(".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); } } #endif #ifdef HAVE_TIFF 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), std::min((img_r * k), (img_c * k)) / 4 , Scalar::all(255)); string filename = cv::tempfile(".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); } } #endif } } 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); } }; #ifdef HAVE_PNG TEST(Highgui_Image, write_big) { CV_GrfmtWriteBigImageTest test; test.safe_run(); } #endif TEST(Highgui_Image, write_imageseq) { CV_GrfmtWriteSequenceImageTest test; test.safe_run(); } TEST(Highgui_Image, read_bmp_rle8) { CV_GrfmtReadBMPRLE8Test test; test.safe_run(); } #ifdef HAVE_PNG class CV_GrfmtPNGEncodeTest : public cvtest::BaseTest { public: void run(int) { try { vector buff; Mat im = Mat::zeros(1000,1000, CV_8U); //randu(im, 0, 256); vector param; param.push_back(CV_IMWRITE_PNG_COMPRESSION); param.push_back(3); //default(3) 0-9. cv::imencode(".png" ,im ,buff, param); // hangs Mat im2 = imdecode(buff,CV_LOAD_IMAGE_ANYDEPTH); } catch(...) { ts->set_failed_test_info(cvtest::TS::FAIL_EXCEPTION); } ts->set_failed_test_info(cvtest::TS::OK); } }; TEST(Highgui_Image, encode_png) { CV_GrfmtPNGEncodeTest test; test.safe_run(); } TEST(Highgui_ImreadVSCvtColor, regression) { cvtest::TS& ts = *cvtest::TS::ptr(); const int MAX_MEAN_DIFF = 1; const int MAX_ABS_DIFF = 10; string imgName = string(ts.get_data_path()) + "/../cv/shared/lena.png"; Mat original_image = imread(imgName); Mat gray_by_codec = imread(imgName, 0); Mat gray_by_cvt; cvtColor(original_image, gray_by_cvt, CV_BGR2GRAY); Mat diff; absdiff(gray_by_codec, gray_by_cvt, diff); double actual_avg_diff = (double)mean(diff)[0]; double actual_maxval, actual_minval; minMaxLoc(diff, &actual_minval, &actual_maxval); //printf("actual avg = %g, actual maxdiff = %g, npixels = %d\n", actual_avg_diff, actual_maxval, (int)diff.total()); EXPECT_LT(actual_avg_diff, MAX_MEAN_DIFF); EXPECT_LT(actual_maxval, MAX_ABS_DIFF); } #endif #ifdef HAVE_JPEG TEST(Highgui_Jpeg, encode_empty) { cv::Mat img; std::vector jpegImg; ASSERT_THROW(cv::imencode(".jpg", img, jpegImg), cv::Exception); } #endif #ifdef HAVE_TIFF // these defines are used to resolve conflict between tiff.h and opencv2/core/types_c.h #define uint64 uint64_hack_ #define int64 int64_hack_ #include "tiff.h" TEST(Highgui_Tiff, decode_tile16384x16384) { // see issue #2161 cv::Mat big(16384, 16384, CV_8UC1, cv::Scalar::all(0)); string file3 = cv::tempfile(".tiff"); string file4 = cv::tempfile(".tiff"); std::vector params; params.push_back(TIFFTAG_ROWSPERSTRIP); params.push_back(big.rows); cv::imwrite(file4, big, params); cv::imwrite(file3, big.colRange(0, big.cols - 1), params); big.release(); try { cv::imread(file3); EXPECT_NO_THROW(cv::imread(file4)); } catch(const std::bad_alloc&) { // have no enough memory } remove(file3.c_str()); remove(file4.c_str()); } #endif