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186 lines
8.5 KiB
C++
186 lines
8.5 KiB
C++
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/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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//
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// By downloading, copying, installing or using the software you agree to this license.
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// If you do not agree to this license, do not download, install,
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// copy or use the software.
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//
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//
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// License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
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// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
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// Third party copyrights are property of their respective owners.
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//
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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//
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// * Redistribution's of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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//
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// * Redistribution's in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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//
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// * The name of the copyright holders may not be used to endorse or promote products
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// derived from this software without specific prior written permission.
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//
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// This software is provided by the copyright holders and contributors "as is" and
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// any express or implied warranties, including, but not limited to, the implied
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// In no event shall the Intel Corporation or contributors be liable for any direct,
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// indirect, incidental, special, exemplary, or consequential damages
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// (including, but not limited to, procurement of substitute goods or services;
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// loss of use, data, or profits; or business interruption) however caused
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// and on any theory of liability, whether in contract, strict liability,
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// or tort (including negligence or otherwise) arising in any way out of
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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#include "test_precomp.hpp"
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#include "opencv2/highgui/highgui.hpp"
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using namespace cv;
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using namespace std;
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class CV_GrfmtWriteBigImageTest : public cvtest::BaseTest
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{
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public:
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void run(int)
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{
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try
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{
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ts->printf(cvtest::TS::LOG, "start reading big image\n");
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Mat img = imread(string(ts->get_data_path()) + "readwrite/read.png");
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ts->printf(cvtest::TS::LOG, "finish reading big image\n");
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if (img.empty()) ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_TEST_DATA);
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ts->printf(cvtest::TS::LOG, "start writing big image\n");
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imwrite(string(ts->get_data_path()) + "readwrite/write.png", img);
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ts->printf(cvtest::TS::LOG, "finish writing big image\n");
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}
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catch(...)
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{
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ts->set_failed_test_info(cvtest::TS::FAIL_EXCEPTION);
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}
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ts->set_failed_test_info(cvtest::TS::OK);
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}
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};
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string ext_from_int(int ext)
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{
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if (ext == 0) return ".png";
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if (ext == 1) return ".bmp";
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if (ext == 2) return ".pgm";
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if (ext == 3) return ".tiff";
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return "";
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}
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class CV_GrfmtWriteSequenceImageTest : public cvtest::BaseTest
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{
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public:
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void run(int)
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{
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try
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{
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const int img_r = 640;
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const int img_c = 480;
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for (int k = 1; k <= 5; ++k)
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{
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for (int ext = 0; ext < 4; ++ext) // 0 - png, 1 - bmp, 2 - pgm, 3 - tiff
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for (int num_channels = 1; num_channels <= 3; num_channels+=2)
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{
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ts->printf(ts->LOG, "image type depth:%d channels:%d ext: %s\n", CV_8U, num_channels, ext_from_int(ext).c_str());
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Mat img(img_r * k, img_c * k, CV_MAKETYPE(CV_8U, num_channels), Scalar::all(0));
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circle(img, Point2i((img_c * k) / 2, (img_r * k) / 2), cv::min((img_r * k), (img_c * k)) / 4 , Scalar::all(255));
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ts->printf(ts->LOG, "writing image : %s\n", string(string(ts->get_data_path()) + "readwrite/test" + ext_from_int(ext)).c_str());
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imwrite(string(ts->get_data_path()) + "readwrite/test" + ext_from_int(ext), img);
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ts->printf(ts->LOG, "reading test image : %s\n", string(string(ts->get_data_path()) + "readwrite/test" + ext_from_int(ext)).c_str());
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Mat img_test = imread(string(ts->get_data_path()) + "readwrite/test" + ext_from_int(ext), CV_LOAD_IMAGE_UNCHANGED);
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if (img_test.empty()) ts->set_failed_test_info(ts->FAIL_MISMATCH);
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CV_Assert(img.size() == img_test.size());
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CV_Assert(img.type() == img_test.type());
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double n = norm(img, img_test);
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if ( n > 1.0)
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{
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ts->printf(ts->LOG, "norm = %f \n", n);
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ts->set_failed_test_info(ts->FAIL_MISMATCH);
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}
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}
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for (int num_channels = 1; num_channels <= 3; num_channels+=2)
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{
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// jpeg
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ts->printf(ts->LOG, "image type depth:%d channels:%d ext: %s\n", CV_8U, num_channels, ".jpg");
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Mat img(img_r * k, img_c * k, CV_MAKETYPE(CV_8U, num_channels), Scalar::all(0));
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circle(img, Point2i((img_c * k) / 2, (img_r * k) / 2), cv::min((img_r * k), (img_c * k)) / 4 , Scalar::all(255));
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string filename = string(ts->get_data_path() + "readwrite/test_" + char(k + 48) + "_c" + char(num_channels + 48) + "_.jpg");
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imwrite(filename, img);
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img = imread(filename, CV_LOAD_IMAGE_UNCHANGED);
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filename = string(ts->get_data_path() + "readwrite/test_" + char(k + 48) + "_c" + char(num_channels + 48) + ".jpg");
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ts->printf(ts->LOG, "reading test image : %s\n", filename.c_str());
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Mat img_test = imread(filename, CV_LOAD_IMAGE_UNCHANGED);
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if (img_test.empty()) ts->set_failed_test_info(ts->FAIL_MISMATCH);
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CV_Assert(img.size() == img_test.size());
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CV_Assert(img.type() == img_test.type());
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double n = norm(img, img_test);
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if ( n > 1.0)
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{
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ts->printf(ts->LOG, "norm = %f \n", n);
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ts->set_failed_test_info(ts->FAIL_MISMATCH);
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}
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}
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for (int num_channels = 1; num_channels <= 3; num_channels+=2)
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{
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// tiff
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ts->printf(ts->LOG, "image type depth:%d channels:%d ext: %s\n", CV_16U, num_channels, ".tiff");
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Mat img(img_r * k, img_c * k, CV_MAKETYPE(CV_16U, num_channels), Scalar::all(0));
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circle(img, Point2i((img_c * k) / 2, (img_r * k) / 2), cv::min((img_r * k), (img_c * k)) / 4 , Scalar::all(255));
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string filename = string(ts->get_data_path() + "readwrite/test.tiff");
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imwrite(filename, img);
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ts->printf(ts->LOG, "reading test image : %s\n", filename.c_str());
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Mat img_test = imread(filename, CV_LOAD_IMAGE_UNCHANGED);
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if (img_test.empty()) ts->set_failed_test_info(ts->FAIL_MISMATCH);
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CV_Assert(img.size() == img_test.size());
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ts->printf(ts->LOG, "img : %d ; %d \n", img.channels(), img.depth());
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ts->printf(ts->LOG, "img_test : %d ; %d \n", img_test.channels(), img_test.depth());
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CV_Assert(img.type() == img_test.type());
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double n = norm(img, img_test);
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if ( n > 1.0)
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{
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ts->printf(ts->LOG, "norm = %f \n", n);
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ts->set_failed_test_info(ts->FAIL_MISMATCH);
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}
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}
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}
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}
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catch(const cv::Exception & e)
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{
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ts->printf(ts->LOG, "Exception: %s\n" , e.what());
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ts->set_failed_test_info(ts->FAIL_MISMATCH);
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}
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}
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};
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TEST(Highgui_Grfmt_WriteBigImage, regression) { CV_GrfmtWriteBigImageTest test; test.safe_run(); }
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TEST(Highgui_Grfmt_WriteSequenceImage, regression) { CV_GrfmtWriteSequenceImageTest test; test.safe_run(); }
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