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434 lines
14 KiB
C++
434 lines
14 KiB
C++
/*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.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(cv::tempfile(".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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#ifdef HAVE_PNG
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if (ext == 0) return ".png";
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#endif
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if (ext == 1) return ".bmp";
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if (ext == 2) return ".pgm";
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#ifdef HAVE_TIFF
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if (ext == 3) return ".tiff";
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#endif
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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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{
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if(ext_from_int(ext).empty())
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continue;
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for (int num_channels = 1; num_channels <= 4; num_channels++)
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{
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if (num_channels == 2) continue;
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if (num_channels == 4 && ext!=3 /*TIFF*/) continue;
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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), std::min((img_r * k), (img_c * k)) / 4 , Scalar::all(255));
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string img_path = cv::tempfile(ext_from_int(ext).c_str());
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ts->printf(ts->LOG, "writing image : %s\n", img_path.c_str());
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imwrite(img_path, img);
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ts->printf(ts->LOG, "reading test image : %s\n", img_path.c_str());
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Mat img_test = imread(img_path, IMREAD_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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CV_Assert(num_channels == img_test.channels());
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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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#ifdef HAVE_JPEG
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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), std::min((img_r * k), (img_c * k)) / 4 , Scalar::all(255));
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string filename = cv::tempfile(".jpg");
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imwrite(filename, img);
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img = imread(filename, IMREAD_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, IMREAD_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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#endif
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#ifdef HAVE_TIFF
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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), std::min((img_r * k), (img_c * k)) / 4 , Scalar::all(255));
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string filename = cv::tempfile(".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, IMREAD_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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#endif
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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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class CV_GrfmtReadBMPRLE8Test : 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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Mat rle = imread(string(ts->get_data_path()) + "readwrite/rle8.bmp");
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Mat bmp = imread(string(ts->get_data_path()) + "readwrite/ordinary.bmp");
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if (norm(rle-bmp)>1.e-10)
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ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
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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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#ifdef HAVE_PNG
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TEST(Highgui_Image, write_big) { CV_GrfmtWriteBigImageTest test; test.safe_run(); }
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#endif
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TEST(Highgui_Image, write_imageseq) { CV_GrfmtWriteSequenceImageTest test; test.safe_run(); }
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TEST(Highgui_Image, read_bmp_rle8) { CV_GrfmtReadBMPRLE8Test test; test.safe_run(); }
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#ifdef HAVE_PNG
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class CV_GrfmtPNGEncodeTest : 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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vector<uchar> buff;
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Mat im = Mat::zeros(1000,1000, CV_8U);
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//randu(im, 0, 256);
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vector<int> param;
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param.push_back(IMWRITE_PNG_COMPRESSION);
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param.push_back(3); //default(3) 0-9.
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cv::imencode(".png" ,im ,buff, param);
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// hangs
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Mat im2 = imdecode(buff,IMREAD_ANYDEPTH);
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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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TEST(Highgui_Image, encode_png) { CV_GrfmtPNGEncodeTest test; test.safe_run(); }
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TEST(Highgui_ImreadVSCvtColor, regression)
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{
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cvtest::TS& ts = *cvtest::TS::ptr();
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const int MAX_MEAN_DIFF = 1;
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const int MAX_ABS_DIFF = 10;
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string imgName = string(ts.get_data_path()) + "/../cv/shared/lena.png";
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Mat original_image = imread(imgName);
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Mat gray_by_codec = imread(imgName, 0);
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Mat gray_by_cvt;
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cvtColor(original_image, gray_by_cvt, CV_BGR2GRAY);
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Mat diff;
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absdiff(gray_by_codec, gray_by_cvt, diff);
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double actual_avg_diff = (double)mean(diff)[0];
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double actual_maxval, actual_minval;
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minMaxLoc(diff, &actual_minval, &actual_maxval);
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//printf("actual avg = %g, actual maxdiff = %g, npixels = %d\n", actual_avg_diff, actual_maxval, (int)diff.total());
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EXPECT_LT(actual_avg_diff, MAX_MEAN_DIFF);
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EXPECT_LT(actual_maxval, MAX_ABS_DIFF);
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}
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#endif
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#ifdef HAVE_JPEG
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TEST(Highgui_Jpeg, encode_empty)
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{
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cv::Mat img;
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std::vector<uchar> jpegImg;
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ASSERT_THROW(cv::imencode(".jpg", img, jpegImg), cv::Exception);
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}
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#endif
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#ifdef HAVE_TIFF
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// these defines are used to resolve conflict between tiff.h and opencv2/core/types_c.h
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#define uint64 uint64_hack_
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#define int64 int64_hack_
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#include "tiff.h"
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TEST(Highgui_Tiff, decode_tile16384x16384)
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{
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// see issue #2161
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cv::Mat big(16384, 16384, CV_8UC1, cv::Scalar::all(0));
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string file3 = cv::tempfile(".tiff");
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string file4 = cv::tempfile(".tiff");
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std::vector<int> params;
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params.push_back(TIFFTAG_ROWSPERSTRIP);
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params.push_back(big.rows);
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cv::imwrite(file4, big, params);
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cv::imwrite(file3, big.colRange(0, big.cols - 1), params);
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big.release();
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try
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{
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cv::imread(file3);
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EXPECT_NO_THROW(cv::imread(file4));
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}
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catch(const std::bad_alloc&)
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{
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// have no enough memory
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}
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remove(file3.c_str());
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remove(file4.c_str());
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}
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#endif
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#ifdef HAVE_WEBP
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TEST(Highgui_WebP, encode_decode_lossless_webp)
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{
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cvtest::TS& ts = *cvtest::TS::ptr();
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string input = string(ts.get_data_path()) + "../cv/shared/lena.png";
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cv::Mat img = cv::imread(input);
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ASSERT_FALSE(img.empty());
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string output = cv::tempfile(".webp");
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EXPECT_NO_THROW(cv::imwrite(output, img)); // lossless
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cv::Mat img_webp = cv::imread(output);
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std::vector<unsigned char> buf;
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FILE * wfile = NULL;
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wfile = fopen(output.c_str(), "rb");
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if (wfile != NULL)
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{
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fseek(wfile, 0, SEEK_END);
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size_t wfile_size = ftell(wfile);
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fseek(wfile, 0, SEEK_SET);
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buf.resize(wfile_size);
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size_t data_size = fread(&buf[0], 1, wfile_size, wfile);
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if(wfile)
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{
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fclose(wfile);
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}
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if (data_size != wfile_size)
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{
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EXPECT_TRUE(false);
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}
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}
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remove(output.c_str());
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cv::Mat decode = cv::imdecode(buf, IMREAD_COLOR);
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ASSERT_FALSE(decode.empty());
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EXPECT_TRUE(cv::norm(decode, img_webp, NORM_INF) == 0);
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ASSERT_FALSE(img_webp.empty());
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EXPECT_TRUE(cv::norm(img, img_webp, NORM_INF) == 0);
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}
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TEST(Highgui_WebP, encode_decode_lossy_webp)
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{
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cvtest::TS& ts = *cvtest::TS::ptr();
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string input = string(ts.get_data_path()) + "/../cv/shared/lena.png";
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cv::Mat img = cv::imread(input);
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ASSERT_FALSE(img.empty());
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for(int q = 100; q>=0; q-=10)
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{
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std::vector<int> params;
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params.push_back(IMWRITE_WEBP_QUALITY);
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params.push_back(q);
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string output = cv::tempfile(".webp");
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EXPECT_NO_THROW(cv::imwrite(output, img, params));
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cv::Mat img_webp = cv::imread(output);
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remove(output.c_str());
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EXPECT_FALSE(img_webp.empty());
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}
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}
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#endif
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TEST(Highgui_Hdr, regression)
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{
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string folder = string(cvtest::TS::ptr()->get_data_path()) + "../cv/hdr/";
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string name_rle = folder + "rle.hdr";
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string name_no_rle = folder + "no_rle.hdr";
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Mat img_rle = imread(name_rle, -1);
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ASSERT_FALSE(img_rle.empty()) << "Could not open " << name_rle;
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Mat img_no_rle = imread(name_no_rle, -1);
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ASSERT_FALSE(img_no_rle.empty()) << "Could not open " << name_no_rle;
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double min = 0.0, max = 1.0;
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minMaxLoc(abs(img_rle - img_no_rle), &min, &max);
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ASSERT_FALSE(max > DBL_EPSILON);
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string tmp_file_name = tempfile(".hdr");
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vector<int>param(1);
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for(int i = 0; i < 2; i++) {
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param[0] = i;
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imwrite(tmp_file_name, img_rle, param);
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Mat written_img = imread(tmp_file_name, -1);
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ASSERT_FALSE(written_img.empty()) << "Could not open " << tmp_file_name;
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minMaxLoc(abs(img_rle - written_img), &min, &max);
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ASSERT_FALSE(max > DBL_EPSILON);
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}
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}
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