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Open Source Computer Vision Library
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123 lines
4.6 KiB
123 lines
4.6 KiB
14 years ago
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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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// Intel License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2000, Intel Corporation, 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 Intel Corporation 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 <iostream>
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#include <string>
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#include <iosfwd>
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#include "test_precomp.hpp"
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using namespace cv;
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using namespace cv::gpu;
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using namespace std;
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struct CV_GpuMeanShiftSegmentationTest : public cvtest::BaseTest {
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CV_GpuMeanShiftSegmentationTest() {}
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void run(int)
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{
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bool cc12_ok = TargetArchs::builtWith(FEATURE_SET_COMPUTE_12) && DeviceInfo().supports(FEATURE_SET_COMPUTE_12);
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if (!cc12_ok)
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{
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ts->printf(cvtest::TS::CONSOLE, "\nCompute capability 1.2 is required");
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ts->set_failed_test_info(cvtest::TS::FAIL_GENERIC);
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return;
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}
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Mat img_rgb = imread(string(ts->get_data_path()) + "meanshift/cones.png");
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if (img_rgb.empty())
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{
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ts->set_failed_test_info(cvtest::TS::FAIL_MISSING_TEST_DATA);
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return;
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}
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Mat img;
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cvtColor(img_rgb, img, CV_BGR2BGRA);
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for (int minsize = 0; minsize < 2000; minsize = (minsize + 1) * 4)
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{
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stringstream path;
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path << ts->get_data_path() << "meanshift/cones_segmented_sp10_sr10_minsize" << minsize;
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if (TargetArchs::builtWith(FEATURE_SET_COMPUTE_20) && DeviceInfo().supports(FEATURE_SET_COMPUTE_20))
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path << ".png";
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else
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path << "_CC1X.png";
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Mat dst;
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meanShiftSegmentation((GpuMat)img, dst, 10, 10, minsize);
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Mat dst_rgb;
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cvtColor(dst, dst_rgb, CV_BGRA2BGR);
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//imwrite(path.str(), dst_rgb);
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Mat dst_ref = imread(path.str());
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if (dst_ref.empty())
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{
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ts->set_failed_test_info(cvtest::TS::FAIL_MISSING_TEST_DATA);
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return;
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}
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if (CheckSimilarity(dst_rgb, dst_ref, 1e-3f) != cvtest::TS::OK)
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{
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ts->printf(cvtest::TS::LOG, "\ndiffers from image *minsize%d.png\n", minsize);
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ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
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}
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}
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ts->set_failed_test_info(cvtest::TS::OK);
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}
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int CheckSimilarity(const Mat& m1, const Mat& m2, float max_err)
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{
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Mat diff;
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cv::matchTemplate(m1, m2, diff, CV_TM_CCORR_NORMED);
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float err = abs(diff.at<float>(0, 0) - 1.f);
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if (err > max_err)
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return cvtest::TS::FAIL_INVALID_OUTPUT;
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return cvtest::TS::OK;
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}
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};
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TEST(meanShiftSegmentation, regression) { CV_GpuMeanShiftSegmentationTest test; test.safe_run(); }
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