mirror of
https://github.com/opencv/opencv.git
synced 2024-12-17 02:48:01 +08:00
123 lines
4.6 KiB
C++
123 lines
4.6 KiB
C++
/*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.
|
|
//
|
|
//
|
|
// Intel License Agreement
|
|
// For Open Source Computer Vision Library
|
|
//
|
|
// Copyright (C) 2000, Intel Corporation, 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 Intel Corporation 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 <iostream>
|
|
#include <string>
|
|
#include <iosfwd>
|
|
#include "test_precomp.hpp"
|
|
using namespace cv;
|
|
using namespace cv::gpu;
|
|
using namespace std;
|
|
|
|
struct CV_GpuMeanShiftSegmentationTest : public cvtest::BaseTest {
|
|
CV_GpuMeanShiftSegmentationTest() {}
|
|
|
|
void run(int)
|
|
{
|
|
bool cc12_ok = TargetArchs::builtWith(FEATURE_SET_COMPUTE_12) && DeviceInfo().supports(FEATURE_SET_COMPUTE_12);
|
|
if (!cc12_ok)
|
|
{
|
|
ts->printf(cvtest::TS::CONSOLE, "\nCompute capability 1.2 is required");
|
|
ts->set_failed_test_info(cvtest::TS::FAIL_GENERIC);
|
|
return;
|
|
}
|
|
|
|
Mat img_rgb = imread(string(ts->get_data_path()) + "meanshift/cones.png");
|
|
if (img_rgb.empty())
|
|
{
|
|
ts->set_failed_test_info(cvtest::TS::FAIL_MISSING_TEST_DATA);
|
|
return;
|
|
}
|
|
|
|
Mat img;
|
|
cvtColor(img_rgb, img, CV_BGR2BGRA);
|
|
|
|
|
|
for (int minsize = 0; minsize < 2000; minsize = (minsize + 1) * 4)
|
|
{
|
|
stringstream path;
|
|
path << ts->get_data_path() << "meanshift/cones_segmented_sp10_sr10_minsize" << minsize;
|
|
if (TargetArchs::builtWith(FEATURE_SET_COMPUTE_20) && DeviceInfo().supports(FEATURE_SET_COMPUTE_20))
|
|
path << ".png";
|
|
else
|
|
path << "_CC1X.png";
|
|
|
|
Mat dst;
|
|
meanShiftSegmentation((GpuMat)img, dst, 10, 10, minsize);
|
|
Mat dst_rgb;
|
|
cvtColor(dst, dst_rgb, CV_BGRA2BGR);
|
|
|
|
//imwrite(path.str(), dst_rgb);
|
|
Mat dst_ref = imread(path.str());
|
|
if (dst_ref.empty())
|
|
{
|
|
ts->set_failed_test_info(cvtest::TS::FAIL_MISSING_TEST_DATA);
|
|
return;
|
|
}
|
|
if (CheckSimilarity(dst_rgb, dst_ref, 1e-3f) != cvtest::TS::OK)
|
|
{
|
|
ts->printf(cvtest::TS::LOG, "\ndiffers from image *minsize%d.png\n", minsize);
|
|
ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
|
|
}
|
|
}
|
|
|
|
ts->set_failed_test_info(cvtest::TS::OK);
|
|
}
|
|
|
|
int CheckSimilarity(const Mat& m1, const Mat& m2, float max_err)
|
|
{
|
|
Mat diff;
|
|
cv::matchTemplate(m1, m2, diff, CV_TM_CCORR_NORMED);
|
|
|
|
float err = abs(diff.at<float>(0, 0) - 1.f);
|
|
|
|
if (err > max_err)
|
|
return cvtest::TS::FAIL_INVALID_OUTPUT;
|
|
|
|
return cvtest::TS::OK;
|
|
}
|
|
|
|
|
|
};
|
|
|
|
|
|
TEST(meanShiftSegmentation, regression) { CV_GpuMeanShiftSegmentationTest test; test.safe_run(); }
|