749 lines
24 KiB
C++
749 lines
24 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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// 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 <cmath>
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#include <limits>
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#include "gputest.hpp"
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using namespace cv;
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using namespace std;
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using namespace gpu;
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class CV_GpuImageProcTest : public CvTest
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{
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public:
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CV_GpuImageProcTest(const char* test_name, const char* test_funcs) : CvTest(test_name, test_funcs) {}
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virtual ~CV_GpuImageProcTest() {}
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protected:
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void run(int);
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int test8UC1 (const Mat& img);
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int test8UC4 (const Mat& img);
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int test32SC1(const Mat& img);
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int test32FC1(const Mat& img);
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virtual int test(const Mat& img) = 0;
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int CheckNorm(const Mat& m1, const Mat& m2);
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};
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int CV_GpuImageProcTest::test8UC1(const Mat& img)
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{
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cv::Mat img_C1;
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cvtColor(img, img_C1, CV_BGR2GRAY);
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return test(img_C1);
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}
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int CV_GpuImageProcTest::test8UC4(const Mat& img)
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{
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cv::Mat img_C4;
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cvtColor(img, img_C4, CV_BGR2BGRA);
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return test(img_C4);
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}
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int CV_GpuImageProcTest::test32SC1(const Mat& img)
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{
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cv::Mat img_C1;
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cvtColor(img, img_C1, CV_BGR2GRAY);
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img_C1.convertTo(img_C1, CV_32S);
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return test(img_C1);
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}
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int CV_GpuImageProcTest::test32FC1(const Mat& img)
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{
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cv::Mat temp, img_C1;
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img.convertTo(temp, CV_32F);
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cvtColor(temp, img_C1, CV_BGR2GRAY);
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return test(img_C1);
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}
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int CV_GpuImageProcTest::CheckNorm(const Mat& m1, const Mat& m2)
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{
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double ret = norm(m1, m2, NORM_INF);
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if (ret < std::numeric_limits<double>::epsilon())
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{
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return CvTS::OK;
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}
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else
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{
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ts->printf(CvTS::LOG, "Norm: %f\n", ret);
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return CvTS::FAIL_GENERIC;
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}
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}
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void CV_GpuImageProcTest::run( int )
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{
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//load image
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cv::Mat img = cv::imread(std::string(ts->get_data_path()) + "stereobp/aloe-L.png");
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if (img.empty())
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{
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ts->set_failed_test_info(CvTS::FAIL_MISSING_TEST_DATA);
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return;
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}
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int testResult = CvTS::OK;
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try
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{
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//run tests
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ts->printf(CvTS::LOG, "\n========Start test 8UC1========\n");
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if (test8UC1(img) == CvTS::OK)
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ts->printf(CvTS::LOG, "SUCCESS\n");
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else
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{
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ts->printf(CvTS::LOG, "FAIL\n");
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testResult = CvTS::FAIL_GENERIC;
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}
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ts->printf(CvTS::LOG, "\n========Start test 8UC4========\n");
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if (test8UC4(img) == CvTS::OK)
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ts->printf(CvTS::LOG, "SUCCESS\n");
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else
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{
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ts->printf(CvTS::LOG, "FAIL\n");
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testResult = CvTS::FAIL_GENERIC;
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}
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ts->printf(CvTS::LOG, "\n========Start test 32SC1========\n");
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if (test32SC1(img) == CvTS::OK)
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ts->printf(CvTS::LOG, "SUCCESS\n");
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else
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{
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ts->printf(CvTS::LOG, "FAIL\n");
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testResult = CvTS::FAIL_GENERIC;
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}
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ts->printf(CvTS::LOG, "\n========Start test 32FC1========\n");
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if (test32FC1(img) == CvTS::OK)
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ts->printf(CvTS::LOG, "SUCCESS\n");
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else
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{
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ts->printf(CvTS::LOG, "FAIL\n");
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testResult = CvTS::FAIL_GENERIC;
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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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if (!check_and_treat_gpu_exception(e, ts))
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throw;
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return;
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}
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ts->set_failed_test_info(testResult);
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}
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////////////////////////////////////////////////////////////////////////////////
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// threshold
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struct CV_GpuNppImageThresholdTest : public CV_GpuImageProcTest
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{
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public:
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CV_GpuNppImageThresholdTest() : CV_GpuImageProcTest( "GPU-NppImageThreshold", "threshold" ) {}
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int test(const Mat& img)
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{
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if (img.type() != CV_32FC1)
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{
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ts->printf(CvTS::LOG, "\nUnsupported type\n");
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return CvTS::OK;
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}
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cv::RNG rng(*ts->get_rng());
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const double thresh = rng;
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cv::Mat cpuRes;
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cv::threshold(img, cpuRes, thresh, 0.0, THRESH_TRUNC);
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GpuMat gpu1(img);
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GpuMat gpuRes;
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cv::gpu::threshold(gpu1, gpuRes, thresh);
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return CheckNorm(cpuRes, gpuRes);
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}
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};
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////////////////////////////////////////////////////////////////////////////////
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// resize
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struct CV_GpuNppImageResizeTest : public CV_GpuImageProcTest
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{
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CV_GpuNppImageResizeTest() : CV_GpuImageProcTest( "GPU-NppImageResize", "resize" ) {}
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int test(const Mat& img)
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{
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if (img.type() != CV_8UC1 && img.type() != CV_8UC4)
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{
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ts->printf(CvTS::LOG, "Unsupported type\n");
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return CvTS::OK;
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}
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int interpolations[] = {INTER_NEAREST, INTER_LINEAR, /*INTER_CUBIC,*/ /*INTER_LANCZOS4*/};
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const char* interpolations_str[] = {"INTER_NEAREST", "INTER_LINEAR", /*"INTER_CUBIC",*/ /*"INTER_LANCZOS4"*/};
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int interpolations_num = sizeof(interpolations) / sizeof(int);
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int test_res = CvTS::OK;
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for (int i = 0; i < interpolations_num; ++i)
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{
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ts->printf(CvTS::LOG, "Interpolation: %s\n", interpolations_str[i]);
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Mat cpu_res;
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cv::resize(img, cpu_res, Size(), 0.5, 0.5, interpolations[i]);
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GpuMat gpu1(img), gpu_res;
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cv::gpu::resize(gpu1, gpu_res, Size(), 0.5, 0.5, interpolations[i]);
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if (CheckNorm(cpu_res, gpu_res) != CvTS::OK)
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test_res = CvTS::FAIL_GENERIC;
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}
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return test_res;
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}
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};
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////////////////////////////////////////////////////////////////////////////////
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// copyMakeBorder
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struct CV_GpuNppImageCopyMakeBorderTest : public CV_GpuImageProcTest
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{
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CV_GpuNppImageCopyMakeBorderTest() : CV_GpuImageProcTest( "GPU-NppImageCopyMakeBorder", "copyMakeBorder" ) {}
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int test(const Mat& img)
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{
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if (img.type() != CV_8UC1 && img.type() != CV_8UC4 && img.type() != CV_32SC1)
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{
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ts->printf(CvTS::LOG, "\nUnsupported type\n");
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return CvTS::OK;
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}
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cv::RNG rng(*ts->get_rng());
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int top = rng.uniform(1, 10);
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int botton = rng.uniform(1, 10);
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int left = rng.uniform(1, 10);
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int right = rng.uniform(1, 10);
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cv::Scalar val(rng.uniform(0, 255), rng.uniform(0, 255), rng.uniform(0, 255), rng.uniform(0, 255));
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Mat cpudst;
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cv::copyMakeBorder(img, cpudst, top, botton, left, right, BORDER_CONSTANT, val);
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GpuMat gpu1(img);
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GpuMat gpudst;
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cv::gpu::copyMakeBorder(gpu1, gpudst, top, botton, left, right, val);
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return CheckNorm(cpudst, gpudst);
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}
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};
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////////////////////////////////////////////////////////////////////////////////
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// warpAffine
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struct CV_GpuNppImageWarpAffineTest : public CV_GpuImageProcTest
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{
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CV_GpuNppImageWarpAffineTest() : CV_GpuImageProcTest( "GPU-NppImageWarpAffine", "warpAffine" ) {}
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int test(const Mat& img)
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{
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if (img.type() == CV_32SC1)
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{
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ts->printf(CvTS::LOG, "\nUnsupported type\n");
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return CvTS::OK;
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}
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static const double coeffs[2][3] =
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{
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{cos(3.14 / 6), -sin(3.14 / 6), 100.0},
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{sin(3.14 / 6), cos(3.14 / 6), -100.0}
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};
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Mat M(2, 3, CV_64F, (void*)coeffs);
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int flags[] = {INTER_NEAREST, INTER_LINEAR, INTER_CUBIC, INTER_NEAREST | WARP_INVERSE_MAP, INTER_LINEAR | WARP_INVERSE_MAP, INTER_CUBIC | WARP_INVERSE_MAP};
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const char* flags_str[] = {"INTER_NEAREST", "INTER_LINEAR", "INTER_CUBIC", "INTER_NEAREST | WARP_INVERSE_MAP", "INTER_LINEAR | WARP_INVERSE_MAP", "INTER_CUBIC | WARP_INVERSE_MAP"};
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int flags_num = sizeof(flags) / sizeof(int);
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int test_res = CvTS::OK;
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for (int i = 0; i < flags_num; ++i)
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{
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ts->printf(CvTS::LOG, "\nFlags: %s\n", flags_str[i]);
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Mat cpudst;
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cv::warpAffine(img, cpudst, M, img.size(), flags[i]);
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GpuMat gpu1(img);
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GpuMat gpudst;
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cv::gpu::warpAffine(gpu1, gpudst, M, gpu1.size(), flags[i]);
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if (CheckNorm(cpudst, gpudst) != CvTS::OK)
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test_res = CvTS::FAIL_GENERIC;
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}
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return test_res;
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}
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};
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////////////////////////////////////////////////////////////////////////////////
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// warpPerspective
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struct CV_GpuNppImageWarpPerspectiveTest : public CV_GpuImageProcTest
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{
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CV_GpuNppImageWarpPerspectiveTest() : CV_GpuImageProcTest( "GPU-NppImageWarpPerspective", "warpPerspective" ) {}
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int test(const Mat& img)
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{
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if (img.type() == CV_32SC1)
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{
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ts->printf(CvTS::LOG, "\nUnsupported type\n");
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return CvTS::OK;
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}
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static const double coeffs[3][3] =
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{
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{cos(3.14 / 6), -sin(3.14 / 6), 100.0},
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{sin(3.14 / 6), cos(3.14 / 6), -100.0},
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{0.0, 0.0, 1.0}
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};
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Mat M(3, 3, CV_64F, (void*)coeffs);
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int flags[] = {INTER_NEAREST, INTER_LINEAR, INTER_CUBIC, INTER_NEAREST | WARP_INVERSE_MAP, INTER_LINEAR | WARP_INVERSE_MAP, INTER_CUBIC | WARP_INVERSE_MAP};
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const char* flags_str[] = {"INTER_NEAREST", "INTER_LINEAR", "INTER_CUBIC", "INTER_NEAREST | WARP_INVERSE_MAP", "INTER_LINEAR | WARP_INVERSE_MAP", "INTER_CUBIC | WARP_INVERSE_MAP"};
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int flags_num = sizeof(flags) / sizeof(int);
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int test_res = CvTS::OK;
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for (int i = 0; i < flags_num; ++i)
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{
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ts->printf(CvTS::LOG, "\nFlags: %s\n", flags_str[i]);
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Mat cpudst;
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cv::warpPerspective(img, cpudst, M, img.size(), flags[i]);
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GpuMat gpu1(img);
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GpuMat gpudst;
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cv::gpu::warpPerspective(gpu1, gpudst, M, gpu1.size(), flags[i]);
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if (CheckNorm(cpudst, gpudst) != CvTS::OK)
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test_res = CvTS::FAIL_GENERIC;
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}
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return test_res;
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}
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};
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////////////////////////////////////////////////////////////////////////////////
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// integral
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struct CV_GpuNppImageIntegralTest : public CV_GpuImageProcTest
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{
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CV_GpuNppImageIntegralTest() : CV_GpuImageProcTest( "GPU-NppImageIntegral", "integral" ) {}
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int test(const Mat& img)
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{
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if (img.type() != CV_8UC1)
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{
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ts->printf(CvTS::LOG, "\nUnsupported type\n");
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return CvTS::OK;
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}
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Mat cpusum, cpusqsum;
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cv::integral(img, cpusum, cpusqsum, CV_32S);
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GpuMat gpu1(img);
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GpuMat gpusum, gpusqsum;
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cv::gpu::integral(gpu1, gpusum, gpusqsum);
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gpusqsum.convertTo(gpusqsum, CV_64F);
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int test_res = CvTS::OK;
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if (CheckNorm(cpusum, gpusum) != CvTS::OK)
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{
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ts->printf(CvTS::LOG, "\nSum failed\n");
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test_res = CvTS::FAIL_GENERIC;
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}
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if (CheckNorm(cpusqsum, gpusqsum) != CvTS::OK)
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{
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ts->printf(CvTS::LOG, "\nSquared sum failed\n");
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test_res = CvTS::FAIL_GENERIC;
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}
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return test_res;
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}
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};
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////////////////////////////////////////////////////////////////////////////////
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// Canny
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struct CV_GpuNppImageCannyTest : public CV_GpuImageProcTest
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{
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CV_GpuNppImageCannyTest() : CV_GpuImageProcTest( "GPU-NppImageCanny", "Canny" ) {}
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int test(const Mat& img)
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{
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if (img.type() != CV_8UC1)
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{
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ts->printf(CvTS::LOG, "\nUnsupported type\n");
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return CvTS::OK;
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}
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const double threshold1 = 1.0, threshold2 = 10.0;
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Mat cpudst;
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cv::Canny(img, cpudst, threshold1, threshold2);
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GpuMat gpu1(img);
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GpuMat gpudst;
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cv::gpu::Canny(gpu1, gpudst, threshold1, threshold2);
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return CheckNorm(cpudst, gpudst);
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}
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};
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////////////////////////////////////////////////////////////////////////////////
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// cvtColor
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class CV_GpuCvtColorTest : public CvTest
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{
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public:
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CV_GpuCvtColorTest() : CvTest("GPU-CvtColor", "cvtColor") {}
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~CV_GpuCvtColorTest() {};
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protected:
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void run(int);
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int CheckNorm(const Mat& m1, const Mat& m2);
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};
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int CV_GpuCvtColorTest::CheckNorm(const Mat& m1, const Mat& m2)
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{
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double ret = norm(m1, m2, NORM_INF);
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if (ret <= 3)
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{
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return CvTS::OK;
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}
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else
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{
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ts->printf(CvTS::LOG, "\nNorm: %f\n", ret);
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return CvTS::FAIL_GENERIC;
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}
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}
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void CV_GpuCvtColorTest::run( int )
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{
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cv::Mat img = cv::imread(std::string(ts->get_data_path()) + "stereobp/aloe-L.png");
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if (img.empty())
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{
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ts->set_failed_test_info(CvTS::FAIL_MISSING_TEST_DATA);
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return;
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}
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int testResult = CvTS::OK;
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cv::Mat cpuRes;
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cv::gpu::GpuMat gpuImg(img), gpuRes;
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try
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{
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int codes[] = { CV_BGR2RGB, CV_RGB2BGRA, CV_BGRA2RGB,
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CV_RGB2BGR555, CV_BGR5552BGR, CV_BGR2BGR565, CV_BGR5652RGB,
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CV_RGB2YCrCb, CV_YCrCb2BGR, CV_BGR2YUV, CV_YUV2RGB,
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CV_RGB2XYZ, CV_XYZ2BGR, CV_BGR2XYZ, CV_XYZ2RGB,
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CV_RGB2HSV, CV_HSV2BGR, CV_BGR2HSV_FULL, CV_HSV2RGB_FULL,
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CV_RGB2HLS, CV_HLS2BGR, CV_BGR2HLS_FULL, CV_HLS2RGB_FULL,
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CV_RGB2GRAY, CV_GRAY2BGRA, CV_BGRA2GRAY,
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|
CV_GRAY2BGR555, CV_BGR5552GRAY, CV_GRAY2BGR565, CV_BGR5652GRAY};
|
|
const char* codes_str[] = { "CV_BGR2RGB", "CV_RGB2BGRA", "CV_BGRA2RGB",
|
|
"CV_RGB2BGR555", "CV_BGR5552BGR", "CV_BGR2BGR565", "CV_BGR5652RGB",
|
|
"CV_RGB2YCrCb", "CV_YCrCb2BGR", "CV_BGR2YUV", "CV_YUV2RGB",
|
|
"CV_RGB2XYZ", "CV_XYZ2BGR", "CV_BGR2XYZ", "CV_XYZ2RGB",
|
|
"CV_RGB2HSV", "CV_HSV2RGB", "CV_BGR2HSV_FULL", "CV_HSV2RGB_FULL",
|
|
"CV_RGB2HLS", "CV_HLS2RGB", "CV_BGR2HLS_FULL", "CV_HLS2RGB_FULL",
|
|
"CV_RGB2GRAY", "CV_GRAY2BGRA", "CV_BGRA2GRAY",
|
|
"CV_GRAY2BGR555", "CV_BGR5552GRAY", "CV_GRAY2BGR565", "CV_BGR5652GRAY"};
|
|
int codes_num = sizeof(codes) / sizeof(int);
|
|
|
|
for (int i = 0; i < codes_num; ++i)
|
|
{
|
|
ts->printf(CvTS::LOG, "\n%s\n", codes_str[i]);
|
|
|
|
cv::cvtColor(img, cpuRes, codes[i]);
|
|
cv::gpu::cvtColor(gpuImg, gpuRes, codes[i]);
|
|
|
|
if (CheckNorm(cpuRes, gpuRes) == CvTS::OK)
|
|
ts->printf(CvTS::LOG, "\nSUCCESS\n");
|
|
else
|
|
{
|
|
ts->printf(CvTS::LOG, "\nFAIL\n");
|
|
testResult = CvTS::FAIL_GENERIC;
|
|
}
|
|
|
|
img = cpuRes;
|
|
gpuImg = gpuRes;
|
|
}
|
|
}
|
|
catch(const cv::Exception& e)
|
|
{
|
|
if (!check_and_treat_gpu_exception(e, ts))
|
|
throw;
|
|
return;
|
|
}
|
|
|
|
ts->set_failed_test_info(testResult);
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////////////////
|
|
// Histograms
|
|
class CV_GpuHistogramsTest : public CvTest
|
|
{
|
|
public:
|
|
CV_GpuHistogramsTest() : CvTest("GPU-Histograms", "histEven") {}
|
|
~CV_GpuHistogramsTest() {};
|
|
|
|
protected:
|
|
void run(int);
|
|
|
|
int CheckNorm(const Mat& m1, const Mat& m2)
|
|
{
|
|
double ret = norm(m1, m2, NORM_INF);
|
|
|
|
if (ret < std::numeric_limits<double>::epsilon())
|
|
{
|
|
return CvTS::OK;
|
|
}
|
|
else
|
|
{
|
|
ts->printf(CvTS::LOG, "\nNorm: %f\n", ret);
|
|
return CvTS::FAIL_GENERIC;
|
|
}
|
|
}
|
|
};
|
|
|
|
void CV_GpuHistogramsTest::run( int )
|
|
{
|
|
//load image
|
|
cv::Mat img = cv::imread(std::string(ts->get_data_path()) + "stereobp/aloe-L.png");
|
|
|
|
if (img.empty())
|
|
{
|
|
ts->set_failed_test_info(CvTS::FAIL_MISSING_TEST_DATA);
|
|
return;
|
|
}
|
|
|
|
try
|
|
{
|
|
Mat hsv;
|
|
cv::cvtColor(img, hsv, CV_BGR2HSV);
|
|
|
|
int hbins = 30;
|
|
int histSize[] = {hbins};
|
|
|
|
float hranges[] = {0, 180};
|
|
const float* ranges[] = {hranges};
|
|
|
|
MatND hist;
|
|
|
|
int channels[] = {0};
|
|
calcHist(&hsv, 1, channels, Mat(), hist, 1, histSize, ranges);
|
|
|
|
GpuMat gpuHsv(hsv);
|
|
std::vector<GpuMat> srcs;
|
|
cv::gpu::split(gpuHsv, srcs);
|
|
GpuMat gpuHist;
|
|
histEven(srcs[0], gpuHist, hbins, (int)hranges[0], (int)hranges[1]);
|
|
|
|
Mat cpuHist = hist;
|
|
cpuHist = cpuHist.t();
|
|
cpuHist.convertTo(cpuHist, CV_32S);
|
|
|
|
ts->set_failed_test_info(CheckNorm(cpuHist, gpuHist));
|
|
}
|
|
catch(const cv::Exception& e)
|
|
{
|
|
if (!check_and_treat_gpu_exception(e, ts))
|
|
throw;
|
|
return;
|
|
}
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////////
|
|
// Corner Harris feature detector
|
|
|
|
struct CV_GpuCornerHarrisTest: CvTest
|
|
{
|
|
CV_GpuCornerHarrisTest(): CvTest("GPU-CornerHarrisTest", "cornerHarris") {}
|
|
|
|
void run(int)
|
|
{
|
|
try
|
|
{
|
|
for (int i = 0; i < 5; ++i)
|
|
{
|
|
int rows = 1 + rand() % 300, cols = 1 + rand() % 300;
|
|
if (!compareToCpuTest(rows, cols, CV_32F, 1 + rand() % 5, 1 + 2 * (rand() % 4))) return;
|
|
if (!compareToCpuTest(rows, cols, CV_32F, 1 + rand() % 5, -1)) return;
|
|
}
|
|
}
|
|
catch (const Exception& e)
|
|
{
|
|
if (!check_and_treat_gpu_exception(e, ts)) throw;
|
|
return;
|
|
}
|
|
}
|
|
|
|
bool compareToCpuTest(int rows, int cols, int depth, int blockSize, int apertureSize)
|
|
{
|
|
RNG rng;
|
|
cv::Mat src(rows, cols, depth);
|
|
if (depth == CV_32F)
|
|
rng.fill(src, RNG::UNIFORM, cv::Scalar(0), cv::Scalar(1));
|
|
|
|
double k = 0.1;
|
|
int borderType = BORDER_DEFAULT;
|
|
|
|
cv::Mat dst_gold;
|
|
cv::cornerHarris(src, dst_gold, blockSize, apertureSize, k, borderType);
|
|
|
|
cv::gpu::GpuMat dst;
|
|
cv::gpu::cornerHarris(cv::gpu::GpuMat(src), dst, blockSize, apertureSize, k);
|
|
|
|
int asize = apertureSize > 0 ? apertureSize : 3;
|
|
|
|
cv::Mat dsth = dst;
|
|
for (int i = max(blockSize, asize) + 2; i < dst.rows - max(blockSize, asize) - 2; ++i)
|
|
{
|
|
for (int j = max(blockSize, asize) + 2; j < dst.cols - max(blockSize, asize) - 2; ++j)
|
|
{
|
|
float a = dst_gold.at<float>(i, j);
|
|
float b = dsth.at<float>(i, j);
|
|
if (fabs(a - b) > 1e-3f)
|
|
{
|
|
ts->printf(CvTS::CONSOLE, "%d %d %f %f %d\n", i, j, a, b, apertureSize);
|
|
ts->set_failed_test_info(CvTS::FAIL_INVALID_OUTPUT);
|
|
return false;
|
|
};
|
|
}
|
|
}
|
|
return true;
|
|
}
|
|
};
|
|
|
|
////////////////////////////////////////////////////////////////////////
|
|
// Corner Min Eigen Val
|
|
|
|
struct CV_GpuCornerMinEigenValTest: CvTest
|
|
{
|
|
CV_GpuCornerMinEigenValTest(): CvTest("GPU-CornerMinEigenValTest", "cornerMinEigenVal") {}
|
|
|
|
void run(int)
|
|
{
|
|
try
|
|
{
|
|
for (int i = 0; i < 3; ++i)
|
|
{
|
|
int rows = 1 + rand() % 300, cols = 1 + rand() % 300;
|
|
if (!compareToCpuTest(rows, cols, CV_32F, 1 + rand() % 5, -1)) return;
|
|
if (!compareToCpuTest(rows, cols, CV_32F, 1 + rand() % 5, 1 + 2 * (rand() % 4))) return;
|
|
}
|
|
}
|
|
catch (const Exception& e)
|
|
{
|
|
if (!check_and_treat_gpu_exception(e, ts)) throw;
|
|
return;
|
|
}
|
|
}
|
|
|
|
bool compareToCpuTest(int rows, int cols, int depth, int blockSize, int apertureSize)
|
|
{
|
|
RNG rng;
|
|
cv::Mat src(rows, cols, depth);
|
|
if (depth == CV_32F)
|
|
rng.fill(src, RNG::UNIFORM, cv::Scalar(0), cv::Scalar(1));
|
|
|
|
int borderType = BORDER_DEFAULT;
|
|
|
|
cv::Mat dst_gold;
|
|
cv::cornerMinEigenVal(src, dst_gold, blockSize, apertureSize, borderType);
|
|
|
|
cv::gpu::GpuMat dst;
|
|
cv::gpu::cornerMinEigenVal(cv::gpu::GpuMat(src), dst, blockSize, apertureSize);
|
|
|
|
int asize = apertureSize > 0 ? apertureSize : 3;
|
|
|
|
cv::Mat dsth = dst;
|
|
for (int i = max(blockSize, asize) + 2; i < dst.rows - max(blockSize, asize) - 2; ++i)
|
|
{
|
|
for (int j = max(blockSize, asize) + 2; j < dst.cols - max(blockSize, asize) - 2; ++j)
|
|
{
|
|
float a = dst_gold.at<float>(i, j);
|
|
float b = dsth.at<float>(i, j);
|
|
if (fabs(a - b) > 1e-3f)
|
|
{
|
|
ts->printf(CvTS::CONSOLE, "%d %d %f %f %d %d\n", i, j, a, b, apertureSize, blockSize);
|
|
ts->set_failed_test_info(CvTS::FAIL_INVALID_OUTPUT);
|
|
return false;
|
|
};
|
|
}
|
|
}
|
|
return true;
|
|
}
|
|
};
|
|
|
|
/////////////////////////////////////////////////////////////////////////////
|
|
/////////////////// tests registration /////////////////////////////////////
|
|
/////////////////////////////////////////////////////////////////////////////
|
|
|
|
// If we comment some tests, we may foget/miss to uncomment it after.
|
|
// Placing all test definitions in one place
|
|
// makes us know about what tests are commented.
|
|
|
|
CV_GpuNppImageThresholdTest CV_GpuNppImageThreshold_test;
|
|
CV_GpuNppImageResizeTest CV_GpuNppImageResize_test;
|
|
CV_GpuNppImageCopyMakeBorderTest CV_GpuNppImageCopyMakeBorder_test;
|
|
CV_GpuNppImageWarpAffineTest CV_GpuNppImageWarpAffine_test;
|
|
CV_GpuNppImageWarpPerspectiveTest CV_GpuNppImageWarpPerspective_test;
|
|
CV_GpuNppImageIntegralTest CV_GpuNppImageIntegral_test;
|
|
CV_GpuNppImageCannyTest CV_GpuNppImageCanny_test;
|
|
CV_GpuCvtColorTest CV_GpuCvtColor_test;
|
|
CV_GpuHistogramsTest CV_GpuHistograms_test;
|
|
CV_GpuCornerHarrisTest CV_GpuCornerHarris_test;
|
|
CV_GpuCornerMinEigenValTest CV_GpuCornerMinEigenVal_test;
|
|
|