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Open Source Computer Vision Library
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277 lines
8.7 KiB
277 lines
8.7 KiB
/*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) 2010-2012, Institute Of Software Chinese Academy Of Science, all rights reserved. |
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// Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved. |
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// Copyright (C) 2010-2012, Multicoreware, Inc., all rights reserved. |
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// Copyright (C) 2014, Itseez, 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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// @Authors |
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// Niko Li, newlife20080214@gmail.com |
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// Jia Haipeng, jiahaipeng95@gmail.com |
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// Shengen Yan, yanshengen@gmail.com |
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// Jiang Liyuan, lyuan001.good@163.com |
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// Rock Li, Rock.Li@amd.com |
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// Wu Zailong, bullet@yeah.net |
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// Xu Pang, pangxu010@163.com |
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// Sen Liu, swjtuls1987@126.com |
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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 "cvconfig.h" |
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#include "opencv2/ts/ocl_test.hpp" |
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#ifdef HAVE_OPENCL |
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namespace cvtest { |
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namespace ocl { |
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/////////////////////////////////////////////////////////////////////////////// |
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PARAM_TEST_CASE(CalcBackProject, MatDepth, int, bool) |
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{ |
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int depth, N; |
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bool useRoi; |
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std::vector<float> ranges; |
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std::vector<int> channels; |
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double scale; |
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std::vector<Mat> images; |
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std::vector<Mat> images_roi; |
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std::vector<UMat> uimages; |
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std::vector<UMat> uimages_roi; |
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TEST_DECLARE_INPUT_PARAMETER(hist); |
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TEST_DECLARE_OUTPUT_PARAMETER(dst); |
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virtual void SetUp() |
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{ |
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depth = GET_PARAM(0); |
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N = GET_PARAM(1); |
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useRoi = GET_PARAM(2); |
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ASSERT_GE(2, N); |
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images.resize(N); |
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images_roi.resize(N); |
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uimages.resize(N); |
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uimages_roi.resize(N); |
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} |
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void random_roi() |
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{ |
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Size roiSize = randomSize(1, MAX_VALUE); |
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int totalChannels = 0; |
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ranges.clear(); |
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channels.clear(); |
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for (int i = 0; i < N; ++i) |
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{ |
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Border srcBorder = randomBorder(0, useRoi ? MAX_VALUE : 0); |
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int cn = randomInt(1, 5); |
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randomSubMat(images[i], images_roi[i], roiSize, srcBorder, CV_MAKE_TYPE(depth, cn), 0, 125); |
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ranges.push_back(10); |
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ranges.push_back(100); |
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channels.push_back(randomInt(0, cn) + totalChannels); |
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totalChannels += cn; |
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} |
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Mat tmpHist; |
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{ |
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std::vector<int> hist_size(N); |
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for (int i = 0 ; i < N; ++i) |
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hist_size[i] = randomInt(10, 50); |
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cv::calcHist(images_roi, channels, noArray(), tmpHist, hist_size, ranges); |
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ASSERT_EQ(CV_32FC1, tmpHist.type()); |
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} |
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Border histBorder = randomBorder(0, useRoi ? MAX_VALUE : 0); |
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randomSubMat(hist, hist_roi, tmpHist.size(), histBorder, tmpHist.type(), 0, MAX_VALUE); |
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tmpHist.copyTo(hist_roi); |
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Border dstBorder = randomBorder(0, useRoi ? MAX_VALUE : 0); |
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randomSubMat(dst, dst_roi, roiSize, dstBorder, CV_MAKE_TYPE(depth, 1), 5, 16); |
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for (int i = 0; i < N; ++i) |
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{ |
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images[i].copyTo(uimages[i]); |
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Size _wholeSize; |
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Point ofs; |
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images_roi[i].locateROI(_wholeSize, ofs); |
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uimages_roi[i] = uimages[i](Rect(ofs.x, ofs.y, images_roi[i].cols, images_roi[i].rows)); |
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} |
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UMAT_UPLOAD_INPUT_PARAMETER(hist); |
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UMAT_UPLOAD_OUTPUT_PARAMETER(dst); |
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scale = randomDouble(0.1, 1); |
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} |
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void test_by_pict() |
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{ |
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Mat frame1 = readImage("optflow/RubberWhale1.png", IMREAD_GRAYSCALE); |
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UMat usrc; |
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frame1.copyTo(usrc); |
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int histSize = randomInt(3, 29); |
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float hue_range[] = { 0, 180 }; |
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const float* ranges1 = { hue_range }; |
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Mat hist1; |
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//compute histogram |
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calcHist(&frame1, 1, 0, Mat(), hist1, 1, &histSize, &ranges1, true, false); |
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normalize(hist1, hist1, 0, 255, NORM_MINMAX, -1, Mat()); |
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Mat dst1; |
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UMat udst1, src, uhist1; |
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hist1.copyTo(uhist1); |
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std::vector<UMat> uims; |
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uims.push_back(usrc); |
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std::vector<float> urngs; |
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urngs.push_back(0); |
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urngs.push_back(180); |
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std::vector<int> chs; |
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chs.push_back(0); |
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OCL_OFF(calcBackProject(&frame1, 1, 0, hist1, dst1, &ranges1, 1, true)); |
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OCL_ON(calcBackProject(uims, chs, uhist1, udst1, urngs, 1.0)); |
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if (cv::ocl::useOpenCL() && cv::ocl::Device::getDefault().isAMD()) |
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{ |
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Size dstSize = dst1.size(); |
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int nDiffs = (int)(0.03f*dstSize.height*dstSize.width); |
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//check if the dst mats are the same except 3% difference |
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EXPECT_MAT_N_DIFF(dst1, udst1, nDiffs); |
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} |
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else |
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{ |
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EXPECT_MAT_NEAR(dst1, udst1, 0.0); |
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} |
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} |
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}; |
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//////////////////////////////// CalcBackProject ////////////////////////////////////////////// |
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OCL_TEST_P(CalcBackProject, Mat) |
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{ |
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for (int j = 0; j < test_loop_times; j++) |
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{ |
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random_roi(); |
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OCL_OFF(cv::calcBackProject(images_roi, channels, hist_roi, dst_roi, ranges, scale)); |
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OCL_ON(cv::calcBackProject(uimages_roi, channels, uhist_roi, udst_roi, ranges, scale)); |
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Size dstSize = dst_roi.size(); |
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int nDiffs = std::max((int)(0.07f*dstSize.area()), 1); |
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//check if the dst mats are the same except 7% difference |
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EXPECT_MAT_N_DIFF(dst_roi, udst_roi, nDiffs); |
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} |
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} |
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OCL_TEST_P(CalcBackProject, Mat_RealImage) |
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{ |
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//check on given image |
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test_by_pict(); |
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} |
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//////////////////////////////// CalcHist ////////////////////////////////////////////// |
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PARAM_TEST_CASE(CalcHist, bool) |
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{ |
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bool useRoi; |
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TEST_DECLARE_INPUT_PARAMETER(src); |
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TEST_DECLARE_OUTPUT_PARAMETER(hist); |
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virtual void SetUp() |
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{ |
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useRoi = GET_PARAM(0); |
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} |
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void random_roi() |
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{ |
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Size roiSize = randomSize(1, MAX_VALUE); |
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Border srcBorder = randomBorder(0, useRoi ? MAX_VALUE : 0); |
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randomSubMat(src, src_roi, roiSize, srcBorder, CV_8UC1, 0, 256); |
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Border histBorder = randomBorder(0, useRoi ? MAX_VALUE : 0); |
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randomSubMat(hist, hist_roi, Size(1, 256), histBorder, CV_32SC1, 0, MAX_VALUE); |
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UMAT_UPLOAD_INPUT_PARAMETER(src); |
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UMAT_UPLOAD_OUTPUT_PARAMETER(hist); |
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} |
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}; |
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OCL_TEST_P(CalcHist, Mat) |
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{ |
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const std::vector<int> channels(1, 0); |
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std::vector<float> ranges(2); |
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std::vector<int> histSize(1, 256); |
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ranges[0] = 0; |
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ranges[1] = 256; |
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for (int j = 0; j < test_loop_times; j++) |
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{ |
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random_roi(); |
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OCL_OFF(cv::calcHist(std::vector<Mat>(1, src_roi), channels, noArray(), hist_roi, histSize, ranges, false)); |
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OCL_ON(cv::calcHist(std::vector<UMat>(1, usrc_roi), channels, noArray(), uhist_roi, histSize, ranges, false)); |
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OCL_EXPECT_MATS_NEAR(hist, 0.0); |
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} |
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} |
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///////////////////////////////////////////////////////////////////////////////////// |
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OCL_INSTANTIATE_TEST_CASE_P(Imgproc, CalcBackProject, Combine(Values((MatDepth)CV_8U), Values(1, 2), Bool())); |
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OCL_INSTANTIATE_TEST_CASE_P(Imgproc, CalcHist, Values(true, false)); |
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} } // namespace cvtest::ocl |
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#endif // HAVE_OPENCL
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