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https://github.com/opencv/opencv.git
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416bf3253d
* attempt to add 0d/1d mat support to OpenCV * revised the patch; now 1D mat is treated as 1xN 2D mat rather than Nx1. * a step towards 'green' tests * another little step towards 'green' tests * calib test failures seem to be fixed now * more fixes _core & _dnn * another step towards green ci; even 0D mat's (a.k.a. scalars) are now partly supported! * * fixed strange bug in aruco/charuco detector, not sure why it did not work * also fixed a few remaining failures (hopefully) in dnn & core * disabled failing GAPI tests - too complex to dig into this compiler pipeline * hopefully fixed java tests * trying to fix some more tests * quick followup fix * continue to fix test failures and warnings * quick followup fix * trying to fix some more tests * partly fixed support for 0D/scalar UMat's * use updated parseReduce() from upstream * trying to fix the remaining test failures * fixed [ch]aruco tests in Python * still trying to fix tests * revert "fix" in dnn's CUDA tensor * trying to fix dnn+CUDA test failures * fixed 1D umat creation * hopefully fixed remaining cuda test failures * removed training whitespaces
277 lines
8.7 KiB
C++
277 lines
8.7 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) 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 "opencv2/ts/ocl_test.hpp"
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#ifdef HAVE_OPENCL
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namespace opencv_test {
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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(256, 1), 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 opencv_test::ocl
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#endif // HAVE_OPENCL
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