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464 lines
13 KiB
C++
464 lines
13 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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// Third party copyrights are property of their respective owners.
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//
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// @Authors
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// Jia Haipeng, jiahaipeng95@gmail.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 oclMaterials 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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#ifdef HAVE_OPENCL
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using namespace cvtest;
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using namespace testing;
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using namespace std;
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////////////////////////////////converto/////////////////////////////////////////////////
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PARAM_TEST_CASE(ConvertToTestBase, MatType, MatType, int, bool)
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{
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int src_depth, dst_depth;
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int cn, dst_type;
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bool use_roi;
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// src mat
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cv::Mat mat;
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cv::Mat dst;
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// set up roi
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int roicols, roirows;
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int srcx, srcy;
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int dstx, dsty;
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// src mat with roi
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cv::Mat mat_roi;
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cv::Mat dst_roi;
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// ocl dst mat for testing
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cv::ocl::oclMat gdst_whole;
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// ocl mat with roi
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cv::ocl::oclMat gsrc;
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cv::ocl::oclMat gdst;
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virtual void SetUp()
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{
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src_depth = GET_PARAM(0);
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dst_depth = GET_PARAM(1);
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cn = GET_PARAM(2);
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int src_type = CV_MAKE_TYPE(src_depth, cn);
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dst_type = CV_MAKE_TYPE(dst_depth, cn);
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use_roi = GET_PARAM(3);
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cv::RNG &rng = TS::ptr()->get_rng();
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mat = randomMat(rng, randomSize(MIN_VALUE, MAX_VALUE), src_type, 5, 136, false);
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dst = randomMat(rng, use_roi ? randomSize(MIN_VALUE, MAX_VALUE) : mat.size(), dst_type, 5, 136, false);
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}
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void random_roi()
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{
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if (use_roi)
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{
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// randomize ROI
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cv::RNG &rng = TS::ptr()->get_rng();
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roicols = rng.uniform(1, MIN_VALUE);
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roirows = rng.uniform(1, MIN_VALUE);
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srcx = rng.uniform(0, mat.cols - roicols);
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srcy = rng.uniform(0, mat.rows - roirows);
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dstx = rng.uniform(0, dst.cols - roicols);
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dsty = rng.uniform(0, dst.rows - roirows);
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}
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else
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{
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roicols = mat.cols;
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roirows = mat.rows;
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srcx = srcy = 0;
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dstx = dsty = 0;
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}
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mat_roi = mat(Rect(srcx, srcy, roicols, roirows));
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dst_roi = dst(Rect(dstx, dsty, roicols, roirows));
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gdst_whole = dst;
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gdst = gdst_whole(Rect(dstx, dsty, roicols, roirows));
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gsrc = mat_roi;
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}
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};
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typedef ConvertToTestBase ConvertTo;
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TEST_P(ConvertTo, Accuracy)
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{
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if((src_depth == CV_64F || dst_depth == CV_64F) &&
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!cv::ocl::Context::getContext()->supportsFeature(cv::ocl::Context::CL_DOUBLE))
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{
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return; // returns silently
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}
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for (int j = 0; j < LOOP_TIMES; j++)
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{
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random_roi();
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mat_roi.convertTo(dst_roi, dst_type);
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gsrc.convertTo(gdst, dst_type);
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EXPECT_MAT_NEAR(dst, Mat(gdst_whole), src_depth == CV_64F ? 1.0 : 0.0);
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EXPECT_MAT_NEAR(dst_roi, Mat(gdst), src_depth == CV_64F ? 1.0 : 0.0);
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}
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}
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///////////////////////////////////////////copyto/////////////////////////////////////////////////////////////
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PARAM_TEST_CASE(CopyToTestBase, MatType, int, bool)
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{
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bool use_roi;
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cv::Mat src, mask, dst;
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// set up roi
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int roicols,roirows;
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int srcx, srcy;
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int dstx, dsty;
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int maskx,masky;
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// src mat with roi
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cv::Mat src_roi;
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cv::Mat mask_roi;
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cv::Mat dst_roi;
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// ocl dst mat for testing
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cv::ocl::oclMat gdst_whole;
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// ocl mat with roi
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cv::ocl::oclMat gsrc, gdst, gmask;
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virtual void SetUp()
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{
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int type = CV_MAKETYPE(GET_PARAM(0), GET_PARAM(1));
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use_roi = GET_PARAM(2);
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cv::RNG &rng = TS::ptr()->get_rng();
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src = randomMat(rng, randomSize(MIN_VALUE, MAX_VALUE), type, 5, 16, false);
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dst = randomMat(rng, use_roi ? randomSize(MIN_VALUE, MAX_VALUE) : src.size(), type, 5, 16, false);
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mask = randomMat(rng, use_roi ? randomSize(MIN_VALUE, MAX_VALUE) : src.size(), CV_8UC1, 0, 2, false);
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cv::threshold(mask, mask, 0.5, 255., CV_8UC1);
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}
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void random_roi()
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{
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if (use_roi)
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{
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// randomize ROI
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cv::RNG &rng = TS::ptr()->get_rng();
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roicols = rng.uniform(1, MIN_VALUE);
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roirows = rng.uniform(1, MIN_VALUE);
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srcx = rng.uniform(0, src.cols - roicols);
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srcy = rng.uniform(0, src.rows - roirows);
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dstx = rng.uniform(0, dst.cols - roicols);
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dsty = rng.uniform(0, dst.rows - roirows);
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maskx = rng.uniform(0, mask.cols - roicols);
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masky = rng.uniform(0, mask.rows - roirows);
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}
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else
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{
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roicols = src.cols;
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roirows = src.rows;
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srcx = srcy = 0;
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dstx = dsty = 0;
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maskx = masky = 0;
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}
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src_roi = src(Rect(srcx, srcy, roicols, roirows));
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mask_roi = mask(Rect(maskx, masky, roicols, roirows));
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dst_roi = dst(Rect(dstx, dsty, roicols, roirows));
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gdst_whole = dst;
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gdst = gdst_whole(Rect(dstx, dsty, roicols, roirows));
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gsrc = src_roi;
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gmask = mask_roi;
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}
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};
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typedef CopyToTestBase CopyTo;
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TEST_P(CopyTo, Without_mask)
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{
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if((src.depth() == CV_64F) &&
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!cv::ocl::Context::getContext()->supportsFeature(cv::ocl::Context::CL_DOUBLE))
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{
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return; // returns silently
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}
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for (int j = 0; j < LOOP_TIMES; j++)
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{
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random_roi();
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src_roi.copyTo(dst_roi);
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gsrc.copyTo(gdst);
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EXPECT_MAT_NEAR(dst, Mat(gdst_whole), 0.0);
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}
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}
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TEST_P(CopyTo, With_mask)
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{
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if(src.depth() == CV_64F &&
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!cv::ocl::Context::getContext()->supportsFeature(cv::ocl::Context::CL_DOUBLE))
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{
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return; // returns silently
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}
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for (int j = 0; j < LOOP_TIMES; j++)
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{
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random_roi();
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src_roi.copyTo(dst_roi, mask_roi);
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gsrc.copyTo(gdst, gmask);
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EXPECT_MAT_NEAR(dst, Mat(gdst_whole), 0.0);
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}
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}
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/////////////////////////////////////////// setTo /////////////////////////////////////////////////////////////
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PARAM_TEST_CASE(SetToTestBase, MatType, int, bool)
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{
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int depth, channels;
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bool use_roi;
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cv::Scalar val;
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cv::Mat src;
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cv::Mat mask;
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// set up roi
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int roicols, roirows;
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int srcx, srcy;
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int maskx, masky;
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// src mat with roi
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cv::Mat src_roi;
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cv::Mat mask_roi;
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// ocl dst mat for testing
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cv::ocl::oclMat gsrc_whole;
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// ocl mat with roi
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cv::ocl::oclMat gsrc;
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cv::ocl::oclMat gmask;
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virtual void SetUp()
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{
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depth = GET_PARAM(0);
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channels = GET_PARAM(1);
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use_roi = GET_PARAM(2);
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cv::RNG &rng = TS::ptr()->get_rng();
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int type = CV_MAKE_TYPE(depth, channels);
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src = randomMat(rng, randomSize(MIN_VALUE, MAX_VALUE), type, 5, 16, false);
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mask = randomMat(rng, use_roi ? randomSize(MIN_VALUE, MAX_VALUE) : src.size(), CV_8UC1, 0, 2, false);
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cv::threshold(mask, mask, 0.5, 255., CV_8UC1);
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val = cv::Scalar(rng.uniform(-10.0, 10.0), rng.uniform(-10.0, 10.0),
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rng.uniform(-10.0, 10.0), rng.uniform(-10.0, 10.0));
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}
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void random_roi()
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{
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if (use_roi)
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{
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// randomize ROI
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cv::RNG &rng = TS::ptr()->get_rng();
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roicols = rng.uniform(1, MIN_VALUE);
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roirows = rng.uniform(1, MIN_VALUE);
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srcx = rng.uniform(0, src.cols - roicols);
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srcy = rng.uniform(0, src.rows - roirows);
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maskx = rng.uniform(0, mask.cols - roicols);
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masky = rng.uniform(0, mask.rows - roirows);
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}
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else
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{
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roicols = src.cols;
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roirows = src.rows;
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srcx = srcy = 0;
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maskx = masky = 0;
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}
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src_roi = src(Rect(srcx, srcy, roicols, roirows));
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mask_roi = mask(Rect(maskx, masky, roicols, roirows));
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gsrc_whole = src;
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gsrc = gsrc_whole(Rect(srcx, srcy, roicols, roirows));
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gmask = mask_roi;
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}
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};
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typedef SetToTestBase SetTo;
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TEST_P(SetTo, Without_mask)
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{
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if(depth == CV_64F &&
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!cv::ocl::Context::getContext()->supportsFeature(cv::ocl::Context::CL_DOUBLE))
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{
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return; // returns silently
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}
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for (int j = 0; j < LOOP_TIMES; j++)
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{
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random_roi();
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src_roi.setTo(val);
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gsrc.setTo(val);
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EXPECT_MAT_NEAR(src, Mat(gsrc_whole), 1.);
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}
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}
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TEST_P(SetTo, With_mask)
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{
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if(depth == CV_64F &&
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!cv::ocl::Context::getContext()->supportsFeature(cv::ocl::Context::CL_DOUBLE))
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{
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return; // returns silently
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}
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for (int j = 0; j < LOOP_TIMES; j++)
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{
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random_roi();
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src_roi.setTo(val, mask_roi);
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gsrc.setTo(val, gmask);
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EXPECT_MAT_NEAR(src, Mat(gsrc_whole), 1.);
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}
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}
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// convertC3C4
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PARAM_TEST_CASE(convertC3C4, MatType, bool)
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{
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int depth;
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bool use_roi;
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//src mat
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cv::Mat src;
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// set up roi
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int roicols, roirows;
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int srcx, srcy;
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//src mat with roi
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cv::Mat src_roi;
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//ocl mat with roi
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cv::ocl::oclMat gsrc_roi;
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virtual void SetUp()
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{
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depth = GET_PARAM(0);
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use_roi = GET_PARAM(1);
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int type = CV_MAKE_TYPE(depth, 3);
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cv::RNG &rng = TS::ptr()->get_rng();
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src = randomMat(rng, randomSize(1, MAX_VALUE), type, 0, 40, false);
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}
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void random_roi()
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{
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if (use_roi)
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{
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//randomize ROI
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cv::RNG &rng = TS::ptr()->get_rng();
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roicols = rng.uniform(1, src.cols);
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roirows = rng.uniform(1, src.rows);
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srcx = rng.uniform(0, src.cols - roicols);
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srcy = rng.uniform(0, src.rows - roirows);
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}
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else
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{
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roicols = src.cols;
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roirows = src.rows;
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srcx = srcy = 0;
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}
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src_roi = src(Rect(srcx, srcy, roicols, roirows));
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}
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};
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TEST_P(convertC3C4, Accuracy)
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{
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if(depth == CV_64F &&
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!cv::ocl::Context::getContext()->supportsFeature(cv::ocl::Context::CL_DOUBLE))
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{
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return; // returns silently
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}
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for (int j = 0; j < LOOP_TIMES; j++)
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{
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random_roi();
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gsrc_roi = src_roi;
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EXPECT_MAT_NEAR(src_roi, Mat(gsrc_roi), 0.0);
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}
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}
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INSTANTIATE_TEST_CASE_P(MatrixOperation, ConvertTo, Combine(
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Values(CV_8U, CV_8S, CV_16U, CV_16S, CV_32S, CV_32F, CV_64F),
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Values(CV_8U, CV_8S, CV_16U, CV_16S, CV_32S, CV_32F, CV_64F),
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Range(1, 5), Bool()));
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INSTANTIATE_TEST_CASE_P(MatrixOperation, CopyTo, Combine(
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Values(CV_8U, CV_8S, CV_16U, CV_16S, CV_32S, CV_32F, CV_64F),
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testing::Range(1, 5), Bool()));
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INSTANTIATE_TEST_CASE_P(MatrixOperation, SetTo, Combine(
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Values(CV_8U, CV_8S, CV_16U, CV_16S, CV_32S, CV_32F, CV_64F),
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testing::Range(1, 5), Bool()));
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INSTANTIATE_TEST_CASE_P(MatrixOperation, convertC3C4, Combine(
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Values(CV_8U, CV_8S, CV_16U, CV_16S, CV_32S, CV_32F, CV_64F),
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Bool()));
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#endif
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