501 lines
16 KiB
C++
501 lines
16 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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// 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(ImgprocTestBase, MatType,
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int, // blockSize
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int, // border type
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bool) // roi or not
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{
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int type, borderType, blockSize;
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bool useRoi;
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TEST_DECLARE_INPUT_PARAMETER(src);
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TEST_DECLARE_OUTPUT_PARAMETER(dst);
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virtual void SetUp()
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{
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type = GET_PARAM(0);
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blockSize = GET_PARAM(1);
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borderType = GET_PARAM(2);
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useRoi = GET_PARAM(3);
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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, type, 5, 256);
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Border dstBorder = randomBorder(0, useRoi ? MAX_VALUE : 0);
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randomSubMat(dst, dst_roi, roiSize, dstBorder, type, 5, 16);
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UMAT_UPLOAD_INPUT_PARAMETER(src);
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UMAT_UPLOAD_OUTPUT_PARAMETER(dst);
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}
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void Near(double threshold = 0.0, bool relative = false)
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{
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if (relative)
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OCL_EXPECT_MATS_NEAR_RELATIVE(dst, threshold);
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else
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OCL_EXPECT_MATS_NEAR(dst, threshold);
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}
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};
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//////////////////////////////// copyMakeBorder ////////////////////////////////////////////
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PARAM_TEST_CASE(CopyMakeBorder, MatDepth, // depth
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Channels, // channels
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bool, // isolated or not
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BorderType, // border type
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bool) // roi or not
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{
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int type, borderType;
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bool useRoi;
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TestUtils::Border border;
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Scalar val;
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TEST_DECLARE_INPUT_PARAMETER(src);
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TEST_DECLARE_OUTPUT_PARAMETER(dst);
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virtual void SetUp()
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{
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type = CV_MAKE_TYPE(GET_PARAM(0), GET_PARAM(1));
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borderType = GET_PARAM(3);
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if (GET_PARAM(2))
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borderType |= BORDER_ISOLATED;
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useRoi = GET_PARAM(4);
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}
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void random_roi()
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{
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border = randomBorder(0, MAX_VALUE << 2);
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val = randomScalar(-MAX_VALUE, MAX_VALUE);
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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, type, -MAX_VALUE, MAX_VALUE);
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Border dstBorder = randomBorder(0, useRoi ? MAX_VALUE : 0);
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dstBorder.top += border.top;
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dstBorder.lef += border.lef;
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dstBorder.rig += border.rig;
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dstBorder.bot += border.bot;
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randomSubMat(dst, dst_roi, roiSize, dstBorder, type, -MAX_VALUE, MAX_VALUE);
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UMAT_UPLOAD_INPUT_PARAMETER(src);
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UMAT_UPLOAD_OUTPUT_PARAMETER(dst);
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}
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void Near()
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{
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OCL_EXPECT_MATS_NEAR(dst, 0);
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}
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};
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OCL_TEST_P(CopyMakeBorder, Mat)
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{
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for (int i = 0; i < test_loop_times; ++i)
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{
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random_roi();
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OCL_OFF(cv::copyMakeBorder(src_roi, dst_roi, border.top, border.bot, border.lef, border.rig, borderType, val));
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OCL_ON(cv::copyMakeBorder(usrc_roi, udst_roi, border.top, border.bot, border.lef, border.rig, borderType, val));
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Near();
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}
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}
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//////////////////////////////// equalizeHist //////////////////////////////////////////////
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typedef ImgprocTestBase EqualizeHist;
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OCL_TEST_P(EqualizeHist, 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::equalizeHist(src_roi, dst_roi));
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OCL_ON(cv::equalizeHist(usrc_roi, udst_roi));
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Near(1);
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}
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}
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//////////////////////////////// Corners test //////////////////////////////////////////
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struct CornerTestBase :
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public ImgprocTestBase
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{
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void random_roi()
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{
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Mat image = readImageType("../gpu/stereobm/aloe-L.png", type);
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ASSERT_FALSE(image.empty());
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bool isFP = CV_MAT_DEPTH(type) >= CV_32F;
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float val = 255.0f;
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if (isFP)
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{
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image.convertTo(image, -1, 1.0 / 255);
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val /= 255.0f;
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}
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Size roiSize = image.size();
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Border srcBorder = randomBorder(0, useRoi ? MAX_VALUE : 0);
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Size wholeSize = Size(roiSize.width + srcBorder.lef + srcBorder.rig, roiSize.height + srcBorder.top + srcBorder.bot);
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src = randomMat(wholeSize, type, -val, val, false);
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src_roi = src(Rect(srcBorder.lef, srcBorder.top, roiSize.width, roiSize.height));
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image.copyTo(src_roi);
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Border dstBorder = randomBorder(0, useRoi ? MAX_VALUE : 0);
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randomSubMat(dst, dst_roi, roiSize, dstBorder, CV_32FC1, 5, 16);
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UMAT_UPLOAD_INPUT_PARAMETER(src);
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UMAT_UPLOAD_OUTPUT_PARAMETER(dst);
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}
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};
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typedef CornerTestBase CornerMinEigenVal;
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OCL_TEST_P(CornerMinEigenVal, 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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int apertureSize = 3;
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OCL_OFF(cv::cornerMinEigenVal(src_roi, dst_roi, blockSize, apertureSize, borderType));
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OCL_ON(cv::cornerMinEigenVal(usrc_roi, udst_roi, blockSize, apertureSize, borderType));
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// The corner kernel uses native_sqrt() which has implementation defined accuracy.
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// If we're using a CL implementation that isn't intel, test with relaxed accuracy.
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if (!ocl::useOpenCL() || ocl::Device::getDefault().isIntel())
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Near(1e-5, true);
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else
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Near(0.1, true);
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}
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}
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//////////////////////////////// cornerHarris //////////////////////////////////////////
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typedef CornerTestBase CornerHarris;
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OCL_TEST_P(CornerHarris, 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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int apertureSize = 3;
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double k = randomDouble(0.01, 0.9);
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OCL_OFF(cv::cornerHarris(src_roi, dst_roi, blockSize, apertureSize, k, borderType));
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OCL_ON(cv::cornerHarris(usrc_roi, udst_roi, blockSize, apertureSize, k, borderType));
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Near(1e-6, true);
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}
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}
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//////////////////////////////// preCornerDetect //////////////////////////////////////////
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typedef ImgprocTestBase PreCornerDetect;
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OCL_TEST_P(PreCornerDetect, 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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const int apertureSize = blockSize;
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OCL_OFF(cv::preCornerDetect(src_roi, dst_roi, apertureSize, borderType));
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OCL_ON(cv::preCornerDetect(usrc_roi, udst_roi, apertureSize, borderType));
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Near(1e-6, true);
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}
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}
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////////////////////////////////// integral /////////////////////////////////////////////////
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struct Integral :
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public ImgprocTestBase
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{
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int sdepth, sqdepth;
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TEST_DECLARE_OUTPUT_PARAMETER(dst2);
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virtual void SetUp()
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{
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type = GET_PARAM(0);
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sdepth = GET_PARAM(1);
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sqdepth = GET_PARAM(2);
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useRoi = GET_PARAM(3);
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}
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void random_roi()
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{
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ASSERT_EQ(CV_MAT_CN(type), 1);
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Size roiSize = randomSize(1, MAX_VALUE), isize = Size(roiSize.width + 1, roiSize.height + 1);
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Border srcBorder = randomBorder(0, useRoi ? 2 : 0);
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randomSubMat(src, src_roi, roiSize, srcBorder, type, 5, 256);
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Border dstBorder = randomBorder(0, useRoi ? 2 : 0);
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randomSubMat(dst, dst_roi, isize, dstBorder, sdepth, 5, 16);
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Border dst2Border = randomBorder(0, useRoi ? 2 : 0);
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randomSubMat(dst2, dst2_roi, isize, dst2Border, sqdepth, 5, 16);
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UMAT_UPLOAD_INPUT_PARAMETER(src);
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UMAT_UPLOAD_OUTPUT_PARAMETER(dst);
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UMAT_UPLOAD_OUTPUT_PARAMETER(dst2);
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}
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void Near2(double threshold = 0.0, bool relative = false)
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{
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if (relative)
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OCL_EXPECT_MATS_NEAR_RELATIVE(dst2, threshold);
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else
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OCL_EXPECT_MATS_NEAR(dst2, threshold);
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}
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};
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OCL_TEST_P(Integral, Mat1)
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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::integral(src_roi, dst_roi, sdepth));
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OCL_ON(cv::integral(usrc_roi, udst_roi, sdepth));
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Near();
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}
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}
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OCL_TEST_P(Integral, Mat2)
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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::integral(src_roi, dst_roi, dst2_roi, sdepth, sqdepth));
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OCL_ON(cv::integral(usrc_roi, udst_roi, udst2_roi, sdepth, sqdepth));
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Near();
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sqdepth == CV_32F ? Near2(1e-6, true) : Near2();
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}
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}
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//////////////////////////////////////// threshold //////////////////////////////////////////////
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struct Threshold :
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public ImgprocTestBase
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{
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int thresholdType;
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virtual void SetUp()
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{
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type = GET_PARAM(0);
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thresholdType = GET_PARAM(2);
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useRoi = GET_PARAM(3);
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}
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};
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OCL_TEST_P(Threshold, 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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double maxVal = randomDouble(20.0, 127.0);
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double thresh = randomDouble(0.0, maxVal);
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OCL_OFF(cv::threshold(src_roi, dst_roi, thresh, maxVal, thresholdType));
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OCL_ON(cv::threshold(usrc_roi, udst_roi, thresh, maxVal, thresholdType));
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Near(1);
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}
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}
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/////////////////////////////////////////// CLAHE //////////////////////////////////////////////////
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PARAM_TEST_CASE(CLAHETest, Size, double, bool)
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{
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Size gridSize;
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double clipLimit;
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bool useRoi;
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TEST_DECLARE_INPUT_PARAMETER(src);
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TEST_DECLARE_OUTPUT_PARAMETER(dst);
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virtual void SetUp()
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{
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gridSize = GET_PARAM(0);
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clipLimit = GET_PARAM(1);
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useRoi = GET_PARAM(2);
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}
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void random_roi()
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{
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Size roiSize = randomSize(std::max(gridSize.height, gridSize.width), 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, 5, 256);
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Border dstBorder = randomBorder(0, useRoi ? MAX_VALUE : 0);
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randomSubMat(dst, dst_roi, roiSize, dstBorder, CV_8UC1, 5, 16);
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UMAT_UPLOAD_INPUT_PARAMETER(src);
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UMAT_UPLOAD_OUTPUT_PARAMETER(dst);
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}
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void Near(double threshold = 0.0)
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{
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OCL_EXPECT_MATS_NEAR(dst, threshold);
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}
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};
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OCL_TEST_P(CLAHETest, Accuracy)
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{
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for (int i = 0; i < test_loop_times; ++i)
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{
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random_roi();
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Ptr<CLAHE> clahe = cv::createCLAHE(clipLimit, gridSize);
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OCL_OFF(clahe->apply(src_roi, dst_roi));
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OCL_ON(clahe->apply(usrc_roi, udst_roi));
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Near(1.0);
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}
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}
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/////////////////////////////////////////////////////////////////////////////////////
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OCL_INSTANTIATE_TEST_CASE_P(Imgproc, EqualizeHist, Combine(
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Values((MatType)CV_8UC1),
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Values(0), // not used
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Values(0), // not used
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Bool()));
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OCL_INSTANTIATE_TEST_CASE_P(Imgproc, CornerMinEigenVal, Combine(
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Values((MatType)CV_8UC1, (MatType)CV_32FC1),
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Values(3, 5),
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Values((BorderType)BORDER_CONSTANT, (BorderType)BORDER_REPLICATE,
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(BorderType)BORDER_REFLECT, (BorderType)BORDER_REFLECT101),
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Bool()));
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OCL_INSTANTIATE_TEST_CASE_P(Imgproc, CornerHarris, Combine(
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Values((MatType)CV_8UC1, CV_32FC1),
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Values(3, 5),
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Values( (BorderType)BORDER_CONSTANT, (BorderType)BORDER_REPLICATE,
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(BorderType)BORDER_REFLECT, (BorderType)BORDER_REFLECT_101),
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Bool()));
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OCL_INSTANTIATE_TEST_CASE_P(Imgproc, PreCornerDetect, Combine(
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Values((MatType)CV_8UC1, CV_32FC1),
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Values(3, 5),
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Values( (BorderType)BORDER_CONSTANT, (BorderType)BORDER_REPLICATE,
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(BorderType)BORDER_REFLECT, (BorderType)BORDER_REFLECT_101),
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Bool()));
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OCL_INSTANTIATE_TEST_CASE_P(Imgproc, Integral, Combine(
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Values((MatType)CV_8UC1), // TODO does not work with CV_32F, CV_64F
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Values(CV_32SC1, CV_32FC1), // desired sdepth
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Values(CV_32FC1, CV_64FC1), // desired sqdepth
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Bool()));
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OCL_INSTANTIATE_TEST_CASE_P(Imgproc, Threshold, Combine(
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Values(CV_8UC1, CV_8UC2, CV_8UC3, CV_8UC4,
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CV_16SC1, CV_16SC2, CV_16SC3, CV_16SC4,
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CV_32FC1, CV_32FC2, CV_32FC3, CV_32FC4),
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Values(0),
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Values(ThreshOp(THRESH_BINARY),
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ThreshOp(THRESH_BINARY_INV), ThreshOp(THRESH_TRUNC),
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ThreshOp(THRESH_TOZERO), ThreshOp(THRESH_TOZERO_INV)),
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Bool()));
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OCL_INSTANTIATE_TEST_CASE_P(Imgproc, CLAHETest, Combine(
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Values(Size(4, 4), Size(32, 8), Size(8, 64)),
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Values(0.0, 10.0, 62.0, 300.0),
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Bool()));
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OCL_INSTANTIATE_TEST_CASE_P(ImgprocTestBase, CopyMakeBorder, Combine(
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testing::Values((MatDepth)CV_8U, (MatDepth)CV_16S, (MatDepth)CV_32S, (MatDepth)CV_32F),
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testing::Values(Channels(1), Channels(3), (Channels)4),
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Bool(), // border isolated or not
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Values((BorderType)BORDER_CONSTANT, (BorderType)BORDER_REPLICATE, (BorderType)BORDER_REFLECT,
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(BorderType)BORDER_WRAP, (BorderType)BORDER_REFLECT_101),
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Bool()));
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} } // namespace opencv_test::ocl
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#endif // HAVE_OPENCL
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