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Open Source Computer Vision Library
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488 lines
15 KiB
488 lines
15 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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// 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(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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virtual 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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{ |
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EXPECT_MAT_NEAR_RELATIVE(dst, udst, threshold); |
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EXPECT_MAT_NEAR_RELATIVE(dst_roi, udst_roi, threshold); |
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} |
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else |
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{ |
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EXPECT_MAT_NEAR(dst, udst, threshold); |
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EXPECT_MAT_NEAR(dst_roi, udst_roi, threshold); |
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} |
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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(double threshold = 0.0) |
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{ |
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EXPECT_MAT_NEAR(dst, udst, threshold); |
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EXPECT_MAT_NEAR(dst_roi, udst_roi, threshold); |
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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(1.1); |
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} |
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} |
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////////////////////////////////cornerMinEigenVal////////////////////////////////////////// |
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struct CornerTestBase : |
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public ImgprocTestBase |
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{ |
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virtual 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, DISABLED_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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Near(1e-5, 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, DISABLED_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-5, 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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virtual 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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{ |
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EXPECT_MAT_NEAR_RELATIVE(dst2, udst2, threshold); |
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EXPECT_MAT_NEAR_RELATIVE(dst2_roi, udst2_roi, threshold); |
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} |
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else |
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{ |
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EXPECT_MAT_NEAR(dst2, udst2, threshold); |
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EXPECT_MAT_NEAR(dst2_roi, udst2_roi, threshold); |
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} |
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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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/////////////////////////////////////////////////////////////////////////////////////////////////// |
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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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blockSize = GET_PARAM(1); |
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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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///////////////////////////////////////////////////////////////////////////////////////////////////////// |
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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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EXPECT_MAT_NEAR(dst, udst, threshold); |
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EXPECT_MAT_NEAR(dst_roi, udst_roi, 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, 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 cvtest::ocl |
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#endif // HAVE_OPENCL
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