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Open Source Computer Vision Library
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268 lines
7.5 KiB
268 lines
7.5 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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// 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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#define MAX_CHANNELS 4 |
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PARAM_TEST_CASE(MergeTestBase, MatType, int, bool) |
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{ |
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int type; |
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int channels; |
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bool use_roi; |
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//src mat |
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cv::Mat mat[MAX_CHANNELS]; |
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//dst 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[MAX_CHANNELS]; |
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int srcy[MAX_CHANNELS]; |
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int dstx, dsty; |
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//src mat with roi |
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cv::Mat mat_roi[MAX_CHANNELS]; |
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//dst mat with 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 gmat[MAX_CHANNELS]; |
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cv::ocl::oclMat gdst; |
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virtual void SetUp() |
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{ |
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type = 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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cv::Size size(MWIDTH, MHEIGHT); |
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for (int i = 0; i < channels; ++i) |
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mat[i] = randomMat(rng, size, CV_MAKETYPE(type, 1), 5, 16, false); |
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dst = randomMat(rng, size, CV_MAKETYPE(type, channels), 5, 16, 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, mat[0].cols); |
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roirows = rng.uniform(1, mat[0].rows); |
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for (int i = 0; i < channels; ++i) |
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{ |
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srcx[i] = rng.uniform(0, mat[i].cols - roicols); |
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srcy[i] = rng.uniform(0, mat[i].rows - roirows); |
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} |
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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[0].cols; |
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roirows = mat[0].rows; |
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for (int i = 0; i < channels; ++i) |
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srcx[i] = srcy[i] = 0; |
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dstx = dsty = 0; |
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} |
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for (int i = 0; i < channels; ++i) |
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mat_roi[i] = mat[i](Rect(srcx[i], srcy[i], 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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for (int i = 0; i < channels; ++i) |
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gmat[i] = mat_roi[i]; |
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} |
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}; |
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struct Merge : MergeTestBase {}; |
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TEST_P(Merge, Accuracy) |
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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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cv::merge(mat_roi, channels, dst_roi); |
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cv::ocl::merge(gmat, channels, 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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PARAM_TEST_CASE(SplitTestBase, MatType, int, bool) |
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{ |
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int type; |
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int channels; |
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bool use_roi; |
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//src mat |
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cv::Mat mat; |
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//dstmat |
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cv::Mat dst[MAX_CHANNELS]; |
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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[MAX_CHANNELS]; |
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int dsty[MAX_CHANNELS]; |
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//src mat with roi |
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cv::Mat mat_roi; |
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//dst mat with roi |
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cv::Mat dst_roi[MAX_CHANNELS]; |
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//ocl dst mat for testing |
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cv::ocl::oclMat gdst_whole[MAX_CHANNELS]; |
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//ocl mat with roi |
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cv::ocl::oclMat gmat; |
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cv::ocl::oclMat gdst[MAX_CHANNELS]; |
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virtual void SetUp() |
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{ |
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type = 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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cv::Size size(MWIDTH, MHEIGHT); |
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mat = randomMat(rng, size, CV_MAKETYPE(type, channels), 5, 16, false); |
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for (int i = 0; i < channels; ++i) |
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dst[i] = randomMat(rng, size, CV_MAKETYPE(type, 1), 5, 16, false); } |
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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, mat.cols); |
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roirows = rng.uniform(1, mat.rows); |
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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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for (int i = 0; i < channels; ++i) |
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{ |
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dstx[i] = rng.uniform(0, dst[i].cols - roicols); |
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dsty[i] = rng.uniform(0, dst[i].rows - roirows); |
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} |
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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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for (int i = 0; i < channels; ++i) |
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dstx[i] = dsty[i] = 0; |
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} |
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mat_roi = mat(Rect(srcx, srcy, roicols, roirows)); |
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for (int i = 0; i < channels; ++i) |
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dst_roi[i] = dst[i](Rect(dstx[i], dsty[i], roicols, roirows)); |
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for (int i = 0; i < channels; ++i) |
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{ |
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gdst_whole[i] = dst[i]; |
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gdst[i] = gdst_whole[i](Rect(dstx[i], dsty[i], roicols, roirows)); |
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} |
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gmat = mat_roi; |
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} |
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}; |
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struct Split : SplitTestBase {}; |
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TEST_P(Split, Accuracy) |
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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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cv::split(mat_roi, dst_roi); |
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cv::ocl::split(gmat, gdst); |
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for (int i = 0; i < channels; ++i) |
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EXPECT_MAT_NEAR(dst[i], Mat(gdst_whole[i]), 0.0); |
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} |
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} |
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INSTANTIATE_TEST_CASE_P(SplitMerge, Merge, Combine( |
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Values(CV_8U, CV_8S, CV_16U, CV_16S, CV_32S, CV_32F), Range(1, 5), Bool())); |
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INSTANTIATE_TEST_CASE_P(SplitMerge, Split , Combine( |
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Values(CV_8U, CV_8S, CV_16U, CV_16S, CV_32S, CV_32F), Range(1, 5), Bool())); |
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#endif // HAVE_OPENCL
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