623 lines
18 KiB
C++
623 lines
18 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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#ifdef HAVE_OPENCL
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using namespace testing;
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using namespace std;
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using namespace cv;
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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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Mat src, dst_whole, src_roi, dst_roi;
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ocl::oclMat gsrc_whole, gsrc_roi, gdst_whole, gdst_roi;
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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_whole, dst_roi, roiSize, dstBorder, type, 5, 16);
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generateOclMat(gsrc_whole, gsrc_roi, src, roiSize, srcBorder);
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generateOclMat(gdst_whole, gdst_roi, dst_whole, roiSize, dstBorder);
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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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Mat roi, whole;
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gdst_whole.download(whole);
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gdst_roi.download(roi);
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if (relative)
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{
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EXPECT_MAT_NEAR_RELATIVE(dst_whole, whole, threshold);
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EXPECT_MAT_NEAR_RELATIVE(dst_roi, roi, threshold);
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}
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else
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{
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EXPECT_MAT_NEAR(dst_whole, whole, threshold);
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EXPECT_MAT_NEAR(dst_roi, 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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Border, // 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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Border border;
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Scalar val;
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Mat src, dst_whole, src_roi, dst_roi;
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ocl::oclMat gsrc_whole, gsrc_roi, gdst_whole, gdst_roi;
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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_whole, dst_roi, roiSize, dstBorder, type, -MAX_VALUE, MAX_VALUE);
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generateOclMat(gsrc_whole, gsrc_roi, src, roiSize, srcBorder);
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generateOclMat(gdst_whole, gdst_roi, dst_whole, roiSize, dstBorder);
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}
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void Near(double threshold = 0.0)
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{
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Mat whole, roi;
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gdst_whole.download(whole);
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gdst_roi.download(roi);
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EXPECT_MAT_NEAR(dst_whole, whole, threshold);
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EXPECT_MAT_NEAR(dst_roi, 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 < LOOP_TIMES; ++i)
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{
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random_roi();
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cv::copyMakeBorder(src_roi, dst_roi, border.top, border.bot, border.lef, border.rig, borderType, val);
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ocl::copyMakeBorder(gsrc_roi, gdst_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 < LOOP_TIMES; j++)
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{
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random_roi();
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equalizeHist(src_roi, dst_roi);
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ocl::equalizeHist(gsrc_roi, gdst_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_whole, dst_roi, roiSize, dstBorder, CV_32FC1, 5, 16);
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generateOclMat(gsrc_whole, gsrc_roi, src, roiSize, srcBorder);
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generateOclMat(gdst_whole, gdst_roi, dst_whole, roiSize, dstBorder);
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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 < LOOP_TIMES; j++)
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{
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random_roi();
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int apertureSize = 3;
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cornerMinEigenVal(src_roi, dst_roi, blockSize, apertureSize, borderType);
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ocl::cornerMinEigenVal(gsrc_roi, gdst_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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struct CornerHarris :
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public ImgprocTestBase
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{
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void Near(double threshold = 0.0)
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{
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Mat whole, roi;
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gdst_whole.download(whole);
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gdst_roi.download(roi);
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absdiff(whole, dst_whole, whole);
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absdiff(roi, dst_roi, roi);
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divide(whole, dst_whole, whole);
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divide(roi, dst_roi, roi);
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absdiff(dst_whole, dst_whole, dst_whole);
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absdiff(dst_roi, dst_roi, dst_roi);
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EXPECT_MAT_NEAR(dst_whole, whole, threshold);
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EXPECT_MAT_NEAR(dst_roi, roi, threshold);
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}
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};
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OCL_TEST_P(CornerHarris, Mat)
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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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int apertureSize = 3;
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double k = randomDouble(0.01, 0.9);
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cornerHarris(src_roi, dst_roi, blockSize, apertureSize, k, borderType);
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ocl::cornerHarris(gsrc_roi, gdst_roi, blockSize, apertureSize, k, borderType);
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Near(1e-5);
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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;
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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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sdepth = 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(Integral, Mat1)
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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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ocl::integral(gsrc_roi, gdst_roi, sdepth);
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integral(src_roi, dst_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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Mat dst1;
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ocl::oclMat gdst1;
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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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integral(src_roi, dst_roi, dst1, sdepth);
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ocl::integral(gsrc_roi, gdst_roi, gdst1, sdepth);
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Near();
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if(gdst1.clCxt->supportsFeature(ocl::FEATURE_CL_DOUBLE))
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EXPECT_MAT_NEAR(dst1, Mat(gdst1), 0.);
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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 < 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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threshold(src_roi, dst_roi, thresh, maxVal, thresholdType);
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ocl::threshold(gsrc_roi, gdst_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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// calcHist
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static void calcHistGold(const Mat &src, Mat &hist)
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{
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hist = Mat(1, 256, CV_32SC1, Scalar::all(0));
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int * const hist_row = hist.ptr<int>();
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for (int y = 0; y < src.rows; ++y)
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{
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const uchar * const src_row = src.ptr(y);
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for (int x = 0; x < src.cols; ++x)
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++hist_row[src_row[x]];
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}
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}
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typedef ImgprocTestBase CalcHist;
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OCL_TEST_P(CalcHist, Mat)
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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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calcHistGold(src_roi, dst_roi);
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ocl::calcHist(gsrc_roi, gdst_roi);
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Near();
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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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Mat src, dst_whole, src_roi, dst_roi;
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ocl::oclMat gsrc_whole, gsrc_roi, gdst_whole, gdst_roi;
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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_whole, dst_roi, roiSize, dstBorder, CV_8UC1, 5, 16);
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generateOclMat(gsrc_whole, gsrc_roi, src, roiSize, srcBorder);
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generateOclMat(gdst_whole, gdst_roi, dst_whole, roiSize, dstBorder);
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}
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void Near(double threshold = 0.0)
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{
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Mat whole, roi;
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gdst_whole.download(whole);
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gdst_roi.download(roi);
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EXPECT_MAT_NEAR(dst_whole, whole, threshold);
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EXPECT_MAT_NEAR(dst_roi, 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 < LOOP_TIMES; ++i)
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{
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random_roi();
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Ptr<CLAHE> clahe = ocl::createCLAHE(clipLimit, gridSize);
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clahe->apply(gsrc_roi, gdst_roi);
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Ptr<CLAHE> clahe_gold = createCLAHE(clipLimit, gridSize);
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clahe_gold->apply(src_roi, dst_roi);
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Near(1.0);
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}
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}
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/////////////////////////////Convolve//////////////////////////////////
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static void convolve_gold(const Mat & src, const Mat & kernel, Mat & dst)
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{
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for (int i = 0; i < src.rows; i++)
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{
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float * const dstptr = dst.ptr<float>(i);
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for (int j = 0; j < src.cols; j++)
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{
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float temp = 0;
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for (int m = 0; m < kernel.rows; m++)
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{
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const float * const kptr = kernel.ptr<float>(m);
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for (int n = 0; n < kernel.cols; n++)
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{
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int r = clipInt(i - kernel.rows / 2 + m, 0, src.rows - 1);
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int c = clipInt(j - kernel.cols / 2 + n, 0, src.cols - 1);
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temp += src.ptr<float>(r)[c] * kptr[n];
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}
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}
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dstptr[j] = temp;
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}
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}
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}
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typedef ImgprocTestBase Convolve;
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OCL_TEST_P(Convolve, Mat)
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{
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Mat kernel, kernel_roi;
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ocl::oclMat gkernel, gkernel_roi;
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const Size roiSize(7, 7);
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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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Border kernelBorder = randomBorder(0, useRoi ? MAX_VALUE : 0);
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randomSubMat(kernel, kernel_roi, roiSize, kernelBorder, type, 5, 16);
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generateOclMat(gkernel, gkernel_roi, kernel, roiSize, kernelBorder);
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convolve_gold(src_roi, kernel_roi, dst_roi);
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ocl::convolve(gsrc_roi, gkernel_roi, gdst_roi);
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Near(1);
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}
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}
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////////////////////////////////// ColumnSum //////////////////////////////////////
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static void columnSum_gold(const Mat & src, Mat & dst)
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{
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float * prevdptr = dst.ptr<float>(0);
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const float * sptr = src.ptr<float>(0);
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for (int x = 0; x < src.cols; ++x)
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prevdptr[x] = sptr[x];
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for (int y = 1; y < src.rows; ++y)
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{
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sptr = src.ptr<float>(y);
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float * const dptr = dst.ptr<float>(y);
|
|
|
|
for (int x = 0; x < src.cols; ++x)
|
|
dptr[x] = prevdptr[x] + sptr[x];
|
|
|
|
prevdptr = dptr;
|
|
}
|
|
}
|
|
|
|
typedef ImgprocTestBase ColumnSum;
|
|
|
|
OCL_TEST_P(ColumnSum, Accuracy)
|
|
{
|
|
for (int i = 0; i < LOOP_TIMES; ++i)
|
|
{
|
|
random_roi();
|
|
|
|
columnSum_gold(src_roi, dst_roi);
|
|
ocl::columnSum(gsrc_roi, gdst_roi);
|
|
|
|
Near(1e-5);
|
|
}
|
|
}
|
|
|
|
/////////////////////////////////////////////////////////////////////////////////////
|
|
|
|
INSTANTIATE_TEST_CASE_P(Imgproc, EqualizeHist, Combine(
|
|
Values((MatType)CV_8UC1),
|
|
Values(0), // not used
|
|
Values(0), // not used
|
|
Bool()));
|
|
|
|
INSTANTIATE_TEST_CASE_P(Imgproc, CornerMinEigenVal, Combine(
|
|
Values((MatType)CV_8UC1, (MatType)CV_32FC1),
|
|
Values(3, 5),
|
|
Values((int)BORDER_CONSTANT, (int)BORDER_REPLICATE, (int)BORDER_REFLECT, (int)BORDER_REFLECT101),
|
|
Bool()));
|
|
|
|
INSTANTIATE_TEST_CASE_P(Imgproc, CornerHarris, Combine(
|
|
Values((MatType)CV_8UC1, CV_32FC1),
|
|
Values(3, 5),
|
|
Values( (int)BORDER_CONSTANT, (int)BORDER_REPLICATE, (int)BORDER_REFLECT, (int)BORDER_REFLECT_101),
|
|
Bool()));
|
|
|
|
INSTANTIATE_TEST_CASE_P(Imgproc, Integral, Combine(
|
|
Values((MatType)CV_8UC1), // TODO does not work with CV_32F, CV_64F
|
|
Values(0), // not used
|
|
Values((MatType)CV_32SC1, (MatType)CV_32FC1),
|
|
Bool()));
|
|
|
|
INSTANTIATE_TEST_CASE_P(Imgproc, Threshold, Combine(
|
|
Values(CV_8UC1, CV_8UC2, CV_8UC3, CV_8UC4,
|
|
CV_16SC1, CV_16SC2, CV_16SC3, CV_16SC4,
|
|
CV_32FC1, CV_32FC2, CV_32FC3, CV_32FC4),
|
|
Values(0),
|
|
Values(ThreshOp(THRESH_BINARY),
|
|
ThreshOp(THRESH_BINARY_INV), ThreshOp(THRESH_TRUNC),
|
|
ThreshOp(THRESH_TOZERO), ThreshOp(THRESH_TOZERO_INV)),
|
|
Bool()));
|
|
|
|
INSTANTIATE_TEST_CASE_P(Imgproc, CalcHist, Combine(
|
|
Values((MatType)CV_8UC1),
|
|
Values(0), // not used
|
|
Values(0), // not used
|
|
Bool()));
|
|
|
|
INSTANTIATE_TEST_CASE_P(Imgproc, CLAHETest, Combine(
|
|
Values(Size(4, 4), Size(32, 8), Size(8, 64)),
|
|
Values(0.0, 10.0, 62.0, 300.0),
|
|
Bool()));
|
|
|
|
INSTANTIATE_TEST_CASE_P(Imgproc, Convolve, Combine(
|
|
Values((MatType)CV_32FC1),
|
|
Values(0), // not used
|
|
Values(0), // not used
|
|
Bool()));
|
|
|
|
INSTANTIATE_TEST_CASE_P(Imgproc, ColumnSum, Combine(
|
|
Values(MatType(CV_32FC1)),
|
|
Values(0), // not used
|
|
Values(0), // not used
|
|
Bool()));
|
|
|
|
INSTANTIATE_TEST_CASE_P(ImgprocTestBase, CopyMakeBorder, Combine(
|
|
testing::Values((MatDepth)CV_8U, (MatDepth)CV_16S, (MatDepth)CV_32S, (MatDepth)CV_32F),
|
|
testing::Values(Channels(1), Channels(3), (Channels)4),
|
|
Bool(), // border isolated or not
|
|
Values((Border)BORDER_REPLICATE, (Border)BORDER_REFLECT,
|
|
(Border)BORDER_WRAP, (Border)BORDER_REFLECT_101),
|
|
Bool()));
|
|
|
|
#endif // HAVE_OPENCL
|