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Open Source Computer Vision Library
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176 lines
6.8 KiB
176 lines
6.8 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, Multicoreware, Inc., all rights reserved. |
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// Copyright (C) 2010-2012, Advanced Micro Devices, 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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// Nathan, liujun@multicorewareinc.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 <iomanip> |
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using namespace cv; |
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using namespace cv::ocl; |
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using namespace testing; |
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using namespace std; |
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template <typename T> |
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static void blendLinearGold(const Mat &img1, const Mat &img2, |
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const Mat &weights1, const Mat &weights2, |
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Mat &result_gold) |
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{ |
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CV_Assert(img1.size() == img2.size() && img1.type() == img2.type()); |
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CV_Assert(weights1.size() == weights2.size() && weights1.size() == img1.size() && |
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weights1.type() == CV_32FC1 && weights2.type() == CV_32FC1); |
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result_gold.create(img1.size(), img1.type()); |
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int cn = img1.channels(); |
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int step1 = img1.cols * img1.channels(); |
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for (int y = 0; y < img1.rows; ++y) |
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{ |
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const float * const weights1_row = weights1.ptr<float>(y); |
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const float * const weights2_row = weights2.ptr<float>(y); |
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const T * const img1_row = img1.ptr<T>(y); |
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const T * const img2_row = img2.ptr<T>(y); |
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T * const result_gold_row = result_gold.ptr<T>(y); |
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for (int x = 0; x < step1; ++x) |
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{ |
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int x1 = x / cn; |
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float w1 = weights1_row[x1], w2 = weights2_row[x1]; |
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result_gold_row[x] = saturate_cast<T>(((float)img1_row[x] * w1 |
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+ (float)img2_row[x] * w2) / (w1 + w2 + 1e-5f)); |
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} |
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} |
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} |
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PARAM_TEST_CASE(Blend, MatDepth, int, bool) |
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{ |
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int depth, channels; |
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bool useRoi; |
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Mat src1, src2, weights1, weights2, dst; |
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Mat src1_roi, src2_roi, weights1_roi, weights2_roi, dst_roi; |
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oclMat gsrc1, gsrc2, gweights1, gweights2, gdst, gst; |
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oclMat gsrc1_roi, gsrc2_roi, gweights1_roi, gweights2_roi, gdst_roi; |
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virtual void SetUp() |
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{ |
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depth = GET_PARAM(0); |
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channels = GET_PARAM(1); |
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useRoi = GET_PARAM(2); |
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} |
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void random_roi() |
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{ |
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const int type = CV_MAKE_TYPE(depth, channels); |
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const double upValue = 256; |
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const double sumMinValue = 0.01; // we don't want to divide by "zero" |
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Size roiSize = randomSize(1, 20); |
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Border src1Border = randomBorder(0, useRoi ? MAX_VALUE : 0); |
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randomSubMat(src1, src1_roi, roiSize, src1Border, type, -upValue, upValue); |
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Border src2Border = randomBorder(0, useRoi ? MAX_VALUE : 0); |
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randomSubMat(src2, src2_roi, roiSize, src2Border, type, -upValue, upValue); |
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Border weights1Border = randomBorder(0, useRoi ? MAX_VALUE : 0); |
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randomSubMat(weights1, weights1_roi, roiSize, weights1Border, CV_32FC1, -upValue, upValue); |
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Border weights2Border = randomBorder(0, useRoi ? MAX_VALUE : 0); |
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randomSubMat(weights2, weights2_roi, roiSize, weights2Border, CV_32FC1, sumMinValue, upValue); // fill it as a (w1 + w12) |
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weights2_roi = weights2_roi - weights1_roi; |
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// check that weights2_roi is still a part of weights2 (not a new matrix) |
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CV_Assert(checkNorm(weights2_roi, |
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weights2(Rect(weights2Border.lef, weights2Border.top, roiSize.width, roiSize.height))) < 1e-6); |
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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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generateOclMat(gsrc1, gsrc1_roi, src1, roiSize, src1Border); |
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generateOclMat(gsrc2, gsrc2_roi, src2, roiSize, src2Border); |
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generateOclMat(gweights1, gweights1_roi, weights1, roiSize, weights1Border); |
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generateOclMat(gweights2, gweights2_roi, weights2, roiSize, weights2Border); |
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generateOclMat(gdst, gdst_roi, dst, roiSize, dstBorder); |
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} |
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void Near(double eps = 0.0) |
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{ |
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Mat whole, roi; |
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gdst.download(whole); |
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gdst_roi.download(roi); |
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EXPECT_MAT_NEAR(dst, whole, eps); |
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EXPECT_MAT_NEAR(dst_roi, roi, eps); |
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} |
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}; |
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typedef void (*blendLinearFunc)(const cv::Mat &img1, const cv::Mat &img2, const cv::Mat &weights1, const cv::Mat &weights2, cv::Mat &result_gold); |
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OCL_TEST_P(Blend, 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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cv::ocl::blendLinear(gsrc1_roi, gsrc2_roi, gweights1_roi, gweights2_roi, gdst_roi); |
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static blendLinearFunc funcs[] = { |
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blendLinearGold<uchar>, |
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blendLinearGold<schar>, |
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blendLinearGold<ushort>, |
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blendLinearGold<short>, |
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blendLinearGold<int>, |
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blendLinearGold<float>, |
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}; |
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blendLinearFunc func = funcs[depth]; |
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func(src1_roi, src2_roi, weights1_roi, weights2_roi, dst_roi); |
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Near(depth <= CV_32S ? 1.0 : 0.2); |
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} |
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} |
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INSTANTIATE_TEST_CASE_P(OCL_ImgProc, Blend, |
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Combine(testing::Values(CV_8U, CV_8S, CV_16U, CV_16S, CV_32S, CV_32F), |
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testing::Range(1, 5), Bool()));
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