131 lines
5.0 KiB
C++
131 lines
5.0 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, 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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// Fangfang Bai, fangfang@multicorewareinc.com
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// Jin Ma, jin@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 "perf_precomp.hpp"
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using namespace perf;
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using namespace cv;
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using std::tr1::get;
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///////////// blend ////////////////////////
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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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typedef void (*blendFunction)(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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typedef Size_MatType BlendLinearFixture;
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OCL_PERF_TEST_P(BlendLinearFixture, BlendLinear,
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::testing::Combine(OCL_TEST_SIZES, OCL_PERF_ENUM(CV_32FC1, CV_32FC4)))
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{
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Size_MatType_t params = GetParam();
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const Size srcSize = get<0>(params);
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const int srcType = get<1>(params);
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const double eps = CV_MAT_DEPTH(srcType) <= CV_32S ? 1.0 : 0.2;
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Mat src1(srcSize, srcType), src2(srcSize, srcType), dst(srcSize, srcType);
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Mat weights1(srcSize, CV_32FC1), weights2(srcSize, CV_32FC1);
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declare.in(src1, src2, WARMUP_RNG).out(dst);
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randu(weights1, 0.0f, 1.0f);
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randu(weights2, 0.0f, 1.0f);
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if (RUN_OCL_IMPL)
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{
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ocl::oclMat oclSrc1(src1), oclSrc2(src2), oclDst;
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ocl::oclMat oclWeights1(weights1), oclWeights2(weights2);
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OCL_TEST_CYCLE() ocl::blendLinear(oclSrc1, oclSrc2, oclWeights1, oclWeights2, oclDst);
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oclDst.download(dst);
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SANITY_CHECK(dst, eps);
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}
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else if (RUN_PLAIN_IMPL)
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{
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blendFunction funcs[] = { (blendFunction)blendLinearGold<uchar>, (blendFunction)blendLinearGold<float> };
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int funcIdx = CV_MAT_DEPTH(srcType) == CV_8UC1 ? 0 : 1;
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TEST_CYCLE() (funcs[funcIdx])(src1, src2, weights1, weights2, dst);
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SANITY_CHECK(dst, eps);
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}
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else
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OCL_PERF_ELSE
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}
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