Open Source Computer Vision Library https://opencv.org/
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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2010-2012, Multicoreware, Inc., all rights reserved.
// Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// @Authors
// Fangfang Bai, fangfang@multicorewareinc.com
// Jin Ma, jin@multicorewareinc.com
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
11 years ago
// and/or other materials provided with the distribution.
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// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
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// This software is provided by the copyright holders and contributors as is and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
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//M*/
#include "perf_precomp.hpp"
using namespace perf;
using namespace cv;
using std::tr1::get;
///////////// blend ////////////////////////
template <typename T>
static void blendLinearGold(const Mat &img1, const Mat &img2,
const Mat &weights1, const Mat &weights2,
Mat &result_gold)
{
CV_Assert(img1.size() == img2.size() && img1.type() == img2.type());
CV_Assert(weights1.size() == weights2.size() && weights1.size() == img1.size() &&
weights1.type() == CV_32FC1 && weights2.type() == CV_32FC1);
result_gold.create(img1.size(), img1.type());
int cn = img1.channels();
int step1 = img1.cols * img1.channels();
for (int y = 0; y < img1.rows; ++y)
{
const float * const weights1_row = weights1.ptr<float>(y);
const float * const weights2_row = weights2.ptr<float>(y);
const T * const img1_row = img1.ptr<T>(y);
const T * const img2_row = img2.ptr<T>(y);
T * const result_gold_row = result_gold.ptr<T>(y);
for (int x = 0; x < step1; ++x)
{
int x1 = x / cn;
float w1 = weights1_row[x1], w2 = weights2_row[x1];
result_gold_row[x] = saturate_cast<T>(((float)img1_row[x] * w1
+ (float)img2_row[x] * w2) / (w1 + w2 + 1e-5f));
}
}
}
typedef void (*blendFunction)(const Mat &img1, const Mat &img2,
const Mat &weights1, const Mat &weights2,
Mat &result_gold);
typedef Size_MatType BlendLinearFixture;
OCL_PERF_TEST_P(BlendLinearFixture, BlendLinear,
::testing::Combine(OCL_TEST_SIZES, OCL_PERF_ENUM(CV_32FC1, CV_32FC4)))
{
Size_MatType_t params = GetParam();
const Size srcSize = get<0>(params);
const int srcType = get<1>(params);
const double eps = CV_MAT_DEPTH(srcType) <= CV_32S ? 1.0 : 0.2;
Mat src1(srcSize, srcType), src2(srcSize, srcType), dst(srcSize, srcType);
Mat weights1(srcSize, CV_32FC1), weights2(srcSize, CV_32FC1);
declare.in(src1, src2, WARMUP_RNG).out(dst);
randu(weights1, 0.0f, 1.0f);
randu(weights2, 0.0f, 1.0f);
if (RUN_OCL_IMPL)
{
ocl::oclMat oclSrc1(src1), oclSrc2(src2), oclDst;
ocl::oclMat oclWeights1(weights1), oclWeights2(weights2);
OCL_TEST_CYCLE() ocl::blendLinear(oclSrc1, oclSrc2, oclWeights1, oclWeights2, oclDst);
oclDst.download(dst);
SANITY_CHECK(dst, eps);
}
else if (RUN_PLAIN_IMPL)
{
blendFunction funcs[] = { (blendFunction)blendLinearGold<uchar>, (blendFunction)blendLinearGold<float> };
int funcIdx = CV_MAT_DEPTH(srcType) == CV_8UC1 ? 0 : 1;
TEST_CYCLE() (funcs[funcIdx])(src1, src2, weights1, weights2, dst);
SANITY_CHECK(dst, eps);
}
else
OCL_PERF_ELSE
}