Open Source Computer Vision Library https://opencv.org/
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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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// If you do not agree to this license, do not download, install,
// copy or use the software.
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//
// 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:
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// this list of conditions and the following disclaimer in the documentation
11 years ago
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//M*/
#include "perf_precomp.hpp"
using namespace perf;
///////////// blend ////////////////////////
template <typename T>
static void blendLinearGold(const cv::Mat &img1, const cv::Mat &img2,
const cv::Mat &weights1, const cv::Mat &weights2,
cv::Mat &result_gold)
{
result_gold.create(img1.size(), img1.type());
int cn = img1.channels();
for (int y = 0; y < img1.rows; ++y)
{
const float *weights1_row = weights1.ptr<float>(y);
const float *weights2_row = weights2.ptr<float>(y);
const T *img1_row = img1.ptr<T>(y);
const T *img2_row = img2.ptr<T>(y);
T *result_gold_row = result_gold.ptr<T>(y);
for (int x = 0; x < img1.cols * cn; ++x)
{
int x1 = x * cn;
float w1 = weights1_row[x];
float w2 = weights2_row[x];
result_gold_row[x] = static_cast<T>((img1_row[x1] * w1
+ img2_row[x1] * w2) / (w1 + w2 + 1e-5f));
}
}
}
typedef TestBaseWithParam<Size> blendLinearFixture;
PERF_TEST_P(blendLinearFixture, blendLinear, OCL_TYPICAL_MAT_SIZES)
{
const Size srcSize = GetParam();
const int type = CV_8UC1;
Mat src1(srcSize, type), src2(srcSize, CV_8UC1), dst;
Mat weights1(srcSize, CV_32FC1), weights2(srcSize, CV_32FC1);
declare.in(src1, src2, WARMUP_RNG);
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() cv::ocl::blendLinear(oclSrc1, oclSrc2, oclWeights1, oclWeights2, oclDst);
oclDst.download(dst);
SANITY_CHECK(dst);
}
else if (RUN_PLAIN_IMPL)
{
TEST_CYCLE() blendLinearGold<uchar>(src1, src2, weights1, weights2, dst);
SANITY_CHECK(dst);
}
else
OCL_PERF_ELSE
}