opencv/modules/ocl/perf/perf_blend.cpp
2013-05-28 17:53:06 +08:00

122 lines
4.7 KiB
C++

/*M///////////////////////////////////////////////////////////////////////////////////////
//
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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.
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//
// @Authors
// Fangfang Bai, fangfang@multicorewareinc.com
// Jin Ma, jin@multicorewareinc.com
//
// Redistribution and use in source and binary forms, with or without modification,
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#include "precomp.hpp"
///////////// blend ////////////////////////
template <typename T>
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)
{
float w1 = weights1_row[x / cn];
float w2 = weights2_row[x / cn];
result_gold_row[x] = static_cast<T>((img1_row[x] * w1 + img2_row[x] * w2) / (w1 + w2 + 1e-5f));
}
}
}
PERFTEST(blend)
{
Mat src1, src2, weights1, weights2, dst, ocl_dst;
ocl::oclMat d_src1, d_src2, d_weights1, d_weights2, d_dst;
int all_type[] = {CV_8UC1, CV_8UC4};
std::string type_name[] = {"CV_8UC1", "CV_8UC4"};
for (int size = Min_Size; size <= Max_Size; size *= Multiple)
{
for (size_t j = 0; j < sizeof(all_type) / sizeof(int); j++)
{
SUBTEST << size << 'x' << size << "; " << type_name[j] << " and CV_32FC1";
gen(src1, size, size, all_type[j], 0, 256);
gen(src2, size, size, all_type[j], 0, 256);
gen(weights1, size, size, CV_32FC1, 0, 1);
gen(weights2, size, size, CV_32FC1, 0, 1);
blendLinearGold<uchar>(src1, src2, weights1, weights2, dst);
CPU_ON;
blendLinearGold<uchar>(src1, src2, weights1, weights2, dst);
CPU_OFF;
d_src1.upload(src1);
d_src2.upload(src2);
d_weights1.upload(weights1);
d_weights2.upload(weights2);
WARMUP_ON;
ocl::blendLinear(d_src1, d_src2, d_weights1, d_weights2, d_dst);
WARMUP_OFF;
GPU_ON;
ocl::blendLinear(d_src1, d_src2, d_weights1, d_weights2, d_dst);
GPU_OFF;
GPU_FULL_ON;
d_src1.upload(src1);
d_src2.upload(src2);
d_weights1.upload(weights1);
d_weights2.upload(weights2);
ocl::blendLinear(d_src1, d_src2, d_weights1, d_weights2, d_dst);
d_dst.download(ocl_dst);
GPU_FULL_OFF;
TestSystem::instance().ExpectedMatNear(dst, ocl_dst, 1.f);
}
}
}