mirror of https://github.com/opencv/opencv.git
Open Source Computer Vision Library
https://opencv.org/
You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
122 lines
4.7 KiB
122 lines
4.7 KiB
/*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 |
|
// and/or other oclMaterials provided with the distribution. |
|
// |
|
// * The name of the copyright holders may not be used to endorse or promote products |
|
// derived from this software without specific prior written permission. |
|
// |
|
// 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 |
|
// (including, but not limited to, procurement of substitute goods or services; |
|
// loss of use, data, or profits; or business interruption) however caused |
|
// and on any theory of liability, whether in contract, strict liability, |
|
// or tort (including negligence or otherwise) arising in any way out of |
|
// the use of this software, even if advised of the possibility of such damage. |
|
// |
|
//M*/ |
|
|
|
#include "perf_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); |
|
} |
|
} |
|
}
|
|
|