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160 lines
5.4 KiB
C++
160 lines
5.4 KiB
C++
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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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* (3 - clause BSD License)
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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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* *Redistributions 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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* * Redistributions 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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* * Neither the names of the copyright holders nor the names of the contributors
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* may be used to endorse or promote products derived from this software
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* 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 copyright holders 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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#include "perf_precomp.hpp"
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namespace cvtest
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{
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using std::tr1::tuple;
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using std::tr1::get;
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using namespace perf;
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using namespace testing;
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using namespace cv;
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void MakeArtificialExample(RNG rng, Mat& dst_left_view, Mat& dst_view);
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CV_ENUM(SGBMModes, StereoSGBM::MODE_SGBM, StereoSGBM::MODE_SGBM_3WAY);
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typedef tuple<Size, int, SGBMModes> SGBMParams;
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typedef TestBaseWithParam<SGBMParams> TestStereoCorresp;
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PERF_TEST_P( TestStereoCorresp, SGBM, Combine(Values(Size(1280,720),Size(640,480)), Values(256,128), SGBMModes::all()) )
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{
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RNG rng(0);
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SGBMParams params = GetParam();
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Size sz = get<0>(params);
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int num_disparities = get<1>(params);
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int mode = get<2>(params);
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Mat src_left(sz, CV_8UC3);
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Mat src_right(sz, CV_8UC3);
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Mat dst(sz, CV_16S);
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MakeArtificialExample(rng,src_left,src_right);
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cv::setNumThreads(cv::getNumberOfCPUs());
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int wsize = 3;
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int P1 = 8*src_left.channels()*wsize*wsize;
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TEST_CYCLE()
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{
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Ptr<StereoSGBM> sgbm = StereoSGBM::create(0,num_disparities,wsize,P1,4*P1,1,63,25,0,0,mode);
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sgbm->compute(src_left,src_right,dst);
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}
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SANITY_CHECK(dst, .01, ERROR_RELATIVE);
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}
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void MakeArtificialExample(RNG rng, Mat& dst_left_view, Mat& dst_right_view)
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{
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int w = dst_left_view.cols;
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int h = dst_left_view.rows;
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//params:
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unsigned char bg_level = (unsigned char)rng.uniform(0.0,255.0);
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unsigned char fg_level = (unsigned char)rng.uniform(0.0,255.0);
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int rect_width = (int)rng.uniform(w/16,w/2);
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int rect_height = (int)rng.uniform(h/16,h/2);
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int rect_disparity = (int)(0.15*w);
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double sigma = 3.0;
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int rect_x_offset = (w-rect_width) /2;
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int rect_y_offset = (h-rect_height)/2;
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if(dst_left_view.channels()==3)
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{
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dst_left_view = Scalar(Vec3b(bg_level,bg_level,bg_level));
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dst_right_view = Scalar(Vec3b(bg_level,bg_level,bg_level));
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}
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else
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{
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dst_left_view = Scalar(bg_level);
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dst_right_view = Scalar(bg_level);
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}
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Mat dst_left_view_rect = Mat(dst_left_view, Rect(rect_x_offset,rect_y_offset,rect_width,rect_height));
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if(dst_left_view.channels()==3)
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dst_left_view_rect = Scalar(Vec3b(fg_level,fg_level,fg_level));
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else
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dst_left_view_rect = Scalar(fg_level);
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rect_x_offset-=rect_disparity;
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Mat dst_right_view_rect = Mat(dst_right_view, Rect(rect_x_offset,rect_y_offset,rect_width,rect_height));
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if(dst_right_view.channels()==3)
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dst_right_view_rect = Scalar(Vec3b(fg_level,fg_level,fg_level));
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else
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dst_right_view_rect = Scalar(fg_level);
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//add some gaussian noise:
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unsigned char *l, *r;
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for(int i=0;i<h;i++)
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{
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l = dst_left_view.ptr(i);
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r = dst_right_view.ptr(i);
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if(dst_left_view.channels()==3)
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{
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for(int j=0;j<w;j++)
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{
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l[0] = saturate_cast<unsigned char>(l[0] + rng.gaussian(sigma));
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l[1] = saturate_cast<unsigned char>(l[1] + rng.gaussian(sigma));
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l[2] = saturate_cast<unsigned char>(l[2] + rng.gaussian(sigma));
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l+=3;
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r[0] = saturate_cast<unsigned char>(r[0] + rng.gaussian(sigma));
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r[1] = saturate_cast<unsigned char>(r[1] + rng.gaussian(sigma));
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r[2] = saturate_cast<unsigned char>(r[2] + rng.gaussian(sigma));
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r+=3;
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}
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}
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else
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{
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for(int j=0;j<w;j++)
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{
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l[0] = saturate_cast<unsigned char>(l[0] + rng.gaussian(sigma));
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l++;
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r[0] = saturate_cast<unsigned char>(r[0] + rng.gaussian(sigma));
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r++;
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}
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}
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}
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}
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}
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