183 lines
6.1 KiB
C++
183 lines
6.1 KiB
C++
/*
|
|
* 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
|
|
* (3 - clause BSD License)
|
|
*
|
|
* Redistribution and use in source and binary forms, with or without modification,
|
|
* are permitted provided that the following conditions are met :
|
|
*
|
|
* * Redistributions of source code must retain the above copyright notice,
|
|
* this list of conditions and the following disclaimer.
|
|
*
|
|
* * Redistributions in binary form must reproduce the above copyright notice,
|
|
* this list of conditions and the following disclaimer in the documentation
|
|
* and / or other materials provided with the distribution.
|
|
*
|
|
* * Neither the names of the copyright holders nor the names of the contributors
|
|
* may 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 copyright holders 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.
|
|
*/
|
|
|
|
#include "perf_precomp.hpp"
|
|
|
|
namespace opencv_test
|
|
{
|
|
using namespace perf;
|
|
using namespace testing;
|
|
|
|
static void MakeArtificialExample(Mat& dst_left_view, Mat& dst_view);
|
|
|
|
CV_ENUM(SGBMModes, StereoSGBM::MODE_SGBM, StereoSGBM::MODE_SGBM_3WAY, StereoSGBM::MODE_HH4);
|
|
typedef tuple<Size, int, SGBMModes> SGBMParams;
|
|
typedef TestBaseWithParam<SGBMParams> TestStereoCorrespSGBM;
|
|
|
|
#ifndef _DEBUG
|
|
PERF_TEST_P( TestStereoCorrespSGBM, SGBM, Combine(Values(Size(1280,720),Size(640,480)), Values(256,128), SGBMModes::all()) )
|
|
#else
|
|
PERF_TEST_P( TestStereoCorrespSGBM, DISABLED_TooLongInDebug_SGBM, Combine(Values(Size(1280,720),Size(640,480)), Values(256,128), SGBMModes::all()) )
|
|
#endif
|
|
{
|
|
SGBMParams params = GetParam();
|
|
|
|
Size sz = get<0>(params);
|
|
int num_disparities = get<1>(params);
|
|
int mode = get<2>(params);
|
|
|
|
Mat src_left(sz, CV_8UC3);
|
|
Mat src_right(sz, CV_8UC3);
|
|
Mat dst(sz, CV_16S);
|
|
|
|
MakeArtificialExample(src_left,src_right);
|
|
|
|
int wsize = 3;
|
|
int P1 = 8*src_left.channels()*wsize*wsize;
|
|
TEST_CYCLE()
|
|
{
|
|
Ptr<StereoSGBM> sgbm = StereoSGBM::create(0,num_disparities,wsize,P1,4*P1,1,63,25,0,0,mode);
|
|
sgbm->compute(src_left,src_right,dst);
|
|
}
|
|
|
|
SANITY_CHECK(dst, .01, ERROR_RELATIVE);
|
|
}
|
|
|
|
typedef tuple<Size, int> BMParams;
|
|
typedef TestBaseWithParam<BMParams> TestStereoCorrespBM;
|
|
|
|
PERF_TEST_P(TestStereoCorrespBM, BM, Combine(Values(Size(1280, 720), Size(640, 480)), Values(256, 128)))
|
|
{
|
|
BMParams params = GetParam();
|
|
Size sz = get<0>(params);
|
|
int num_disparities = get<1>(params);
|
|
|
|
Mat src_left(sz, CV_8UC1);
|
|
Mat src_right(sz, CV_8UC1);
|
|
Mat dst(sz, CV_16S);
|
|
|
|
MakeArtificialExample(src_left, src_right);
|
|
|
|
int wsize = 21;
|
|
TEST_CYCLE()
|
|
{
|
|
Ptr<StereoBM> bm = StereoBM::create(num_disparities, wsize);
|
|
bm->compute(src_left, src_right, dst);
|
|
}
|
|
|
|
SANITY_CHECK(dst, .01, ERROR_RELATIVE);
|
|
}
|
|
|
|
void MakeArtificialExample(Mat& dst_left_view, Mat& dst_right_view)
|
|
{
|
|
RNG rng(0);
|
|
int w = dst_left_view.cols;
|
|
int h = dst_left_view.rows;
|
|
|
|
//params:
|
|
unsigned char bg_level = (unsigned char)rng.uniform(0.0,255.0);
|
|
unsigned char fg_level = (unsigned char)rng.uniform(0.0,255.0);
|
|
int rect_width = (int)rng.uniform(w/16,w/2);
|
|
int rect_height = (int)rng.uniform(h/16,h/2);
|
|
int rect_disparity = (int)(0.15*w);
|
|
double sigma = 3.0;
|
|
|
|
int rect_x_offset = (w-rect_width) /2;
|
|
int rect_y_offset = (h-rect_height)/2;
|
|
|
|
if(dst_left_view.channels()==3)
|
|
{
|
|
dst_left_view = Scalar(Vec3b(bg_level,bg_level,bg_level));
|
|
dst_right_view = Scalar(Vec3b(bg_level,bg_level,bg_level));
|
|
}
|
|
else
|
|
{
|
|
dst_left_view = Scalar(bg_level);
|
|
dst_right_view = Scalar(bg_level);
|
|
}
|
|
|
|
Mat dst_left_view_rect = Mat(dst_left_view, Rect(rect_x_offset,rect_y_offset,rect_width,rect_height));
|
|
if(dst_left_view.channels()==3)
|
|
dst_left_view_rect = Scalar(Vec3b(fg_level,fg_level,fg_level));
|
|
else
|
|
dst_left_view_rect = Scalar(fg_level);
|
|
|
|
rect_x_offset-=rect_disparity;
|
|
|
|
Mat dst_right_view_rect = Mat(dst_right_view, Rect(rect_x_offset,rect_y_offset,rect_width,rect_height));
|
|
if(dst_right_view.channels()==3)
|
|
dst_right_view_rect = Scalar(Vec3b(fg_level,fg_level,fg_level));
|
|
else
|
|
dst_right_view_rect = Scalar(fg_level);
|
|
|
|
//add some gaussian noise:
|
|
unsigned char *l, *r;
|
|
for(int i=0;i<h;i++)
|
|
{
|
|
l = dst_left_view.ptr(i);
|
|
r = dst_right_view.ptr(i);
|
|
|
|
if(dst_left_view.channels()==3)
|
|
{
|
|
for(int j=0;j<w;j++)
|
|
{
|
|
l[0] = saturate_cast<unsigned char>(l[0] + rng.gaussian(sigma));
|
|
l[1] = saturate_cast<unsigned char>(l[1] + rng.gaussian(sigma));
|
|
l[2] = saturate_cast<unsigned char>(l[2] + rng.gaussian(sigma));
|
|
l+=3;
|
|
|
|
r[0] = saturate_cast<unsigned char>(r[0] + rng.gaussian(sigma));
|
|
r[1] = saturate_cast<unsigned char>(r[1] + rng.gaussian(sigma));
|
|
r[2] = saturate_cast<unsigned char>(r[2] + rng.gaussian(sigma));
|
|
r+=3;
|
|
}
|
|
}
|
|
else
|
|
{
|
|
for(int j=0;j<w;j++)
|
|
{
|
|
l[0] = saturate_cast<unsigned char>(l[0] + rng.gaussian(sigma));
|
|
l++;
|
|
|
|
r[0] = saturate_cast<unsigned char>(r[0] + rng.gaussian(sigma));
|
|
r++;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
}
|