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/*
* 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++;
}
}
}
}
}
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