Merge pull request #4179 from sbokov:improvingStereoSGBM

This commit is contained in:
Maksim Shabunin 2015-07-24 21:12:56 +00:00
commit ecd3661119
5 changed files with 857 additions and 50 deletions

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@ -1555,7 +1555,8 @@ public:
enum
{
MODE_SGBM = 0,
MODE_HH = 1
MODE_HH = 1,
MODE_SGBM_3WAY = 2
};
CV_WRAP virtual int getPreFilterCap() const = 0;

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@ -0,0 +1,159 @@
/*
* 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 cvtest
{
using std::tr1::tuple;
using std::tr1::get;
using namespace perf;
using namespace testing;
using namespace cv;
void MakeArtificialExample(RNG rng, Mat& dst_left_view, Mat& dst_view);
CV_ENUM(SGBMModes, StereoSGBM::MODE_SGBM, StereoSGBM::MODE_SGBM_3WAY);
typedef tuple<Size, int, SGBMModes> SGBMParams;
typedef TestBaseWithParam<SGBMParams> TestStereoCorresp;
PERF_TEST_P( TestStereoCorresp, SGBM, Combine(Values(Size(1280,720),Size(640,480)), Values(256,128), SGBMModes::all()) )
{
RNG rng(0);
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(rng,src_left,src_right);
cv::setNumThreads(cv::getNumberOfCPUs());
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);
}
void MakeArtificialExample(RNG rng, Mat& dst_left_view, Mat& dst_right_view)
{
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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@ -52,6 +52,7 @@
#include "precomp.hpp"
#include <limits.h>
#include "opencv2/hal/intrin.hpp"
namespace cv
{
@ -110,7 +111,7 @@ struct StereoSGBMParams
};
/*
For each pixel row1[x], max(-maxD, 0) <= minX <= x < maxX <= width - max(0, -minD),
For each pixel row1[x], max(maxD, 0) <= minX <= x < maxX <= width - max(0, -minD),
and for each disparity minD<=d<maxD the function
computes the cost (cost[(x-minX)*(maxD - minD) + (d - minD)]), depending on the difference between
row1[x] and row2[x-d]. The subpixel algorithm from
@ -125,7 +126,7 @@ static void calcPixelCostBT( const Mat& img1, const Mat& img2, int y,
int tabOfs, int )
{
int x, c, width = img1.cols, cn = img1.channels();
int minX1 = std::max(-maxD, 0), maxX1 = width + std::min(minD, 0);
int minX1 = std::max(maxD, 0), maxX1 = width + std::min(minD, 0);
int minX2 = std::max(minX1 - maxD, 0), maxX2 = std::min(maxX1 - minD, width);
int D = maxD - minD, width1 = maxX1 - minX1, width2 = maxX2 - minX2;
const PixType *row1 = img1.ptr<PixType>(y), *row2 = img2.ptr<PixType>(y);
@ -180,10 +181,6 @@ static void calcPixelCostBT( const Mat& img1, const Mat& img2, int y,
buffer -= minX2;
cost -= minX1*D + minD; // simplify the cost indices inside the loop
#if CV_SSE2
volatile bool useSIMD = checkHardwareSupport(CV_CPU_SSE2);
#endif
#if 1
for( c = 0; c < cn*2; c++, prow1 += width, prow2 += width )
{
@ -211,43 +208,39 @@ static void calcPixelCostBT( const Mat& img1, const Mat& img2, int y,
int u0 = std::min(ul, ur); u0 = std::min(u0, u);
int u1 = std::max(ul, ur); u1 = std::max(u1, u);
#if CV_SSE2
if( useSIMD )
#if CV_SIMD128
v_uint8x16 _u = v_setall_u8((uchar)u), _u0 = v_setall_u8((uchar)u0);
v_uint8x16 _u1 = v_setall_u8((uchar)u1);
for( int d = minD; d < maxD; d += 16 )
{
__m128i _u = _mm_set1_epi8((char)u), _u0 = _mm_set1_epi8((char)u0);
__m128i _u1 = _mm_set1_epi8((char)u1), z = _mm_setzero_si128();
__m128i ds = _mm_cvtsi32_si128(diff_scale);
v_uint8x16 _v = v_load(prow2 + width-x-1 + d);
v_uint8x16 _v0 = v_load(buffer + width-x-1 + d);
v_uint8x16 _v1 = v_load(buffer + width-x-1 + d + width2);
v_uint8x16 c0 = v_max(_u - _v1, _v0 - _u);
v_uint8x16 c1 = v_max(_v - _u1, _u0 - _v);
v_uint8x16 diff = v_min(c0, c1);
for( int d = minD; d < maxD; d += 16 )
{
__m128i _v = _mm_loadu_si128((const __m128i*)(prow2 + width-x-1 + d));
__m128i _v0 = _mm_loadu_si128((const __m128i*)(buffer + width-x-1 + d));
__m128i _v1 = _mm_loadu_si128((const __m128i*)(buffer + width-x-1 + d + width2));
__m128i c0 = _mm_max_epu8(_mm_subs_epu8(_u, _v1), _mm_subs_epu8(_v0, _u));
__m128i c1 = _mm_max_epu8(_mm_subs_epu8(_v, _u1), _mm_subs_epu8(_u0, _v));
__m128i diff = _mm_min_epu8(c0, c1);
v_int16x8 _c0 = v_load_aligned(cost + x*D + d);
v_int16x8 _c1 = v_load_aligned(cost + x*D + d + 8);
c0 = _mm_load_si128((__m128i*)(cost + x*D + d));
c1 = _mm_load_si128((__m128i*)(cost + x*D + d + 8));
_mm_store_si128((__m128i*)(cost + x*D + d), _mm_adds_epi16(c0, _mm_srl_epi16(_mm_unpacklo_epi8(diff,z), ds)));
_mm_store_si128((__m128i*)(cost + x*D + d + 8), _mm_adds_epi16(c1, _mm_srl_epi16(_mm_unpackhi_epi8(diff,z), ds)));
}
v_uint16x8 diff1,diff2;
v_expand(diff,diff1,diff2);
v_store_aligned(cost + x*D + d, _c0 + v_reinterpret_as_s16(diff1 >> diff_scale));
v_store_aligned(cost + x*D + d + 8, _c1 + v_reinterpret_as_s16(diff2 >> diff_scale));
}
#else
for( int d = minD; d < maxD; d++ )
{
int v = prow2[width-x-1 + d];
int v0 = buffer[width-x-1 + d];
int v1 = buffer[width-x-1 + d + width2];
int c0 = std::max(0, u - v1); c0 = std::max(c0, v0 - u);
int c1 = std::max(0, v - u1); c1 = std::max(c1, u0 - v);
cost[x*D + d] = (CostType)(cost[x*D+d] + (std::min(c0, c1) >> diff_scale));
}
else
#endif
{
for( int d = minD; d < maxD; d++ )
{
int v = prow2[width-x-1 + d];
int v0 = buffer[width-x-1 + d];
int v1 = buffer[width-x-1 + d + width2];
int c0 = std::max(0, u - v1); c0 = std::max(c0, v0 - u);
int c1 = std::max(0, v - u1); c1 = std::max(c1, u0 - v);
cost[x*D + d] = (CostType)(cost[x*D+d] + (std::min(c0, c1) >> diff_scale));
}
}
}
}
#else
@ -340,7 +333,7 @@ static void computeDisparitySGBM( const Mat& img1, const Mat& img2,
int disp12MaxDiff = params.disp12MaxDiff > 0 ? params.disp12MaxDiff : 1;
int P1 = params.P1 > 0 ? params.P1 : 2, P2 = std::max(params.P2 > 0 ? params.P2 : 5, P1+1);
int k, width = disp1.cols, height = disp1.rows;
int minX1 = std::max(-maxD, 0), maxX1 = width + std::min(minD, 0);
int minX1 = std::max(maxD, 0), maxX1 = width + std::min(minD, 0);
int D = maxD - minD, width1 = maxX1 - minX1;
int INVALID_DISP = minD - 1, INVALID_DISP_SCALED = INVALID_DISP*DISP_SCALE;
int SW2 = SADWindowSize.width/2, SH2 = SADWindowSize.height/2;
@ -829,6 +822,645 @@ static void computeDisparitySGBM( const Mat& img1, const Mat& img2,
}
}
//////////////////////////////////////////////////////////////////////////////////////////////////////
void getBufferPointers(Mat& buffer, int width, int width1, int D, int num_ch, int SH2, int P2,
CostType*& curCostVolumeLine, CostType*& hsumBuf, CostType*& pixDiff,
PixType*& tmpBuf, CostType*& horPassCostVolume,
CostType*& vertPassCostVolume, CostType*& vertPassMin, CostType*& rightPassBuf,
CostType*& disp2CostBuf, short*& disp2Buf);
struct SGBM3WayMainLoop : public ParallelLoopBody
{
Mat* buffers;
const Mat *img1, *img2;
Mat* dst_disp;
int nstripes, stripe_sz;
int stripe_overlap;
int width,height;
int minD, maxD, D;
int minX1, maxX1, width1;
int SW2, SH2;
int P1, P2;
int uniquenessRatio, disp12MaxDiff;
int costBufSize, hsumBufNRows;
int TAB_OFS, ftzero;
PixType* clipTab;
SGBM3WayMainLoop(Mat *_buffers, const Mat& _img1, const Mat& _img2, Mat* _dst_disp, const StereoSGBMParams& params, PixType* _clipTab, int _nstripes, int _stripe_overlap);
void getRawMatchingCost(CostType* C, CostType* hsumBuf, CostType* pixDiff, PixType* tmpBuf, int y, int src_start_idx) const;
void operator () (const Range& range) const;
};
SGBM3WayMainLoop::SGBM3WayMainLoop(Mat *_buffers, const Mat& _img1, const Mat& _img2, Mat* _dst_disp, const StereoSGBMParams& params, PixType* _clipTab, int _nstripes, int _stripe_overlap):
buffers(_buffers), img1(&_img1), img2(&_img2), dst_disp(_dst_disp), clipTab(_clipTab)
{
nstripes = _nstripes;
stripe_overlap = _stripe_overlap;
stripe_sz = (int)ceil(img1->rows/(double)nstripes);
width = img1->cols; height = img1->rows;
minD = params.minDisparity; maxD = minD + params.numDisparities; D = maxD - minD;
minX1 = std::max(maxD, 0); maxX1 = width + std::min(minD, 0); width1 = maxX1 - minX1;
CV_Assert( D % 16 == 0 );
SW2 = SH2 = params.SADWindowSize > 0 ? params.SADWindowSize/2 : 1;
P1 = params.P1 > 0 ? params.P1 : 2; P2 = std::max(params.P2 > 0 ? params.P2 : 5, P1+1);
uniquenessRatio = params.uniquenessRatio >= 0 ? params.uniquenessRatio : 10;
disp12MaxDiff = params.disp12MaxDiff > 0 ? params.disp12MaxDiff : 1;
costBufSize = width1*D;
hsumBufNRows = SH2*2 + 2;
TAB_OFS = 256*4;
ftzero = std::max(params.preFilterCap, 15) | 1;
}
void getBufferPointers(Mat& buffer, int width, int width1, int D, int num_ch, int SH2, int P2,
CostType*& curCostVolumeLine, CostType*& hsumBuf, CostType*& pixDiff,
PixType*& tmpBuf, CostType*& horPassCostVolume,
CostType*& vertPassCostVolume, CostType*& vertPassMin, CostType*& rightPassBuf,
CostType*& disp2CostBuf, short*& disp2Buf)
{
// allocating all the required memory:
int costVolumeLineSize = width1*D;
int width1_ext = width1+2;
int costVolumeLineSize_ext = width1_ext*D;
int hsumBufNRows = SH2*2 + 2;
// main buffer to store matching costs for the current line:
int curCostVolumeLineSize = costVolumeLineSize*sizeof(CostType);
// auxiliary buffers for the raw matching cost computation:
int hsumBufSize = costVolumeLineSize*hsumBufNRows*sizeof(CostType);
int pixDiffSize = costVolumeLineSize*sizeof(CostType);
int tmpBufSize = width*16*num_ch*sizeof(PixType);
// auxiliary buffers for the matching cost aggregation:
int horPassCostVolumeSize = costVolumeLineSize_ext*sizeof(CostType); // buffer for the 2-pass horizontal cost aggregation
int vertPassCostVolumeSize = costVolumeLineSize_ext*sizeof(CostType); // buffer for the vertical cost aggregation
int vertPassMinSize = width1_ext*sizeof(CostType); // buffer for storing minimum costs from the previous line
int rightPassBufSize = D*sizeof(CostType); // additional small buffer for the right-to-left pass
// buffers for the pseudo-LRC check:
int disp2CostBufSize = width*sizeof(CostType);
int disp2BufSize = width*sizeof(short);
// sum up the sizes of all the buffers:
size_t totalBufSize = curCostVolumeLineSize +
hsumBufSize +
pixDiffSize +
tmpBufSize +
horPassCostVolumeSize +
vertPassCostVolumeSize +
vertPassMinSize +
rightPassBufSize +
disp2CostBufSize +
disp2BufSize +
16; //to compensate for the alignPtr shifts
if( buffer.empty() || !buffer.isContinuous() || buffer.cols*buffer.rows*buffer.elemSize() < totalBufSize )
buffer.create(1, (int)totalBufSize, CV_8U);
// set up all the pointers:
curCostVolumeLine = (CostType*)alignPtr(buffer.ptr(), 16);
hsumBuf = curCostVolumeLine + costVolumeLineSize;
pixDiff = hsumBuf + costVolumeLineSize*hsumBufNRows;
tmpBuf = (PixType*)(pixDiff + costVolumeLineSize);
horPassCostVolume = (CostType*)(tmpBuf + width*16*num_ch);
vertPassCostVolume = horPassCostVolume + costVolumeLineSize_ext;
rightPassBuf = vertPassCostVolume + costVolumeLineSize_ext;
vertPassMin = rightPassBuf + D;
disp2CostBuf = vertPassMin + width1_ext;
disp2Buf = disp2CostBuf + width;
// initialize memory:
memset(buffer.ptr(),0,totalBufSize);
for(int i=0;i<costVolumeLineSize;i++)
curCostVolumeLine[i] = (CostType)P2; //such initialization simplifies the cost aggregation loops a bit
}
// performing block matching and building raw cost-volume for the current row
void SGBM3WayMainLoop::getRawMatchingCost(CostType* C, // target cost-volume row
CostType* hsumBuf, CostType* pixDiff, PixType* tmpBuf, //buffers
int y, int src_start_idx) const
{
int x, d;
int dy1 = (y == src_start_idx) ? src_start_idx : y + SH2, dy2 = (y == src_start_idx) ? src_start_idx+SH2 : dy1;
for(int k = dy1; k <= dy2; k++ )
{
CostType* hsumAdd = hsumBuf + (std::min(k, height-1) % hsumBufNRows)*costBufSize;
if( k < height )
{
calcPixelCostBT( *img1, *img2, k, minD, maxD, pixDiff, tmpBuf, clipTab, TAB_OFS, ftzero );
memset(hsumAdd, 0, D*sizeof(CostType));
for(x = 0; x <= SW2*D; x += D )
{
int scale = x == 0 ? SW2 + 1 : 1;
for( d = 0; d < D; d++ )
hsumAdd[d] = (CostType)(hsumAdd[d] + pixDiff[x + d]*scale);
}
if( y > src_start_idx )
{
const CostType* hsumSub = hsumBuf + (std::max(y - SH2 - 1, src_start_idx) % hsumBufNRows)*costBufSize;
for( x = D; x < width1*D; x += D )
{
const CostType* pixAdd = pixDiff + std::min(x + SW2*D, (width1-1)*D);
const CostType* pixSub = pixDiff + std::max(x - (SW2+1)*D, 0);
#if CV_SIMD128
v_int16x8 hv_reg;
for( d = 0; d < D; d+=8 )
{
hv_reg = v_load_aligned(hsumAdd+x-D+d) + (v_load_aligned(pixAdd+d) - v_load_aligned(pixSub+d));
v_store_aligned(hsumAdd+x+d,hv_reg);
v_store_aligned(C+x+d,v_load_aligned(C+x+d)+(hv_reg-v_load_aligned(hsumSub+x+d)));
}
#else
for( d = 0; d < D; d++ )
{
int hv = hsumAdd[x + d] = (CostType)(hsumAdd[x - D + d] + pixAdd[d] - pixSub[d]);
C[x + d] = (CostType)(C[x + d] + hv - hsumSub[x + d]);
}
#endif
}
}
else
{
for( x = D; x < width1*D; x += D )
{
const CostType* pixAdd = pixDiff + std::min(x + SW2*D, (width1-1)*D);
const CostType* pixSub = pixDiff + std::max(x - (SW2+1)*D, 0);
for( d = 0; d < D; d++ )
hsumAdd[x + d] = (CostType)(hsumAdd[x - D + d] + pixAdd[d] - pixSub[d]);
}
}
}
if( y == src_start_idx )
{
int scale = k == src_start_idx ? SH2 + 1 : 1;
for( x = 0; x < width1*D; x++ )
C[x] = (CostType)(C[x] + hsumAdd[x]*scale);
}
}
}
#if CV_SIMD128 && CV_SSE2
// define some additional reduce operations:
inline short min(const v_int16x8& a)
{
short CV_DECL_ALIGNED(16) buf[8];
v_store_aligned(buf, a);
short s0 = std::min(buf[0], buf[1]);
short s1 = std::min(buf[2], buf[3]);
short s2 = std::min(buf[4], buf[5]);
short s3 = std::min(buf[6], buf[7]);
return std::min(std::min(s0, s1),std::min(s2, s3));
}
inline short min_pos(const v_int16x8& val,const v_int16x8& pos)
{
short CV_DECL_ALIGNED(16) val_buf[8];
v_store_aligned(val_buf, val);
short CV_DECL_ALIGNED(16) pos_buf[8];
v_store_aligned(pos_buf, pos);
short res_pos = 0;
short min_val = SHRT_MAX;
if(val_buf[0]<min_val) {min_val=val_buf[0]; res_pos=pos_buf[0];}
if(val_buf[1]<min_val) {min_val=val_buf[1]; res_pos=pos_buf[1];}
if(val_buf[2]<min_val) {min_val=val_buf[2]; res_pos=pos_buf[2];}
if(val_buf[3]<min_val) {min_val=val_buf[3]; res_pos=pos_buf[3];}
if(val_buf[4]<min_val) {min_val=val_buf[4]; res_pos=pos_buf[4];}
if(val_buf[5]<min_val) {min_val=val_buf[5]; res_pos=pos_buf[5];}
if(val_buf[6]<min_val) {min_val=val_buf[6]; res_pos=pos_buf[6];}
if(val_buf[7]<min_val) {min_val=val_buf[7]; res_pos=pos_buf[7];}
return res_pos;
}
#endif
// performing SGM cost accumulation from left to right (result is stored in leftBuf) and
// in-place cost accumulation from top to bottom (result is stored in topBuf)
inline void accumulateCostsLeftTop(CostType* leftBuf, CostType* leftBuf_prev, CostType* topBuf, CostType* costs,
CostType& leftMinCost, CostType& topMinCost, int D, int P1, int P2)
{
#if CV_SIMD128 && CV_SSE2
v_int16x8 P1_reg = v_setall_s16(cv::saturate_cast<CostType>(P1));
v_int16x8 leftMinCostP2_reg = v_setall_s16(cv::saturate_cast<CostType>(leftMinCost+P2));
v_int16x8 leftMinCost_new_reg = v_setall_s16(SHRT_MAX);
v_int16x8 src0_leftBuf = v_setall_s16(SHRT_MAX);
v_int16x8 src1_leftBuf = v_load_aligned(leftBuf_prev);
v_int16x8 topMinCostP2_reg = v_setall_s16(cv::saturate_cast<CostType>(topMinCost+P2));
v_int16x8 topMinCost_new_reg = v_setall_s16(SHRT_MAX);
v_int16x8 src0_topBuf = v_setall_s16(SHRT_MAX);
v_int16x8 src1_topBuf = v_load_aligned(topBuf);
v_int16x8 src2;
v_int16x8 src_shifted_left,src_shifted_right;
v_int16x8 res;
for(int i=0;i<D-8;i+=8)
{
//process leftBuf:
//lookahead load:
src2 = v_load_aligned(leftBuf_prev+i+8);
//get shifted versions of the current block:
src_shifted_left = v_int16x8(_mm_slli_si128(src1_leftBuf.val, 2));
src_shifted_right = v_int16x8(_mm_srli_si128(src1_leftBuf.val, 2));
// replace shifted-in zeros with proper values and add P1:
src_shifted_left = (src_shifted_left | v_int16x8(_mm_srli_si128(src0_leftBuf.val, 14)))+P1_reg;
src_shifted_right = (src_shifted_right | v_int16x8(_mm_slli_si128(src2.val, 14)))+P1_reg;
// process and save current block:
res = v_load_aligned(costs+i) + (v_min(v_min(src_shifted_left,src_shifted_right),v_min(src1_leftBuf,leftMinCostP2_reg))-leftMinCostP2_reg);
leftMinCost_new_reg = v_min(leftMinCost_new_reg,res);
v_store_aligned(leftBuf+i, res);
//update src buffers:
src0_leftBuf = src1_leftBuf;
src1_leftBuf = src2;
//process topBuf:
//lookahead load:
src2 = v_load_aligned(topBuf+i+8);
//get shifted versions of the current block:
src_shifted_left = v_int16x8(_mm_slli_si128(src1_topBuf.val, 2));
src_shifted_right = v_int16x8(_mm_srli_si128(src1_topBuf.val, 2));
// replace shifted-in zeros with proper values and add P1:
src_shifted_left = (src_shifted_left | v_int16x8(_mm_srli_si128(src0_topBuf.val, 14)))+P1_reg;
src_shifted_right = (src_shifted_right | v_int16x8(_mm_slli_si128(src2.val , 14)))+P1_reg;
// process and save current block:
res = v_load_aligned(costs+i) + (v_min(v_min(src_shifted_left,src_shifted_right),v_min(src1_topBuf,topMinCostP2_reg))-topMinCostP2_reg);
topMinCost_new_reg = v_min(topMinCost_new_reg,res);
v_store_aligned(topBuf+i, res);
//update src buffers:
src0_topBuf = src1_topBuf;
src1_topBuf = src2;
}
// a bit different processing for the last cycle of the loop:
//process leftBuf:
src_shifted_left = v_int16x8(_mm_slli_si128(src1_leftBuf.val, 2));
src_shifted_right = v_int16x8(_mm_srli_si128(src1_leftBuf.val, 2));
src2 = v_setall_s16(SHRT_MAX);
src_shifted_left = (src_shifted_left | v_int16x8(_mm_srli_si128(src0_leftBuf.val, 14)))+P1_reg;
src_shifted_right = (src_shifted_right | v_int16x8(_mm_slli_si128(src2.val , 14)))+P1_reg;
res = v_load_aligned(costs+D-8) + (v_min(v_min(src_shifted_left,src_shifted_right),v_min(src1_leftBuf,leftMinCostP2_reg))-leftMinCostP2_reg);
leftMinCost = min(v_min(leftMinCost_new_reg,res));
v_store_aligned(leftBuf+D-8, res);
//process topBuf:
src_shifted_left = v_int16x8(_mm_slli_si128(src1_topBuf.val, 2));
src_shifted_right = v_int16x8(_mm_srli_si128(src1_topBuf.val, 2));
src2 = v_setall_s16(SHRT_MAX);
src_shifted_left = (src_shifted_left | v_int16x8(_mm_srli_si128(src0_topBuf.val, 14)))+P1_reg;
src_shifted_right = (src_shifted_right | v_int16x8(_mm_slli_si128(src2.val , 14)))+P1_reg;
res = v_load_aligned(costs+D-8) + (v_min(v_min(src_shifted_left,src_shifted_right),v_min(src1_topBuf,topMinCostP2_reg))-topMinCostP2_reg);
topMinCost = min(v_min(topMinCost_new_reg,res));
v_store_aligned(topBuf+D-8, res);
#else
CostType leftMinCost_new = SHRT_MAX;
CostType topMinCost_new = SHRT_MAX;
int leftMinCost_P2 = leftMinCost + P2;
int topMinCost_P2 = topMinCost + P2;
CostType leftBuf_prev_i_minus_1 = SHRT_MAX;
CostType topBuf_i_minus_1 = SHRT_MAX;
CostType tmp;
for(int i=0;i<D-1;i++)
{
leftBuf[i] = cv::saturate_cast<CostType>(costs[i] + std::min(std::min(leftBuf_prev_i_minus_1+P1,leftBuf_prev[i+1]+P1),std::min((int)leftBuf_prev[i],leftMinCost_P2))-leftMinCost_P2);
leftBuf_prev_i_minus_1 = leftBuf_prev[i];
leftMinCost_new = std::min(leftMinCost_new,leftBuf[i]);
tmp = topBuf[i];
topBuf[i] = cv::saturate_cast<CostType>(costs[i] + std::min(std::min(topBuf_i_minus_1+P1,topBuf[i+1]+P1),std::min((int)topBuf[i],topMinCost_P2))-topMinCost_P2);
topBuf_i_minus_1 = tmp;
topMinCost_new = std::min(topMinCost_new,topBuf[i]);
}
leftBuf[D-1] = cv::saturate_cast<CostType>(costs[D-1] + std::min(leftBuf_prev_i_minus_1+P1,std::min((int)leftBuf_prev[D-1],leftMinCost_P2))-leftMinCost_P2);
leftMinCost = std::min(leftMinCost_new,leftBuf[D-1]);
topBuf[D-1] = cv::saturate_cast<CostType>(costs[D-1] + std::min(topBuf_i_minus_1+P1,std::min((int)topBuf[D-1],topMinCost_P2))-topMinCost_P2);
topMinCost = std::min(topMinCost_new,topBuf[D-1]);
#endif
}
// performing in-place SGM cost accumulation from right to left (the result is stored in rightBuf) and
// summing rightBuf, topBuf, leftBuf together (the result is stored in leftBuf), as well as finding the
// optimal disparity value with minimum accumulated cost
inline void accumulateCostsRight(CostType* rightBuf, CostType* topBuf, CostType* leftBuf, CostType* costs,
CostType& rightMinCost, int D, int P1, int P2, int& optimal_disp, CostType& min_cost)
{
#if CV_SIMD128 && CV_SSE2
v_int16x8 P1_reg = v_setall_s16(cv::saturate_cast<CostType>(P1));
v_int16x8 rightMinCostP2_reg = v_setall_s16(cv::saturate_cast<CostType>(rightMinCost+P2));
v_int16x8 rightMinCost_new_reg = v_setall_s16(SHRT_MAX);
v_int16x8 src0_rightBuf = v_setall_s16(SHRT_MAX);
v_int16x8 src1_rightBuf = v_load(rightBuf);
v_int16x8 src2;
v_int16x8 src_shifted_left,src_shifted_right;
v_int16x8 res;
v_int16x8 min_sum_cost_reg = v_setall_s16(SHRT_MAX);
v_int16x8 min_sum_pos_reg = v_setall_s16(0);
v_int16x8 loop_idx(0,1,2,3,4,5,6,7);
v_int16x8 eight_reg = v_setall_s16(8);
for(int i=0;i<D-8;i+=8)
{
//lookahead load:
src2 = v_load_aligned(rightBuf+i+8);
//get shifted versions of the current block:
src_shifted_left = v_int16x8(_mm_slli_si128(src1_rightBuf.val, 2));
src_shifted_right = v_int16x8(_mm_srli_si128(src1_rightBuf.val, 2));
// replace shifted-in zeros with proper values and add P1:
src_shifted_left = (src_shifted_left | v_int16x8(_mm_srli_si128(src0_rightBuf.val, 14)))+P1_reg;
src_shifted_right = (src_shifted_right | v_int16x8(_mm_slli_si128(src2.val , 14)))+P1_reg;
// process and save current block:
res = v_load_aligned(costs+i) + (v_min(v_min(src_shifted_left,src_shifted_right),v_min(src1_rightBuf,rightMinCostP2_reg))-rightMinCostP2_reg);
rightMinCost_new_reg = v_min(rightMinCost_new_reg,res);
v_store_aligned(rightBuf+i, res);
// compute and save total cost:
res = res + v_load_aligned(leftBuf+i) + v_load_aligned(topBuf+i);
v_store_aligned(leftBuf+i, res);
// track disparity value with the minimum cost:
min_sum_cost_reg = v_min(min_sum_cost_reg,res);
min_sum_pos_reg = min_sum_pos_reg + ((min_sum_cost_reg == res) & (loop_idx - min_sum_pos_reg));
loop_idx = loop_idx+eight_reg;
//update src:
src0_rightBuf = src1_rightBuf;
src1_rightBuf = src2;
}
// a bit different processing for the last cycle of the loop:
src_shifted_left = v_int16x8(_mm_slli_si128(src1_rightBuf.val, 2));
src_shifted_right = v_int16x8(_mm_srli_si128(src1_rightBuf.val, 2));
src2 = v_setall_s16(SHRT_MAX);
src_shifted_left = (src_shifted_left | v_int16x8(_mm_srli_si128(src0_rightBuf.val, 14)))+P1_reg;
src_shifted_right = (src_shifted_right | v_int16x8(_mm_slli_si128(src2.val , 14)))+P1_reg;
res = v_load_aligned(costs+D-8) + (v_min(v_min(src_shifted_left,src_shifted_right),v_min(src1_rightBuf,rightMinCostP2_reg))-rightMinCostP2_reg);
rightMinCost = min(v_min(rightMinCost_new_reg,res));
v_store_aligned(rightBuf+D-8, res);
res = res + v_load_aligned(leftBuf+D-8) + v_load_aligned(topBuf+D-8);
v_store_aligned(leftBuf+D-8, res);
min_sum_cost_reg = v_min(min_sum_cost_reg,res);
min_cost = min(min_sum_cost_reg);
min_sum_pos_reg = min_sum_pos_reg + ((min_sum_cost_reg == res) & (loop_idx - min_sum_pos_reg));
optimal_disp = min_pos(min_sum_cost_reg,min_sum_pos_reg);
#else
CostType rightMinCost_new = SHRT_MAX;
int rightMinCost_P2 = rightMinCost + P2;
CostType rightBuf_i_minus_1 = SHRT_MAX;
CostType tmp;
min_cost = SHRT_MAX;
for(int i=0;i<D-1;i++)
{
tmp = rightBuf[i];
rightBuf[i] = cv::saturate_cast<CostType>(costs[i] + std::min(std::min(rightBuf_i_minus_1+P1,rightBuf[i+1]+P1),std::min((int)rightBuf[i],rightMinCost_P2))-rightMinCost_P2);
rightBuf_i_minus_1 = tmp;
rightMinCost_new = std::min(rightMinCost_new,rightBuf[i]);
leftBuf[i] = cv::saturate_cast<CostType>((int)leftBuf[i]+rightBuf[i]+topBuf[i]);
if(leftBuf[i]<min_cost)
{
optimal_disp = i;
min_cost = leftBuf[i];
}
}
rightBuf[D-1] = cv::saturate_cast<CostType>(costs[D-1] + std::min(rightBuf_i_minus_1+P1,std::min((int)rightBuf[D-1],rightMinCost_P2))-rightMinCost_P2);
rightMinCost = std::min(rightMinCost_new,rightBuf[D-1]);
leftBuf[D-1] = cv::saturate_cast<CostType>((int)leftBuf[D-1]+rightBuf[D-1]+topBuf[D-1]);
if(leftBuf[D-1]<min_cost)
{
optimal_disp = D-1;
min_cost = leftBuf[D-1];
}
#endif
}
void SGBM3WayMainLoop::operator () (const Range& range) const
{
// force separate processing of stripes:
if(range.end>range.start+1)
{
for(int n=range.start;n<range.end;n++)
(*this)(Range(n,n+1));
return;
}
const int DISP_SCALE = (1 << StereoMatcher::DISP_SHIFT);
int INVALID_DISP = minD - 1, INVALID_DISP_SCALED = INVALID_DISP*DISP_SCALE;
// setting up the ranges:
int src_start_idx = std::max(std::min(range.start * stripe_sz - stripe_overlap, height),0);
int src_end_idx = std::min(range.end * stripe_sz, height);
int dst_offset;
if(range.start==0)
dst_offset=stripe_overlap;
else
dst_offset=0;
Mat cur_buffer = buffers [range.start];
Mat cur_disp = dst_disp[range.start];
cur_disp = Scalar(INVALID_DISP_SCALED);
// prepare buffers:
CostType *curCostVolumeLine, *hsumBuf, *pixDiff;
PixType* tmpBuf;
CostType *horPassCostVolume, *vertPassCostVolume, *vertPassMin, *rightPassBuf, *disp2CostBuf;
short* disp2Buf;
getBufferPointers(cur_buffer,width,width1,D,img1->channels(),SH2,P2,
curCostVolumeLine,hsumBuf,pixDiff,tmpBuf,horPassCostVolume,
vertPassCostVolume,vertPassMin,rightPassBuf,disp2CostBuf,disp2Buf);
// start real processing:
for(int y=src_start_idx;y<src_end_idx;y++)
{
getRawMatchingCost(curCostVolumeLine,hsumBuf,pixDiff,tmpBuf,y,src_start_idx);
short* disp_row = (short*)cur_disp.ptr(dst_offset+(y-src_start_idx));
// initialize the auxiliary buffers for the pseudo left-right consistency check:
for(int x=0;x<width;x++)
{
disp2Buf[x] = (short)INVALID_DISP_SCALED;
disp2CostBuf[x] = SHRT_MAX;
}
CostType* C = curCostVolumeLine - D;
CostType prev_min, min_cost;
int d, best_d;
d = best_d = 0;
// forward pass
prev_min=0;
for (int x=D;x<(1+width1)*D;x+=D)
accumulateCostsLeftTop(horPassCostVolume+x,horPassCostVolume+x-D,vertPassCostVolume+x,C+x,prev_min,vertPassMin[x/D],D,P1,P2);
//backward pass
memset(rightPassBuf,0,D*sizeof(CostType));
prev_min=0;
for (int x=width1*D;x>=D;x-=D)
{
accumulateCostsRight(rightPassBuf,vertPassCostVolume+x,horPassCostVolume+x,C+x,prev_min,D,P1,P2,best_d,min_cost);
if(uniquenessRatio>0)
{
#if CV_SIMD128
horPassCostVolume+=x;
int thresh = (100*min_cost)/(100-uniquenessRatio);
v_int16x8 thresh_reg = v_setall_s16((short)(thresh+1));
v_int16x8 d1 = v_setall_s16((short)(best_d-1));
v_int16x8 d2 = v_setall_s16((short)(best_d+1));
v_int16x8 eight_reg = v_setall_s16(8);
v_int16x8 cur_d(0,1,2,3,4,5,6,7);
v_int16x8 mask,cost1,cost2;
for( d = 0; d < D; d+=16 )
{
cost1 = v_load_aligned(horPassCostVolume+d);
cost2 = v_load_aligned(horPassCostVolume+d+8);
mask = cost1 < thresh_reg;
mask = mask & ( (cur_d<d1) | (cur_d>d2) );
if( v_signmask(mask) )
break;
cur_d = cur_d+eight_reg;
mask = cost2 < thresh_reg;
mask = mask & ( (cur_d<d1) | (cur_d>d2) );
if( v_signmask(mask) )
break;
cur_d = cur_d+eight_reg;
}
horPassCostVolume-=x;
#else
for( d = 0; d < D; d++ )
{
if( horPassCostVolume[x+d]*(100 - uniquenessRatio) < min_cost*100 && std::abs(d - best_d) > 1 )
break;
}
#endif
if( d < D )
continue;
}
d = best_d;
int _x2 = x/D - 1 + minX1 - d - minD;
if( _x2>=0 && _x2<width && disp2CostBuf[_x2] > min_cost )
{
disp2CostBuf[_x2] = min_cost;
disp2Buf[_x2] = (short)(d + minD);
}
if( 0 < d && d < D-1 )
{
// do subpixel quadratic interpolation:
// fit parabola into (x1=d-1, y1=Sp[d-1]), (x2=d, y2=Sp[d]), (x3=d+1, y3=Sp[d+1])
// then find minimum of the parabola.
int denom2 = std::max(horPassCostVolume[x+d-1] + horPassCostVolume[x+d+1] - 2*horPassCostVolume[x+d], 1);
d = d*DISP_SCALE + ((horPassCostVolume[x+d-1] - horPassCostVolume[x+d+1])*DISP_SCALE + denom2)/(denom2*2);
}
else
d *= DISP_SCALE;
disp_row[(x/D)-1 + minX1] = (DispType)(d + minD*DISP_SCALE);
}
for(int x = minX1; x < maxX1; x++ )
{
// pseudo LRC consistency check using only one disparity map;
// pixels with difference more than disp12MaxDiff are invalidated
int d1 = disp_row[x];
if( d1 == INVALID_DISP_SCALED )
continue;
int _d = d1 >> StereoMatcher::DISP_SHIFT;
int d_ = (d1 + DISP_SCALE-1) >> StereoMatcher::DISP_SHIFT;
int _x = x - _d, x_ = x - d_;
if( 0 <= _x && _x < width && disp2Buf[_x] >= minD && std::abs(disp2Buf[_x] - _d) > disp12MaxDiff &&
0 <= x_ && x_ < width && disp2Buf[x_] >= minD && std::abs(disp2Buf[x_] - d_) > disp12MaxDiff )
disp_row[x] = (short)INVALID_DISP_SCALED;
}
}
}
static void computeDisparity3WaySGBM( const Mat& img1, const Mat& img2,
Mat& disp1, const StereoSGBMParams& params,
Mat* buffers, int nstripes )
{
// precompute a lookup table for the raw matching cost computation:
const int TAB_OFS = 256*4, TAB_SIZE = 256 + TAB_OFS*2;
PixType* clipTab = new PixType[TAB_SIZE];
int ftzero = std::max(params.preFilterCap, 15) | 1;
for(int k = 0; k < TAB_SIZE; k++ )
clipTab[k] = (PixType)(std::min(std::max(k - TAB_OFS, -ftzero), ftzero) + ftzero);
// allocate separate dst_disp arrays to avoid conflicts due to stripe overlap:
int stripe_sz = (int)ceil(img1.rows/(double)nstripes);
int stripe_overlap = (params.SADWindowSize/2+1) + (int)ceil(0.1*stripe_sz);
Mat* dst_disp = new Mat[nstripes];
for(int i=0;i<nstripes;i++)
dst_disp[i].create(stripe_sz+stripe_overlap,img1.cols,CV_16S);
parallel_for_(Range(0,nstripes),SGBM3WayMainLoop(buffers,img1,img2,dst_disp,params,clipTab,nstripes,stripe_overlap));
//assemble disp1 from dst_disp:
short* dst_row;
short* src_row;
for(int i=0;i<disp1.rows;i++)
{
dst_row = (short*)disp1.ptr(i);
src_row = (short*)dst_disp[i/stripe_sz].ptr(stripe_overlap+i%stripe_sz);
memcpy(dst_row,src_row,disp1.cols*sizeof(short));
}
delete[] clipTab;
delete[] dst_disp;
}
class StereoSGBMImpl : public StereoSGBM
{
public:
@ -857,7 +1489,11 @@ public:
disparr.create( left.size(), CV_16S );
Mat disp = disparr.getMat();
computeDisparitySGBM( left, right, disp, params, buffer );
if(params.mode==MODE_SGBM_3WAY)
computeDisparity3WaySGBM( left, right, disp, params, buffers, num_stripes );
else
computeDisparitySGBM( left, right, disp, params, buffer );
medianBlur(disp, disp, 3);
if( params.speckleWindowSize > 0 )
@ -933,6 +1569,12 @@ public:
StereoSGBMParams params;
Mat buffer;
// the number of stripes is fixed, disregarding the number of threads/processors
// to make the results fully reproducible:
static const int num_stripes = 4;
Mat buffers[num_stripes];
static const char* name_;
};

View File

@ -742,7 +742,7 @@ protected:
{
int ndisp;
int winSize;
bool fullDP;
int mode;
};
vector<RunParams> caseRunParams;
@ -757,7 +757,7 @@ protected:
RunParams params;
String ndisp = fn[i+2]; params.ndisp = atoi(ndisp.c_str());
String winSize = fn[i+3]; params.winSize = atoi(winSize.c_str());
String fullDP = fn[i+4]; params.fullDP = atoi(fullDP.c_str()) == 0 ? false : true;
String mode = fn[i+4]; params.mode = atoi(mode.c_str());
caseNames.push_back( caseName );
caseDatasets.push_back( datasetName );
caseRunParams.push_back( params );
@ -773,8 +773,7 @@ protected:
Ptr<StereoSGBM> sgbm = StereoSGBM::create( 0, params.ndisp, params.winSize,
10*params.winSize*params.winSize,
40*params.winSize*params.winSize,
1, 63, 10, 100, 32, params.fullDP ?
StereoSGBM::MODE_HH : StereoSGBM::MODE_SGBM );
1, 63, 10, 100, 32, params.mode );
sgbm->compute( leftImg, rightImg, leftDisp );
CV_Assert( leftDisp.type() == CV_16SC1 );
leftDisp/=16;

View File

@ -20,7 +20,7 @@ using namespace cv;
static void print_help()
{
printf("\nDemo stereo matching converting L and R images into disparity and point clouds\n");
printf("\nUsage: stereo_match <left_image> <right_image> [--algorithm=bm|sgbm|hh] [--blocksize=<block_size>]\n"
printf("\nUsage: stereo_match <left_image> <right_image> [--algorithm=bm|sgbm|hh|sgbm3way] [--blocksize=<block_size>]\n"
"[--max-disparity=<max_disparity>] [--scale=scale_factor>] [-i <intrinsic_filename>] [-e <extrinsic_filename>]\n"
"[--no-display] [-o <disparity_image>] [-p <point_cloud_file>]\n");
}
@ -61,7 +61,7 @@ int main(int argc, char** argv)
const char* disparity_filename = 0;
const char* point_cloud_filename = 0;
enum { STEREO_BM=0, STEREO_SGBM=1, STEREO_HH=2, STEREO_VAR=3 };
enum { STEREO_BM=0, STEREO_SGBM=1, STEREO_HH=2, STEREO_VAR=3, STEREO_3WAY=4 };
int alg = STEREO_SGBM;
int SADWindowSize = 0, numberOfDisparities = 0;
bool no_display = false;
@ -85,7 +85,8 @@ int main(int argc, char** argv)
alg = strcmp(_alg, "bm") == 0 ? STEREO_BM :
strcmp(_alg, "sgbm") == 0 ? STEREO_SGBM :
strcmp(_alg, "hh") == 0 ? STEREO_HH :
strcmp(_alg, "var") == 0 ? STEREO_VAR : -1;
strcmp(_alg, "var") == 0 ? STEREO_VAR :
strcmp(_alg, "sgbm3way") == 0 ? STEREO_3WAY : -1;
if( alg < 0 )
{
printf("Command-line parameter error: Unknown stereo algorithm\n\n");
@ -257,7 +258,12 @@ int main(int argc, char** argv)
sgbm->setSpeckleWindowSize(100);
sgbm->setSpeckleRange(32);
sgbm->setDisp12MaxDiff(1);
sgbm->setMode(alg == STEREO_HH ? StereoSGBM::MODE_HH : StereoSGBM::MODE_SGBM);
if(alg==STEREO_HH)
sgbm->setMode(StereoSGBM::MODE_HH);
else if(alg==STEREO_SGBM)
sgbm->setMode(StereoSGBM::MODE_SGBM);
else if(alg==STEREO_3WAY)
sgbm->setMode(StereoSGBM::MODE_SGBM_3WAY);
Mat disp, disp8;
//Mat img1p, img2p, dispp;
@ -267,7 +273,7 @@ int main(int argc, char** argv)
int64 t = getTickCount();
if( alg == STEREO_BM )
bm->compute(img1, img2, disp);
else if( alg == STEREO_SGBM || alg == STEREO_HH )
else if( alg == STEREO_SGBM || alg == STEREO_HH || alg == STEREO_3WAY )
sgbm->compute(img1, img2, disp);
t = getTickCount() - t;
printf("Time elapsed: %fms\n", t*1000/getTickFrequency());