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Merge pull request #6958 from mschoeneck:Common-Canny-parallelization

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* Common Canny parallelization added. TBB and single thread code removed. Final pass vectorized with SSE2 intrinsics.

* wrong #ifdef replaced with #if

* Merged to actual Canny version

* Merged common parallelized Canny with actual Canny implementation

* Remove 'Mutex *mutex' and pass 'Mutex mutex' from outside to parallelCanny

* Replaced extern Mutex with intern mutable Mutex.
This commit is contained in:
mschoeneck 2016-08-05 16:20:56 +02:00 committed by Alexander Alekhin
parent 35d0a45df6
commit 5f30a0a076
1 changed files with 163 additions and 82 deletions
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245
modules/imgproc/src/canny.cpp
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@ -42,6 +42,7 @@
#include "precomp.hpp"
#include "opencl_kernels_imgproc.hpp"
#include <queue>
#ifdef _MSC_VER
#pragma warning( disable: 4127 ) // conditional expression is constant
@ -276,25 +277,22 @@ static bool ocl_Canny(InputArray _src, const UMat& dx_, const UMat& dy_, OutputA
#endif
#ifdef HAVE_TBB
// Queue with peaks that will processed serially.
static tbb::concurrent_queue<uchar*> borderPeaks;
class tbbCanny
class parallelCanny : public ParallelLoopBody
{
public:
tbbCanny(const Range _boundaries, const Mat& _src, uchar* _map, int _low,
int _high, int _aperture_size, bool _L2gradient)
: boundaries(_boundaries), src(_src), map(_map), low(_low), high(_high),
aperture_size(_aperture_size), L2gradient(_L2gradient)
{}
// This parallel version of Canny algorithm splits the src image in threadsNumber horizontal slices.
// The first row of each slice contains the last row of the previous slice and
// the last row of each slice contains the first row of the next slice
// so that each slice is independent and no mutexes are required.
void operator()() const
public:
parallelCanny(const Mat& _src, uchar* _map, int _low, int _high, int _aperture_size, bool _L2gradient, std::queue<uchar*> *borderPeaksParallel) :
src(_src), map(_map), low(_low), high(_high), aperture_size(_aperture_size), L2gradient(_L2gradient), _borderPeaksParallel(borderPeaksParallel)
{
}
~parallelCanny()
{
}
parallelCanny& operator=(const parallelCanny&) { return *this; }
void operator()(const Range &boundaries) const
{
#if CV_SSE2
bool haveSSE2 = checkHardwareSupport(CV_CPU_SSE2);
@ -303,13 +301,19 @@ public:
const int type = src.type(), cn = CV_MAT_CN(type);
Mat dx, dy;
std::queue<uchar*> borderPeaksLocal;
ptrdiff_t mapstep = src.cols + 2;
// In sobel transform we calculate ksize2 extra lines for the first and last rows of each slice
// because IPPDerivSobel expects only isolated ROIs, in contrast with the opencv version which
// uses the pixels outside of the ROI to form a border.
uchar ksize2 = aperture_size / 2;
int ksize2 = aperture_size / 2;
// If Scharr filter: aperture_size is 3 and ksize2 is 1
if(aperture_size == -1)
{
ksize2 = 1;
}
if (boundaries.start == 0 && boundaries.end == src.rows)
{
@ -408,14 +412,20 @@ public:
{
__m128i v_dx = _mm_loadu_si128((const __m128i *)(_dx + j));
__m128i v_dy = _mm_loadu_si128((const __m128i *)(_dy + j));
v_dx = _mm_max_epi16(v_dx, _mm_sub_epi16(v_zero, v_dx));
v_dy = _mm_max_epi16(v_dy, _mm_sub_epi16(v_zero, v_dy));
__m128i v_norm = _mm_add_epi32(_mm_unpacklo_epi16(v_dx, v_zero), _mm_unpacklo_epi16(v_dy, v_zero));
_mm_storeu_si128((__m128i *)(_norm + j), v_norm);
__m128i v_dx_abs = _mm_max_epi16(v_dx, _mm_sub_epi16(v_zero, v_dx));
__m128i v_dy_abs = _mm_max_epi16(v_dy, _mm_sub_epi16(v_zero, v_dy));
v_norm = _mm_add_epi32(_mm_unpackhi_epi16(v_dx, v_zero), _mm_unpackhi_epi16(v_dy, v_zero));
_mm_storeu_si128((__m128i *)(_norm + j + 4), v_norm);
__m128i v_dx_ml = _mm_unpacklo_epi16(v_dx_abs, v_zero);
__m128i v_dy_ml = _mm_unpacklo_epi16(v_dy_abs, v_zero);
__m128i v_dx_mh = _mm_unpackhi_epi16(v_dx_abs, v_zero);
__m128i v_dy_mh = _mm_unpackhi_epi16(v_dy_abs, v_zero);
__m128i v_norm_ml = _mm_add_epi32(v_dx_ml, v_dy_ml);
__m128i v_norm_mh = _mm_add_epi32(v_dx_mh, v_dy_mh);
_mm_storeu_si128((__m128i *)(_norm + j), v_norm_ml);
_mm_storeu_si128((__m128i *)(_norm + j + 4), v_norm_mh);
}
}
#elif CV_NEON
@ -444,8 +454,10 @@ public:
__m128i v_dx_dy_ml = _mm_unpacklo_epi16(v_dx, v_dy);
__m128i v_dx_dy_mh = _mm_unpackhi_epi16(v_dx, v_dy);
__m128i v_norm_ml = _mm_madd_epi16(v_dx_dy_ml, v_dx_dy_ml);
__m128i v_norm_mh = _mm_madd_epi16(v_dx_dy_mh, v_dx_dy_mh);
_mm_storeu_si128((__m128i *)(_norm + j), v_norm_ml);
_mm_storeu_si128((__m128i *)(_norm + j + 4), v_norm_mh);
}
@ -508,13 +520,13 @@ public:
#define CANNY_PUSH(d) *(d) = uchar(2), *stack_top++ = (d)
#define CANNY_POP(d) (d) = *--stack_top
#define CANNY_SHIFT 15
const int TG22 = (int)(0.4142135623730950488016887242097*(1 << CANNY_SHIFT) + 0.5);
int prev_flag = 0;
bool canny_push = false;
for (int j = 0; j < src.cols; j++)
{
#define CANNY_SHIFT 15
const int TG22 = (int)(0.4142135623730950488016887242097*(1<<CANNY_SHIFT) + 0.5);
int m = _mag[j];
if (m > low)
@ -592,7 +604,7 @@ public:
// slice in a queue to be serially processed later.
if ( (m < map + (boundaries.start + 2) * mapstep) || (m >= map + boundaries.end * mapstep) )
{
borderPeaks.push(m);
borderPeaksLocal.push(m);
continue;
}
@ -605,20 +617,103 @@ public:
if (!m[mapstep]) CANNY_PUSH(m + mapstep);
if (!m[mapstep+1]) CANNY_PUSH(m + mapstep + 1);
}
AutoLock lock(mutex);
while (!borderPeaksLocal.empty()) {
_borderPeaksParallel->push(borderPeaksLocal.front());
borderPeaksLocal.pop();
}
}
private:
const Range boundaries;
const Mat& src;
uchar* map;
int low;
int high;
int aperture_size;
int low, high, aperture_size;
bool L2gradient;
std::queue<uchar*> *_borderPeaksParallel;
mutable Mutex mutex;
};
class finalPass : public ParallelLoopBody
{
public:
finalPass(const Mat & _src, Mat &_dst, uchar *_map, ptrdiff_t _mapstep) :
src(_src), dst(_dst), map(_map), mapstep(_mapstep) {}
~finalPass() {}
finalPass& operator=(const finalPass&) {return *this;}
void operator()(const Range &boundaries) const
{
// the final pass, form the final image
const uchar* pmap = map + mapstep + 1 + (ptrdiff_t)(mapstep * boundaries.start);
uchar* pdst = dst.ptr() + (ptrdiff_t)(dst.step * boundaries.start);
#if CV_SSE2
bool haveSSE2 = checkHardwareSupport(CV_CPU_SSE2);
#endif
for (int i = boundaries.start; i < boundaries.end; i++, pmap += mapstep, pdst += dst.step)
{
int j = 0;
#if CV_SSE2
if(haveSSE2) {
const __m128i v_zero = _mm_setzero_si128();
for(; j <= src.cols - 32; j += 32) {
__m128i v_pmap1 = _mm_loadu_si128((const __m128i*)(pmap + j));
__m128i v_pmap2 = _mm_loadu_si128((const __m128i*)(pmap + j + 16));
__m128i v_pmaplo1 = _mm_unpacklo_epi8(v_pmap1, v_zero);
__m128i v_pmaphi1 = _mm_unpackhi_epi8(v_pmap1, v_zero);
__m128i v_pmaplo2 = _mm_unpacklo_epi8(v_pmap2, v_zero);
__m128i v_pmaphi2 = _mm_unpackhi_epi8(v_pmap2, v_zero);
v_pmaplo1 = _mm_srli_epi16(v_pmaplo1, 1);
v_pmaphi1 = _mm_srli_epi16(v_pmaphi1, 1);
v_pmaplo2 = _mm_srli_epi16(v_pmaplo2, 1);
v_pmaphi2 = _mm_srli_epi16(v_pmaphi2, 1);
v_pmap1 = _mm_packus_epi16(v_pmaplo1, v_pmaphi1);
v_pmap2 = _mm_packus_epi16(v_pmaplo2, v_pmaphi2);
v_pmap1 = _mm_sub_epi8(v_zero, v_pmap1);
v_pmap2 = _mm_sub_epi8(v_zero, v_pmap2);
_mm_storeu_si128((__m128i*)(pdst + j), v_pmap1);
_mm_storeu_si128((__m128i*)(pdst + j + 16), v_pmap2);
}
for(; j <= src.cols - 16; j += 16) {
__m128i v_pmap = _mm_loadu_si128((const __m128i*)(pmap + j));
__m128i v_pmaplo = _mm_unpacklo_epi8(v_pmap, v_zero);
__m128i v_pmaphi = _mm_unpackhi_epi8(v_pmap, v_zero);
v_pmaplo = _mm_srli_epi16(v_pmaplo, 1);
v_pmaphi = _mm_srli_epi16(v_pmaphi, 1);
v_pmap = _mm_packus_epi16(v_pmaplo, v_pmaphi);
v_pmap = _mm_sub_epi8(v_zero, v_pmap);
_mm_storeu_si128((__m128i*)(pdst + j), v_pmap);
}
}
#endif
for (; j < src.cols; j++)
pdst[j] = (uchar)-(pmap[j] >> 1);
}
}
private:
const Mat &src;
Mat &dst;
uchar *map;
ptrdiff_t mapstep;
};
void Canny( InputArray _src, OutputArray _dst,
double low_thresh, double high_thresh,
int aperture_size, bool L2gradient )
@ -654,8 +749,6 @@ void Canny( InputArray _src, OutputArray _dst,
CV_IPP_RUN(USE_IPP_CANNY && (aperture_size == 3 && !L2gradient && 1 == cn), ippCanny<false>(src, Mat(), Mat(), dst, (float)low_thresh, (float)high_thresh))
#ifdef HAVE_TBB
if (L2gradient)
{
low_thresh = std::min(32767.0, low_thresh);
@ -667,44 +760,49 @@ if (L2gradient)
int low = cvFloor(low_thresh);
int high = cvFloor(high_thresh);
ptrdiff_t mapstep = src.cols + 2;
AutoBuffer<uchar> buffer((src.cols+2)*(src.rows+2));
ptrdiff_t mapstep = src.cols + 2;
AutoBuffer<uchar> buffer((src.cols+2)*(src.rows+2) + cn * mapstep * 3 * sizeof(int));
uchar* map = (uchar*)buffer;
memset(map, 1, mapstep);
memset(map + mapstep*(src.rows + 1), 1, mapstep);
int* mag_buf[3];
mag_buf[0] = (int*)(uchar*)buffer;
mag_buf[1] = mag_buf[0] + mapstep*cn;
mag_buf[2] = mag_buf[1] + mapstep*cn;
memset(mag_buf[0], 0, /* cn* */mapstep*sizeof(int));
int threadsNumber = tbb::task_scheduler_init::default_num_threads();
int grainSize = src.rows / threadsNumber;
uchar *map = (uchar*)(mag_buf[2] + mapstep*cn);
memset(map, 1, mapstep);
memset(map + mapstep*(src.rows + 1), 1, mapstep);
// Make a fallback for pictures with too few rows.
uchar ksize2 = aperture_size / 2;
int minGrainSize = 1 + ksize2;
int maxGrainSize = src.rows - 2 - 2*ksize2;
if ( !( minGrainSize <= grainSize && grainSize <= maxGrainSize ) )
{
threadsNumber = 1;
grainSize = src.rows;
}
// Minimum number of threads should be 1, maximum should not exceed number of CPU's, because of overhead
int numOfThreads = std::max(1, std::min(getNumThreads(), getNumberOfCPUs()));
tbb::task_group g;
// Make a fallback for pictures with too few rows.
int grainSize = src.rows / numOfThreads;
int ksize2 = aperture_size / 2;
// If Scharr filter: aperture size is 3, ksize2 is 1
if(aperture_size == -1)
{
ksize2 = 1;
}
for (int i = 0; i < threadsNumber; ++i)
{
if (i < threadsNumber - 1)
g.run(tbbCanny(Range(i * grainSize, (i + 1) * grainSize), src, map, low, high, aperture_size, L2gradient));
else
g.run(tbbCanny(Range(i * grainSize, src.rows), src, map, low, high, aperture_size, L2gradient));
}
int minGrainSize = 2 * (ksize2 + 1);
if (grainSize < minGrainSize)
{
numOfThreads = std::max(1, src.rows / minGrainSize);
}
g.wait();
std::queue<uchar*> borderPeaksParallel;
#define CANNY_PUSH_SERIAL(d) *(d) = uchar(2), borderPeaks.push(d)
parallel_for_(Range(0, src.rows), parallelCanny(src, map, low, high, aperture_size, L2gradient, &borderPeaksParallel), numOfThreads);
// now track the edges (hysteresis thresholding)
uchar* m;
while (borderPeaks.try_pop(m))
{
#define CANNY_PUSH_SERIAL(d) *(d) = uchar(2), borderPeaksParallel.push(d)
// now track the edges (hysteresis thresholding)
uchar* m;
while (!borderPeaksParallel.empty())
{
m = borderPeaksParallel.front();
borderPeaksParallel.pop();
if (!m[-1]) CANNY_PUSH_SERIAL(m - 1);
if (!m[1]) CANNY_PUSH_SERIAL(m + 1);
if (!m[-mapstep-1]) CANNY_PUSH_SERIAL(m - mapstep - 1);
@ -715,24 +813,7 @@ while (borderPeaks.try_pop(m))
if (!m[mapstep+1]) CANNY_PUSH_SERIAL(m + mapstep + 1);
}
// the final pass, form the final image
const uchar* pmap = map + mapstep + 1;
uchar* pdst = dst.ptr();
for (int i = 0; i < src.rows; i++, pmap += mapstep, pdst += dst.step)
{
for (int j = 0; j < src.cols; j++)
pdst[j] = (uchar)-(pmap[j] >> 1);
}
#else
Mat dx(src.rows, src.cols, CV_16SC(cn));
Mat dy(src.rows, src.cols, CV_16SC(cn));
Sobel(src, dx, CV_16S, 1, 0, aperture_size, 1, 0, BORDER_REPLICATE);
Sobel(src, dy, CV_16S, 0, 1, aperture_size, 1, 0, BORDER_REPLICATE);
CannyImpl(dx, dy, dst, low_thresh, high_thresh, L2gradient);
#endif
parallel_for_(Range(0, src.rows), finalPass(src, dst, map, mapstep), src.total()/(double)(1<<16));
}
void Canny( InputArray _dx, InputArray _dy, OutputArray _dst,