/*M/////////////////////////////////////////////////////////////////////////////////////// // // IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. // // 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 // // Copyright (C) 2000-2008, Intel Corporation, all rights reserved. // Copyright (C) 2009, Willow Garage Inc., all rights reserved. // Third party copyrights are property of their respective owners. // // Redistribution and use in source and binary forms, with or without modification, // are permitted provided that the following conditions are met: // // * Redistribution's of source code must retain the above copyright notice, // this list of conditions and the following disclaimer. // // * Redistribution's 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. // // * The name of the copyright holders may not 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 the Intel Corporation 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. // //M*/ #if !defined CUDA_DISABLER #include #include #include #include #include #include namespace cv { namespace cuda { namespace device { namespace ccl { enum { WARP_SIZE = 32, WARP_LOG = 5, CTA_SIZE_X = 32, CTA_SIZE_Y = 8, STA_SIZE_MERGE_Y = 4, STA_SIZE_MERGE_X = 32, TPB_X = 1, TPB_Y = 4, TILE_COLS = CTA_SIZE_X * TPB_X, TILE_ROWS = CTA_SIZE_Y * TPB_Y }; template struct IntervalsTraits { typedef T elem_type; }; template<> struct IntervalsTraits { typedef int dist_type; enum {ch = 1}; }; template<> struct IntervalsTraits { typedef int3 dist_type; enum {ch = 3}; }; template<> struct IntervalsTraits { typedef int4 dist_type; enum {ch = 4}; }; template<> struct IntervalsTraits { typedef int dist_type; enum {ch = 1}; }; template<> struct IntervalsTraits { typedef int3 dist_type; enum {ch = 3}; }; template<> struct IntervalsTraits { typedef int4 dist_type; enum {ch = 4}; }; template<> struct IntervalsTraits { typedef float dist_type; enum {ch = 1}; }; template<> struct IntervalsTraits { typedef int dist_type; enum {ch = 1}; }; typedef unsigned char component; enum Edges { UP = 1, DOWN = 2, LEFT = 4, RIGHT = 8, EMPTY = 0xF0 }; template struct InInterval {}; template struct InInterval { typedef typename VecTraits::elem_type E; __host__ __device__ __forceinline__ InInterval(const float4& _lo, const float4& _hi) : lo((E)(-_lo.x)), hi((E)_hi.x) { } T lo, hi; template __device__ __forceinline__ bool operator() (const I& a, const I& b) const { I d = a - b; return lo <= d && d <= hi; } }; template struct InInterval { typedef typename VecTraits::elem_type E; __host__ __device__ __forceinline__ InInterval(const float4& _lo, const float4& _hi) : lo (VecTraits::make((E)(-_lo.x), (E)(-_lo.y), (E)(-_lo.z))), hi (VecTraits::make((E)_hi.x, (E)_hi.y, (E)_hi.z)) { } T lo, hi; template __device__ __forceinline__ bool operator() (const I& a, const I& b) const { I d = saturate_cast(a - b); return lo.x <= d.x && d.x <= hi.x && lo.y <= d.y && d.y <= hi.y && lo.z <= d.z && d.z <= hi.z; } }; template struct InInterval { typedef typename VecTraits::elem_type E; __host__ __device__ __forceinline__ InInterval(const float4& _lo, const float4& _hi) : lo (VecTraits::make((E)(-_lo.x), (E)(-_lo.y), (E)(-_lo.z), (E)(-_lo.w))), hi (VecTraits::make((E)_hi.x, (E)_hi.y, (E)_hi.z, (E)_hi.w)) { } T lo, hi; template __device__ __forceinline__ bool operator() (const I& a, const I& b) const { I d = saturate_cast(a - b); return lo.x <= d.x && d.x <= hi.x && lo.y <= d.y && d.y <= hi.y && lo.z <= d.z && d.z <= hi.z && lo.w <= d.w && d.w <= hi.w; } }; template __global__ void computeConnectivity(const PtrStepSz image, PtrStepSzb components, F connected) { int x = threadIdx.x + blockIdx.x * blockDim.x; int y = threadIdx.y + blockIdx.y * blockDim.y; if (x >= image.cols || y >= image.rows) return; T intensity = image(y, x); component c = 0; if ( x > 0 && connected(intensity, image(y, x - 1))) c |= LEFT; if ( y > 0 && connected(intensity, image(y - 1, x))) c |= UP; if ( x + 1 < image.cols && connected(intensity, image(y, x + 1))) c |= RIGHT; if ( y + 1 < image.rows && connected(intensity, image(y + 1, x))) c |= DOWN; components(y, x) = c; } template< typename T> void computeEdges(const PtrStepSzb& image, PtrStepSzb edges, const float4& lo, const float4& hi, cudaStream_t stream) { dim3 block(CTA_SIZE_X, CTA_SIZE_Y); dim3 grid(divUp(image.cols, block.x), divUp(image.rows, block.y)); typedef InInterval::dist_type, IntervalsTraits::ch> Int_t; Int_t inInt(lo, hi); computeConnectivity<<>>(static_cast >(image), edges, inInt); cudaSafeCall( cudaGetLastError() ); if (stream == 0) cudaSafeCall( cudaDeviceSynchronize() ); } template void computeEdges (const PtrStepSzb& image, PtrStepSzb edges, const float4& lo, const float4& hi, cudaStream_t stream); template void computeEdges (const PtrStepSzb& image, PtrStepSzb edges, const float4& lo, const float4& hi, cudaStream_t stream); template void computeEdges (const PtrStepSzb& image, PtrStepSzb edges, const float4& lo, const float4& hi, cudaStream_t stream); template void computeEdges (const PtrStepSzb& image, PtrStepSzb edges, const float4& lo, const float4& hi, cudaStream_t stream); template void computeEdges(const PtrStepSzb& image, PtrStepSzb edges, const float4& lo, const float4& hi, cudaStream_t stream); template void computeEdges(const PtrStepSzb& image, PtrStepSzb edges, const float4& lo, const float4& hi, cudaStream_t stream); template void computeEdges (const PtrStepSzb& image, PtrStepSzb edges, const float4& lo, const float4& hi, cudaStream_t stream); template void computeEdges (const PtrStepSzb& image, PtrStepSzb edges, const float4& lo, const float4& hi, cudaStream_t stream); __global__ void lableTiles(const PtrStepSzb edges, PtrStepSzi comps) { int x = threadIdx.x + blockIdx.x * TILE_COLS; int y = threadIdx.y + blockIdx.y * TILE_ROWS; if (x >= edges.cols || y >= edges.rows) return; //currently x is 1 int bounds = ((y + TPB_Y) < edges.rows); __shared__ int labelsTile[TILE_ROWS][TILE_COLS]; __shared__ int edgesTile[TILE_ROWS][TILE_COLS]; int new_labels[TPB_Y][TPB_X]; int old_labels[TPB_Y][TPB_X]; #pragma unroll for (int i = 0; i < TPB_Y; ++i) #pragma unroll for (int j = 0; j < TPB_X; ++j) { int yloc = threadIdx.y + CTA_SIZE_Y * i; int xloc = threadIdx.x + CTA_SIZE_X * j; component c = edges(bounds * (y + CTA_SIZE_Y * i), x + CTA_SIZE_X * j); if (!xloc) c &= ~LEFT; if (!yloc) c &= ~UP; if (xloc == TILE_COLS -1) c &= ~RIGHT; if (yloc == TILE_ROWS -1) c &= ~DOWN; new_labels[i][j] = yloc * TILE_COLS + xloc; edgesTile[yloc][xloc] = c; } for (int k = 0; ;++k) { //1. backup #pragma unroll for (int i = 0; i < TPB_Y; ++i) #pragma unroll for (int j = 0; j < TPB_X; ++j) { int yloc = threadIdx.y + CTA_SIZE_Y * i; int xloc = threadIdx.x + CTA_SIZE_X * j; old_labels[i][j] = new_labels[i][j]; labelsTile[yloc][xloc] = new_labels[i][j]; } __syncthreads(); //2. compare local arrays #pragma unroll for (int i = 0; i < TPB_Y; ++i) #pragma unroll for (int j = 0; j < TPB_X; ++j) { int yloc = threadIdx.y + CTA_SIZE_Y * i; int xloc = threadIdx.x + CTA_SIZE_X * j; component c = edgesTile[yloc][xloc]; int label = new_labels[i][j]; if (c & UP) label = ::min(label, labelsTile[yloc - 1][xloc]); if (c & DOWN) label = ::min(label, labelsTile[yloc + 1][xloc]); if (c & LEFT) label = ::min(label, labelsTile[yloc][xloc - 1]); if (c & RIGHT) label = ::min(label, labelsTile[yloc][xloc + 1]); new_labels[i][j] = label; } __syncthreads(); //3. determine: Is any value changed? int changed = 0; #pragma unroll for (int i = 0; i < TPB_Y; ++i) #pragma unroll for (int j = 0; j < TPB_X; ++j) { if (new_labels[i][j] < old_labels[i][j]) { changed = 1; Emulation::smem::atomicMin(&labelsTile[0][0] + old_labels[i][j], new_labels[i][j]); } } changed = Emulation::syncthreadsOr(changed); if (!changed) break; //4. Compact paths const int *labels = &labelsTile[0][0]; #pragma unroll for (int i = 0; i < TPB_Y; ++i) #pragma unroll for (int j = 0; j < TPB_X; ++j) { int label = new_labels[i][j]; while( labels[label] < label ) label = labels[label]; new_labels[i][j] = label; } __syncthreads(); } #pragma unroll for (int i = 0; i < TPB_Y; ++i) #pragma unroll for (int j = 0; j < TPB_X; ++j) { int label = new_labels[i][j]; int yloc = label / TILE_COLS; int xloc = label - yloc * TILE_COLS; xloc += blockIdx.x * TILE_COLS; yloc += blockIdx.y * TILE_ROWS; label = yloc * edges.cols + xloc; // do it for x too. if (y + CTA_SIZE_Y * i < comps.rows) comps(y + CTA_SIZE_Y * i, x + CTA_SIZE_X * j) = label; } } __device__ __forceinline__ int root(const PtrStepSzi& comps, int label) { while(1) { int y = label / comps.cols; int x = label - y * comps.cols; int parent = comps(y, x); if (label == parent) break; label = parent; } return label; } __device__ __forceinline__ void isConnected(PtrStepSzi& comps, int l1, int l2, bool& changed) { int r1 = root(comps, l1); int r2 = root(comps, l2); if (r1 == r2) return; int mi = ::min(r1, r2); int ma = ::max(r1, r2); int y = ma / comps.cols; int x = ma - y * comps.cols; atomicMin(&comps.ptr(y)[x], mi); changed = true; } __global__ void crossMerge(const int tilesNumY, const int tilesNumX, int tileSizeY, int tileSizeX, const PtrStepSzb edges, PtrStepSzi comps, const int yIncomplete, int xIncomplete) { int tid = threadIdx.y * blockDim.x + threadIdx.x; int stride = blockDim.y * blockDim.x; int ybegin = blockIdx.y * (tilesNumY * tileSizeY); int yend = ybegin + tilesNumY * tileSizeY; if (blockIdx.y == gridDim.y - 1) { yend -= yIncomplete * tileSizeY; yend -= tileSizeY; tileSizeY = (edges.rows % tileSizeY); yend += tileSizeY; } int xbegin = blockIdx.x * tilesNumX * tileSizeX; int xend = xbegin + tilesNumX * tileSizeX; if (blockIdx.x == gridDim.x - 1) { if (xIncomplete) yend = ybegin; xend -= xIncomplete * tileSizeX; xend -= tileSizeX; tileSizeX = (edges.cols % tileSizeX); xend += tileSizeX; } if (blockIdx.y == (gridDim.y - 1) && yIncomplete) { xend = xbegin; } int tasksV = (tilesNumX - 1) * (yend - ybegin); int tasksH = (tilesNumY - 1) * (xend - xbegin); int total = tasksH + tasksV; bool changed; do { changed = false; for (int taskIdx = tid; taskIdx < total; taskIdx += stride) { if (taskIdx < tasksH) { int indexH = taskIdx; int row = indexH / (xend - xbegin); int col = indexH - row * (xend - xbegin); int y = ybegin + (row + 1) * tileSizeY; int x = xbegin + col; component e = edges( x, y); if (e & UP) { int lc = comps(y,x); int lu = comps(y - 1, x); isConnected(comps, lc, lu, changed); } } else { int indexV = taskIdx - tasksH; int col = indexV / (yend - ybegin); int row = indexV - col * (yend - ybegin); int x = xbegin + (col + 1) * tileSizeX; int y = ybegin + row; component e = edges(x, y); if (e & LEFT) { int lc = comps(y, x); int ll = comps(y, x - 1); isConnected(comps, lc, ll, changed); } } } } while (Emulation::syncthreadsOr(changed)); } __global__ void flatten(const PtrStepSzb edges, PtrStepSzi comps) { int x = threadIdx.x + blockIdx.x * blockDim.x; int y = threadIdx.y + blockIdx.y * blockDim.y; if( x < comps.cols && y < comps.rows) comps(y, x) = root(comps, comps(y, x)); } enum {CC_NO_COMPACT = 0, CC_COMPACT_LABELS = 1}; void labelComponents(const PtrStepSzb& edges, PtrStepSzi comps, int flags, cudaStream_t stream) { (void) flags; dim3 block(CTA_SIZE_X, CTA_SIZE_Y); dim3 grid(divUp(edges.cols, TILE_COLS), divUp(edges.rows, TILE_ROWS)); lableTiles<<>>(edges, comps); cudaSafeCall( cudaGetLastError() ); int tileSizeX = TILE_COLS, tileSizeY = TILE_ROWS; while (grid.x > 1 || grid.y > 1) { dim3 mergeGrid((int)ceilf(grid.x / 2.f), (int)ceilf(grid.y / 2.f)); dim3 mergeBlock(STA_SIZE_MERGE_X, STA_SIZE_MERGE_Y); // debug log // std::cout << "merging: " << grid.y << " x " << grid.x << " ---> " << mergeGrid.y << " x " << mergeGrid.x << " for tiles: " << tileSizeY << " x " << tileSizeX << std::endl; crossMerge<<>>(2, 2, tileSizeY, tileSizeX, edges, comps, (int)ceilf(grid.y / 2.f) - grid.y / 2, (int)ceilf(grid.x / 2.f) - grid.x / 2); tileSizeX <<= 1; tileSizeY <<= 1; grid = mergeGrid; cudaSafeCall( cudaGetLastError() ); } grid.x = divUp(edges.cols, block.x); grid.y = divUp(edges.rows, block.y); flatten<<>>(edges, comps); cudaSafeCall( cudaGetLastError() ); if (stream == 0) cudaSafeCall( cudaDeviceSynchronize() ); } } } } } #endif /* CUDA_DISABLER */