diff --git a/modules/ocl/src/brute_force_matcher.cpp b/modules/ocl/src/brute_force_matcher.cpp index e8f28b778..9c4a217f4 100644 --- a/modules/ocl/src/brute_force_matcher.cpp +++ b/modules/ocl/src/brute_force_matcher.cpp @@ -64,11 +64,19 @@ namespace cv static const int OPT_SIZE = 100; +static const char * T_ARR [] = { + "uchar", + "char", + "ushort", + "short", + "int", + "float -D T_FLOAT", + "double"}; + template < int BLOCK_SIZE, int MAX_DESC_LEN/*, typename Mask*/ > void matchUnrolledCached(const oclMat &query, const oclMat &train, const oclMat &/*mask*/, const oclMat &trainIdx, const oclMat &distance, int distType) { - assert(query.type() == CV_32F); cv::ocl::Context *ctx = query.clCxt; size_t globalSize[] = {(query.rows + BLOCK_SIZE - 1) / BLOCK_SIZE * BLOCK_SIZE, BLOCK_SIZE, 1}; size_t localSize[] = {BLOCK_SIZE, BLOCK_SIZE, 1}; @@ -78,7 +86,9 @@ void matchUnrolledCached(const oclMat &query, const oclMat &train, const oclMat vector< pair > args; char opt [OPT_SIZE] = ""; - sprintf(opt, "-D DIST_TYPE=%d -D BLOCK_SIZE=%d -D MAX_DESC_LEN=%d", distType, block_size, m_size); + sprintf(opt, + "-D T=%s -D DIST_TYPE=%d -D BLOCK_SIZE=%d -D MAX_DESC_LEN=%d", + T_ARR[query.depth()], distType, block_size, m_size); if(globalSize[0] != 0) { @@ -96,7 +106,7 @@ void matchUnrolledCached(const oclMat &query, const oclMat &train, const oclMat std::string kernelName = "BruteForceMatch_UnrollMatch"; - openCLExecuteKernel(ctx, &brute_force_match, kernelName, globalSize, localSize, args, -1, query.depth(), opt); + openCLExecuteKernel(ctx, &brute_force_match, kernelName, globalSize, localSize, args, -1, -1, opt); } } @@ -110,7 +120,6 @@ template < int BLOCK_SIZE/*, typename Mask*/ > void match(const oclMat &query, const oclMat &train, const oclMat &/*mask*/, const oclMat &trainIdx, const oclMat &distance, int distType) { - assert(query.type() == CV_32F); cv::ocl::Context *ctx = query.clCxt; size_t globalSize[] = {(query.rows + BLOCK_SIZE - 1) / BLOCK_SIZE * BLOCK_SIZE, BLOCK_SIZE, 1}; size_t localSize[] = {BLOCK_SIZE, BLOCK_SIZE, 1}; @@ -119,8 +128,9 @@ void match(const oclMat &query, const oclMat &train, const oclMat &/*mask*/, vector< pair > args; char opt [OPT_SIZE] = ""; - sprintf(opt, "-D DIST_TYPE=%d -D BLOCK_SIZE=%d", distType, block_size); - + sprintf(opt, + "-D T=%s -D DIST_TYPE=%d -D BLOCK_SIZE=%d", + T_ARR[query.depth()], distType, block_size); if(globalSize[0] != 0) { args.push_back( make_pair( sizeof(cl_mem), (void *)&query.data )); @@ -137,7 +147,7 @@ void match(const oclMat &query, const oclMat &train, const oclMat &/*mask*/, std::string kernelName = "BruteForceMatch_Match"; - openCLExecuteKernel(ctx, &brute_force_match, kernelName, globalSize, localSize, args, -1, query.depth(), opt); + openCLExecuteKernel(ctx, &brute_force_match, kernelName, globalSize, localSize, args, -1, -1, opt); } } @@ -152,7 +162,6 @@ template < int BLOCK_SIZE, int MAX_DESC_LEN/*, typename Mask*/ > void matchUnrolledCached(const oclMat &query, const oclMat &train, float maxDistance, const oclMat &/*mask*/, const oclMat &trainIdx, const oclMat &distance, const oclMat &nMatches, int distType) { - assert(query.type() == CV_32F); cv::ocl::Context *ctx = query.clCxt; size_t globalSize[] = {(train.rows + BLOCK_SIZE - 1) / BLOCK_SIZE * BLOCK_SIZE, (query.rows + BLOCK_SIZE - 1) / BLOCK_SIZE * BLOCK_SIZE, 1}; size_t localSize[] = {BLOCK_SIZE, BLOCK_SIZE, 1}; @@ -162,7 +171,9 @@ void matchUnrolledCached(const oclMat &query, const oclMat &train, float maxDist vector< pair > args; char opt [OPT_SIZE] = ""; - sprintf(opt, "-D DIST_TYPE=%d -D BLOCK_SIZE=%d -D MAX_DESC_LEN=%d", distType, block_size, m_size); + sprintf(opt, + "-D T=%s -D DIST_TYPE=%d -D BLOCK_SIZE=%d -D MAX_DESC_LEN=%d", + T_ARR[query.depth()], distType, block_size, m_size); if(globalSize[0] != 0) { @@ -184,7 +195,7 @@ void matchUnrolledCached(const oclMat &query, const oclMat &train, float maxDist std::string kernelName = "BruteForceMatch_RadiusUnrollMatch"; - openCLExecuteKernel(ctx, &brute_force_match, kernelName, globalSize, localSize, args, -1, query.depth(), opt); + openCLExecuteKernel(ctx, &brute_force_match, kernelName, globalSize, localSize, args, -1, -1, opt); } } @@ -193,7 +204,6 @@ template < int BLOCK_SIZE/*, typename Mask*/ > void radius_match(const oclMat &query, const oclMat &train, float maxDistance, const oclMat &/*mask*/, const oclMat &trainIdx, const oclMat &distance, const oclMat &nMatches, int distType) { - assert(query.type() == CV_32F); cv::ocl::Context *ctx = query.clCxt; size_t globalSize[] = {(train.rows + BLOCK_SIZE - 1) / BLOCK_SIZE * BLOCK_SIZE, (query.rows + BLOCK_SIZE - 1) / BLOCK_SIZE * BLOCK_SIZE, 1}; size_t localSize[] = {BLOCK_SIZE, BLOCK_SIZE, 1}; @@ -202,7 +212,9 @@ void radius_match(const oclMat &query, const oclMat &train, float maxDistance, c vector< pair > args; char opt [OPT_SIZE] = ""; - sprintf(opt, "-D DIST_TYPE=%d -D BLOCK_SIZE=%d", distType, block_size); + sprintf(opt, + "-D T=%s -D DIST_TYPE=%d -D BLOCK_SIZE=%d", + T_ARR[query.depth()], distType, block_size); if(globalSize[0] != 0) { @@ -224,7 +236,7 @@ void radius_match(const oclMat &query, const oclMat &train, float maxDistance, c std::string kernelName = "BruteForceMatch_RadiusMatch"; - openCLExecuteKernel(ctx, &brute_force_match, kernelName, globalSize, localSize, args, -1, query.depth(), opt); + openCLExecuteKernel(ctx, &brute_force_match, kernelName, globalSize, localSize, args, -1, -1, opt); } } @@ -300,7 +312,9 @@ void knn_matchUnrolledCached(const oclMat &query, const oclMat &train, const ocl vector< pair > args; char opt [OPT_SIZE] = ""; - sprintf(opt, "-D DIST_TYPE=%d -D BLOCK_SIZE=%d -D MAX_DESC_LEN=%d", distType, block_size, m_size); + sprintf(opt, + "-D T=%s -D DIST_TYPE=%d -D BLOCK_SIZE=%d -D MAX_DESC_LEN=%d", + T_ARR[query.depth()], distType, block_size, m_size); if(globalSize[0] != 0) { @@ -318,7 +332,7 @@ void knn_matchUnrolledCached(const oclMat &query, const oclMat &train, const ocl std::string kernelName = "BruteForceMatch_knnUnrollMatch"; - openCLExecuteKernel(ctx, &brute_force_match, kernelName, globalSize, localSize, args, -1, query.depth(), opt); + openCLExecuteKernel(ctx, &brute_force_match, kernelName, globalSize, localSize, args, -1, -1, opt); } } @@ -334,7 +348,9 @@ void knn_match(const oclMat &query, const oclMat &train, const oclMat &/*mask*/, vector< pair > args; char opt [OPT_SIZE] = ""; - sprintf(opt, "-D DIST_TYPE=%d -D BLOCK_SIZE=%d", distType, block_size); + sprintf(opt, + "-D T=%s -D DIST_TYPE=%d -D BLOCK_SIZE=%d", + T_ARR[query.depth()], distType, block_size); if(globalSize[0] != 0) { @@ -352,7 +368,7 @@ void knn_match(const oclMat &query, const oclMat &train, const oclMat &/*mask*/, std::string kernelName = "BruteForceMatch_knnMatch"; - openCLExecuteKernel(ctx, &brute_force_match, kernelName, globalSize, localSize, args, -1, query.depth(), opt); + openCLExecuteKernel(ctx, &brute_force_match, kernelName, globalSize, localSize, args, -1, -1, opt); } } @@ -368,7 +384,10 @@ void calcDistanceUnrolled(const oclMat &query, const oclMat &train, const oclMat vector< pair > args; char opt [OPT_SIZE] = ""; - sprintf(opt, "-D DIST_TYPE=%d", distType); + sprintf(opt, + "-D T=%s -D DIST_TYPE=%d -D BLOCK_SIZE=%d -D MAX_DESC_LEN=%d", + T_ARR[query.depth()], distType, block_size, m_size); + if(globalSize[0] != 0) { args.push_back( make_pair( sizeof(cl_mem), (void *)&query.data )); @@ -386,7 +405,7 @@ void calcDistanceUnrolled(const oclMat &query, const oclMat &train, const oclMat std::string kernelName = "BruteForceMatch_calcDistanceUnrolled"; - openCLExecuteKernel(ctx, &brute_force_match, kernelName, globalSize, localSize, args, -1, query.depth(), opt); + openCLExecuteKernel(ctx, &brute_force_match, kernelName, globalSize, localSize, args, -1, -1, opt); } } @@ -401,7 +420,10 @@ void calcDistance(const oclMat &query, const oclMat &train, const oclMat &/*mask vector< pair > args; char opt [OPT_SIZE] = ""; - sprintf(opt, "-D DIST_TYPE=%d", distType); + sprintf(opt, + "-D T=%s -D DIST_TYPE=%d -D BLOCK_SIZE=%d", + T_ARR[query.depth()], distType, block_size); + if(globalSize[0] != 0) { args.push_back( make_pair( sizeof(cl_mem), (void *)&query.data )); @@ -418,7 +440,7 @@ void calcDistance(const oclMat &query, const oclMat &train, const oclMat &/*mask std::string kernelName = "BruteForceMatch_calcDistance"; - openCLExecuteKernel(ctx, &brute_force_match, kernelName, globalSize, localSize, args, -1, query.depth(), opt); + openCLExecuteKernel(ctx, &brute_force_match, kernelName, globalSize, localSize, args, -1, -1, opt); } } @@ -480,7 +502,7 @@ void findKnnMatch(int k, const oclMat &trainIdx, const oclMat &distance, const o //args.push_back( make_pair( sizeof(cl_int), (void *)&train.cols )); //args.push_back( make_pair( sizeof(cl_int), (void *)&query.step )); - openCLExecuteKernel(ctx, &brute_force_match, kernelName, globalSize, localSize, args, trainIdx.depth(), -1); + openCLExecuteKernel(ctx, &brute_force_match, kernelName, globalSize, localSize, args, -1, -1); } } @@ -540,17 +562,6 @@ void cv::ocl::BruteForceMatcher_OCL_base::matchSingle(const oclMat &query, const if (query.empty() || train.empty()) return; - // match1 doesn't support signed char type, match2 only support float, hamming support uchar, ushort and int - int callType = query.depth(); - if (callType != 5) - CV_Error(CV_UNSUPPORTED_FORMAT_ERR, "BruteForceMatch OpenCL only support float type query!\n"); - - if ((distType == 0 && callType == 1 ) || (distType == 1 && callType != 5) || (distType == 2 && (callType != 0 - || callType != 2 || callType != 4))) - { - CV_Error(CV_UNSUPPORTED_DEPTH_ERR, "BruteForceMatch OpenCL only support float type query!\n"); - } - CV_Assert(query.channels() == 1 && query.depth() < CV_64F); CV_Assert(train.cols == query.cols && train.type() == query.type()); @@ -605,7 +616,7 @@ void cv::ocl::BruteForceMatcher_OCL_base::matchConvert(const Mat &trainIdx, cons void cv::ocl::BruteForceMatcher_OCL_base::match(const oclMat &query, const oclMat &train, vector &matches, const oclMat &mask) { - assert(mask.empty()); // mask is not supported at the moment + assert(mask.empty()); // mask is not supported at the moment oclMat trainIdx, distance; matchSingle(query, train, trainIdx, distance, mask); matchDownload(trainIdx, distance, matches); @@ -661,26 +672,14 @@ void cv::ocl::BruteForceMatcher_OCL_base::matchCollection(const oclMat &query, c if (query.empty() || trainCollection.empty()) return; - // match1 doesn't support signed char type, match2 only support float, hamming support uchar, ushort and int - int callType = query.depth(); - if (callType != 5) - CV_Error(CV_UNSUPPORTED_FORMAT_ERR, "BruteForceMatch OpenCL only support float type query!\n"); - - if ((distType == 0 && callType == 1 ) || (distType == 1 && callType != 5) || (distType == 2 && (callType != 0 - || callType != 2 || callType != 4))) - { - CV_Error(CV_UNSUPPORTED_DEPTH_ERR, "BruteForceMatch OpenCL only support float type query!\n"); - } - CV_Assert(query.channels() == 1 && query.depth() < CV_64F); - - const int nQuery = query.rows; + + const int nQuery = query.rows; ensureSizeIsEnough(1, nQuery, CV_32S, trainIdx); ensureSizeIsEnough(1, nQuery, CV_32S, imgIdx); ensureSizeIsEnough(1, nQuery, CV_32F, distance); - matchDispatcher(query, (const oclMat *)trainCollection.ptr(), trainCollection.cols, masks, trainIdx, imgIdx, distance, distType); return; @@ -752,18 +751,6 @@ void cv::ocl::BruteForceMatcher_OCL_base::knnMatchSingle(const oclMat &query, co if (query.empty() || train.empty()) return; - // match1 doesn't support signed char type, match2 only support float, hamming support uchar, ushort and int - int callType = query.depth(); - - if (callType != 5) - CV_Error(CV_UNSUPPORTED_FORMAT_ERR, "BruteForceMatch OpenCL only support float type query!\n"); - - if ((distType == 0 && callType == 1 ) || (distType == 1 && callType != 5) || (distType == 2 && (callType != 0 - || callType != 2 || callType != 4))) - { - CV_Error(CV_UNSUPPORTED_DEPTH_ERR, "BruteForceMatch OpenCL only support float type query!\n"); - } - CV_Assert(query.channels() == 1 && query.depth() < CV_64F); CV_Assert(train.type() == query.type() && train.cols == query.cols); @@ -860,26 +847,7 @@ void cv::ocl::BruteForceMatcher_OCL_base::knnMatch2Collection(const oclMat &quer typedef void (*caller_t)(const oclMat & query, const oclMat & trains, const oclMat & masks, const oclMat & trainIdx, const oclMat & imgIdx, const oclMat & distance); -#if 0 - static const caller_t callers[3][6] = - { - { - ocl_match2L1_gpu, 0/*match2L1_gpu*/, - ocl_match2L1_gpu, ocl_match2L1_gpu, - ocl_match2L1_gpu, ocl_match2L1_gpu - }, - { - 0/*match2L2_gpu*/, 0/*match2L2_gpu*/, - 0/*match2L2_gpu*/, 0/*match2L2_gpu*/, - 0/*match2L2_gpu*/, ocl_match2L2_gpu - }, - { - ocl_match2Hamming_gpu, 0/*match2Hamming_gpu*/, - ocl_match2Hamming_gpu, 0/*match2Hamming_gpu*/, - ocl_match2Hamming_gpu, 0/*match2Hamming_gpu*/ - } - }; -#endif + CV_Assert(query.channels() == 1 && query.depth() < CV_64F); const int nQuery = query.rows; @@ -1025,23 +993,11 @@ void cv::ocl::BruteForceMatcher_OCL_base::knnMatch(const oclMat &query, vector< // radiusMatchSingle void cv::ocl::BruteForceMatcher_OCL_base::radiusMatchSingle(const oclMat &query, const oclMat &train, - oclMat &trainIdx, oclMat &distance, oclMat &nMatches, float maxDistance, const oclMat &mask) + oclMat &trainIdx, oclMat &distance, oclMat &nMatches, float maxDistance, const oclMat &mask) { if (query.empty() || train.empty()) return; - // match1 doesn't support signed char type, match2 only support float, hamming support uchar, ushort and int - int callType = query.depth(); - - if (callType != 5) - CV_Error(CV_UNSUPPORTED_FORMAT_ERR, "BruteForceMatch OpenCL only support float type query!\n"); - - if ((distType == 0 && callType == 1 ) || (distType == 1 && callType != 5) || (distType == 2 && (callType != 0 - || callType != 2 || callType != 4))) - { - CV_Error(CV_UNSUPPORTED_DEPTH_ERR, "BruteForceMatch OpenCL only support float type query!\n"); - } - const int nQuery = query.rows; const int nTrain = train.rows; diff --git a/modules/ocl/src/opencl/brute_force_match.cl b/modules/ocl/src/opencl/brute_force_match.cl index 7446c779b..8dcb9d207 100644 --- a/modules/ocl/src/opencl/brute_force_match.cl +++ b/modules/ocl/src/opencl/brute_force_match.cl @@ -47,6 +47,10 @@ #pragma OPENCL EXTENSION cl_khr_global_int32_base_atomics:enable #define MAX_FLOAT 3.40282e+038f +#ifndef T +#define T float +#endif + #ifndef BLOCK_SIZE #define BLOCK_SIZE 16 #endif @@ -54,68 +58,85 @@ #define MAX_DESC_LEN 64 #endif -int bit1Count(float x) -{ - int c = 0; - int ix = (int)x; - for (int i = 0 ; i < 32 ; i++) - { - c += ix & 0x1; - ix >>= 1; - } - return (float)c; -} - #ifndef DIST_TYPE #define DIST_TYPE 0 #endif -#if (DIST_TYPE == 0) -#define DIST(x, y) fabs((x) - (y)) -#elif (DIST_TYPE == 1) -#define DIST(x, y) (((x) - (y)) * ((x) - (y))) -#elif (DIST_TYPE == 2) -#define DIST(x, y) bit1Count((uint)(x) ^ (uint)(y)) -#endif - - -float reduce_block(__local float *s_query, - __local float *s_train, - int lidx, - int lidy - ) +//http://graphics.stanford.edu/~seander/bithacks.html#CountBitsSetParallel +int bit1Count(int v) { - float result = 0; - #pragma unroll - for (int j = 0 ; j < BLOCK_SIZE ; j++) - { - result += DIST(s_query[lidy * BLOCK_SIZE + j], s_train[j * BLOCK_SIZE + lidx]); - } - return result; + v = v - ((v >> 1) & 0x55555555); // reuse input as temporary + v = (v & 0x33333333) + ((v >> 2) & 0x33333333); // temp + return ((v + (v >> 4) & 0xF0F0F0F) * 0x1010101) >> 24; // count } -float reduce_multi_block(__local float *s_query, - __local float *s_train, - int block_index, - int lidx, - int lidy - ) +// dirty fix for non-template support +#if (DIST_TYPE == 0) // L1Dist +# ifdef T_FLOAT +# define DIST(x, y) fabs((x) - (y)) + typedef float value_type; + typedef float result_type; +# else +# define DIST(x, y) abs((x) - (y)) + typedef int value_type; + typedef int result_type; +# endif +#define DIST_RES(x) (x) +#elif (DIST_TYPE == 1) // L2Dist +#define DIST(x, y) (((x) - (y)) * ((x) - (y))) +typedef float value_type; +typedef float result_type; +#define DIST_RES(x) sqrt(x) +#elif (DIST_TYPE == 2) // Hamming +#define DIST(x, y) bit1Count( (x) ^ (y) ) +typedef int value_type; +typedef int result_type; +#define DIST_RES(x) (x) +#endif + +result_type reduce_block( + __local value_type *s_query, + __local value_type *s_train, + int lidx, + int lidy + ) { - float result = 0; + result_type result = 0; #pragma unroll for (int j = 0 ; j < BLOCK_SIZE ; j++) { - result += DIST(s_query[lidy * MAX_DESC_LEN + block_index * BLOCK_SIZE + j], s_train[j * BLOCK_SIZE + lidx]); + result += DIST( + s_query[lidy * BLOCK_SIZE + j], + s_train[j * BLOCK_SIZE + lidx]); } - return result; + return DIST_RES(result); +} + +result_type reduce_multi_block( + __local value_type *s_query, + __local value_type *s_train, + int block_index, + int lidx, + int lidy + ) +{ + result_type result = 0; + #pragma unroll + for (int j = 0 ; j < BLOCK_SIZE ; j++) + { + result += DIST( + s_query[lidy * MAX_DESC_LEN + block_index * BLOCK_SIZE + j], + s_train[j * BLOCK_SIZE + lidx]); + } + return DIST_RES(result); } /* 2dim launch, global size: dim0 is (query rows + BLOCK_SIZE - 1) / BLOCK_SIZE * BLOCK_SIZE, dim1 is BLOCK_SIZE local size: dim0 is BLOCK_SIZE, dim1 is BLOCK_SIZE. */ -__kernel void BruteForceMatch_UnrollMatch_D5( - __global float *query, - __global float *train, +__kernel void BruteForceMatch_UnrollMatch( + __global T *query, + __global T *train, //__global float *mask, __global int *bestTrainIdx, __global float *bestDistance, @@ -127,13 +148,12 @@ __kernel void BruteForceMatch_UnrollMatch_D5( int step ) { - const int lidx = get_local_id(0); const int lidy = get_local_id(1); const int groupidx = get_group_id(0); - __local float *s_query = sharebuffer; - __local float *s_train = sharebuffer + BLOCK_SIZE * MAX_DESC_LEN; + __local value_type *s_query = (__local value_type *)sharebuffer; + __local value_type *s_train = (__local value_type *)sharebuffer + BLOCK_SIZE * MAX_DESC_LEN; int queryIdx = groupidx * BLOCK_SIZE + lidy; // load the query into local memory. @@ -151,7 +171,7 @@ __kernel void BruteForceMatch_UnrollMatch_D5( volatile int imgIdx = 0; for (int t = 0, endt = (train_rows + BLOCK_SIZE - 1) / BLOCK_SIZE; t < endt; t++) { - float result = 0; + result_type result = 0; #pragma unroll for (int i = 0 ; i < MAX_DESC_LEN / BLOCK_SIZE ; i++) { @@ -207,9 +227,9 @@ __kernel void BruteForceMatch_UnrollMatch_D5( } } -__kernel void BruteForceMatch_Match_D5( - __global float *query, - __global float *train, +__kernel void BruteForceMatch_Match( + __global T *query, + __global T *train, //__global float *mask, __global int *bestTrainIdx, __global float *bestDistance, @@ -230,14 +250,13 @@ __kernel void BruteForceMatch_Match_D5( float myBestDistance = MAX_FLOAT; int myBestTrainIdx = -1; - __local float *s_query = sharebuffer; - __local float *s_train = sharebuffer + BLOCK_SIZE * BLOCK_SIZE; + __local value_type *s_query = (__local value_type *)sharebuffer; + __local value_type *s_train = (__local value_type *)sharebuffer + BLOCK_SIZE * BLOCK_SIZE; // loop for (int t = 0 ; t < (train_rows + BLOCK_SIZE - 1) / BLOCK_SIZE ; t++) { - //Dist dist; - float result = 0; + result_type result = 0; for (int i = 0 ; i < (query_cols + BLOCK_SIZE - 1) / BLOCK_SIZE ; i++) { const int loadx = lidx + i * BLOCK_SIZE; @@ -299,9 +318,9 @@ __kernel void BruteForceMatch_Match_D5( } //radius_unrollmatch -__kernel void BruteForceMatch_RadiusUnrollMatch_D5( - __global float *query, - __global float *train, +__kernel void BruteForceMatch_RadiusUnrollMatch( + __global T *query, + __global T *train, float maxDistance, //__global float *mask, __global int *bestTrainIdx, @@ -325,10 +344,10 @@ __kernel void BruteForceMatch_RadiusUnrollMatch_D5( const int queryIdx = groupidy * BLOCK_SIZE + lidy; const int trainIdx = groupidx * BLOCK_SIZE + lidx; - __local float *s_query = sharebuffer; - __local float *s_train = sharebuffer + BLOCK_SIZE * BLOCK_SIZE; + __local value_type *s_query = (__local value_type *)sharebuffer; + __local value_type *s_train = (__local value_type *)sharebuffer + BLOCK_SIZE * BLOCK_SIZE; - float result = 0; + result_type result = 0; for (int i = 0 ; i < MAX_DESC_LEN / BLOCK_SIZE ; ++i) { //load a BLOCK_SIZE * BLOCK_SIZE block into local train. @@ -345,7 +364,8 @@ __kernel void BruteForceMatch_RadiusUnrollMatch_D5( barrier(CLK_LOCAL_MEM_FENCE); } - if (queryIdx < query_rows && trainIdx < train_rows && result < maxDistance/* && mask(queryIdx, trainIdx)*/) + if (queryIdx < query_rows && trainIdx < train_rows && + convert_float(result) < maxDistance/* && mask(queryIdx, trainIdx)*/) { unsigned int ind = atom_inc(nMatches + queryIdx/*, (unsigned int) -1*/); @@ -359,9 +379,9 @@ __kernel void BruteForceMatch_RadiusUnrollMatch_D5( } //radius_match -__kernel void BruteForceMatch_RadiusMatch_D5( - __global float *query, - __global float *train, +__kernel void BruteForceMatch_RadiusMatch( + __global T *query, + __global T *train, float maxDistance, //__global float *mask, __global int *bestTrainIdx, @@ -385,10 +405,10 @@ __kernel void BruteForceMatch_RadiusMatch_D5( const int queryIdx = groupidy * BLOCK_SIZE + lidy; const int trainIdx = groupidx * BLOCK_SIZE + lidx; - __local float *s_query = sharebuffer; - __local float *s_train = sharebuffer + BLOCK_SIZE * BLOCK_SIZE; + __local value_type *s_query = (__local value_type *)sharebuffer; + __local value_type *s_train = (__local value_type *)sharebuffer + BLOCK_SIZE * BLOCK_SIZE; - float result = 0; + result_type result = 0; for (int i = 0 ; i < (query_cols + BLOCK_SIZE - 1) / BLOCK_SIZE ; ++i) { //load a BLOCK_SIZE * BLOCK_SIZE block into local train. @@ -405,7 +425,8 @@ __kernel void BruteForceMatch_RadiusMatch_D5( barrier(CLK_LOCAL_MEM_FENCE); } - if (queryIdx < query_rows && trainIdx < train_rows && result < maxDistance/* && mask(queryIdx, trainIdx)*/) + if (queryIdx < query_rows && trainIdx < train_rows && + convert_float(result) < maxDistance/* && mask(queryIdx, trainIdx)*/) { unsigned int ind = atom_inc(nMatches + queryIdx); @@ -419,9 +440,9 @@ __kernel void BruteForceMatch_RadiusMatch_D5( } -__kernel void BruteForceMatch_knnUnrollMatch_D5( - __global float *query, - __global float *train, +__kernel void BruteForceMatch_knnUnrollMatch( + __global T *query, + __global T *train, //__global float *mask, __global int2 *bestTrainIdx, __global float2 *bestDistance, @@ -438,8 +459,8 @@ __kernel void BruteForceMatch_knnUnrollMatch_D5( const int groupidx = get_group_id(0); const int queryIdx = groupidx * BLOCK_SIZE + lidy; - local float *s_query = sharebuffer; - local float *s_train = sharebuffer + BLOCK_SIZE * MAX_DESC_LEN; + __local value_type *s_query = (__local value_type *)sharebuffer; + __local value_type *s_train = (__local value_type *)sharebuffer + BLOCK_SIZE * MAX_DESC_LEN; // load the query into local memory. for (int i = 0 ; i < MAX_DESC_LEN / BLOCK_SIZE; i ++) @@ -457,10 +478,9 @@ __kernel void BruteForceMatch_knnUnrollMatch_D5( volatile int imgIdx = 0; for (int t = 0 ; t < (train_rows + BLOCK_SIZE - 1) / BLOCK_SIZE ; t++) { - float result = 0; + result_type result = 0; for (int i = 0 ; i < MAX_DESC_LEN / BLOCK_SIZE ; i++) { - const int loadX = lidx + i * BLOCK_SIZE; //load a BLOCK_SIZE * BLOCK_SIZE block into local train. const int loadx = lidx + i * BLOCK_SIZE; s_train[lidx * BLOCK_SIZE + lidy] = loadx < train_cols ? train[min(t * BLOCK_SIZE + lidy, train_rows - 1) * (step / sizeof(float)) + loadx] : 0; @@ -494,8 +514,8 @@ __kernel void BruteForceMatch_knnUnrollMatch_D5( barrier(CLK_LOCAL_MEM_FENCE); - local float *s_distance = (local float *)sharebuffer; - local int *s_trainIdx = (local int *)(sharebuffer + BLOCK_SIZE * BLOCK_SIZE); + __local float *s_distance = (local float *)sharebuffer; + __local int *s_trainIdx = (local int *)(sharebuffer + BLOCK_SIZE * BLOCK_SIZE); // find BestMatch s_distance += lidy * BLOCK_SIZE; @@ -565,9 +585,9 @@ __kernel void BruteForceMatch_knnUnrollMatch_D5( } } -__kernel void BruteForceMatch_knnMatch_D5( - __global float *query, - __global float *train, +__kernel void BruteForceMatch_knnMatch( + __global T *query, + __global T *train, //__global float *mask, __global int2 *bestTrainIdx, __global float2 *bestDistance, @@ -584,8 +604,8 @@ __kernel void BruteForceMatch_knnMatch_D5( const int groupidx = get_group_id(0); const int queryIdx = groupidx * BLOCK_SIZE + lidy; - local float *s_query = sharebuffer; - local float *s_train = sharebuffer + BLOCK_SIZE * BLOCK_SIZE; + __local value_type *s_query = (__local value_type *)sharebuffer; + __local value_type *s_train = (__local value_type *)sharebuffer + BLOCK_SIZE * BLOCK_SIZE; float myBestDistance1 = MAX_FLOAT; float myBestDistance2 = MAX_FLOAT; @@ -595,7 +615,7 @@ __kernel void BruteForceMatch_knnMatch_D5( //loop for (int t = 0 ; t < (train_rows + BLOCK_SIZE - 1) / BLOCK_SIZE ; t++) { - float result = 0.0f; + result_type result = 0.0f; for (int i = 0 ; i < (query_cols + BLOCK_SIZE -1) / BLOCK_SIZE ; i++) { const int loadx = lidx + i * BLOCK_SIZE; @@ -708,9 +728,9 @@ __kernel void BruteForceMatch_knnMatch_D5( } } -kernel void BruteForceMatch_calcDistanceUnrolled_D5( - __global float *query, - __global float *train, +kernel void BruteForceMatch_calcDistanceUnrolled( + __global T *query, + __global T *train, //__global float *mask, __global float *allDist, __local float *sharebuffer, @@ -723,9 +743,9 @@ kernel void BruteForceMatch_calcDistanceUnrolled_D5( /* Todo */ } -kernel void BruteForceMatch_calcDistance_D5( - __global float *query, - __global float *train, +kernel void BruteForceMatch_calcDistance( + __global T *query, + __global T *train, //__global float *mask, __global float *allDist, __local float *sharebuffer, @@ -738,7 +758,7 @@ kernel void BruteForceMatch_calcDistance_D5( /* Todo */ } -kernel void BruteForceMatch_findBestMatch_D5( +kernel void BruteForceMatch_findBestMatch( __global float *allDist, __global int *bestTrainIdx, __global float *bestDistance, @@ -746,4 +766,4 @@ kernel void BruteForceMatch_findBestMatch_D5( ) { /* Todo */ -} \ No newline at end of file +} diff --git a/modules/ocl/test/test_brute_force_matcher.cpp b/modules/ocl/test/test_brute_force_matcher.cpp index d658c32d1..59a81e825 100644 --- a/modules/ocl/test/test_brute_force_matcher.cpp +++ b/modules/ocl/test/test_brute_force_matcher.cpp @@ -158,11 +158,7 @@ namespace TEST_P(BruteForceMatcher, RadiusMatch_Single) { - float radius; - if(distType == cv::ocl::BruteForceMatcher_OCL_base::L2Dist) - radius = 1.f / countFactor / countFactor; - else - radius = 1.f / countFactor; + float radius = 1.f / countFactor; cv::ocl::BruteForceMatcher_OCL_base matcher(distType); @@ -191,8 +187,20 @@ namespace INSTANTIATE_TEST_CASE_P(OCL_Features2D, BruteForceMatcher, testing::Combine( - testing::Values(DistType(cv::ocl::BruteForceMatcher_OCL_base::L1Dist), DistType(cv::ocl::BruteForceMatcher_OCL_base::L2Dist)), - testing::Values(DescriptorSize(57), DescriptorSize(64), DescriptorSize(83), DescriptorSize(128), DescriptorSize(179), DescriptorSize(256), DescriptorSize(304)))); - + testing::Values( + DistType(cv::ocl::BruteForceMatcher_OCL_base::L1Dist), + DistType(cv::ocl::BruteForceMatcher_OCL_base::L2Dist)/*, + DistType(cv::ocl::BruteForceMatcher_OCL_base::HammingDist)*/ + ), + testing::Values( + DescriptorSize(57), + DescriptorSize(64), + DescriptorSize(83), + DescriptorSize(128), + DescriptorSize(179), + DescriptorSize(256), + DescriptorSize(304)) + ) + ); } // namespace #endif