Allow more query/train types for ocl::bfmatcher
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1db20099a9
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@ -77,7 +77,6 @@ template < int BLOCK_SIZE, int MAX_DESC_LEN/*, typename Mask*/ >
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void matchUnrolledCached(const oclMat &query, const oclMat &train, const oclMat &/*mask*/,
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const oclMat &trainIdx, const oclMat &distance, int distType)
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{
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assert(query.type() == CV_32F);
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cv::ocl::Context *ctx = query.clCxt;
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size_t globalSize[] = {(query.rows + BLOCK_SIZE - 1) / BLOCK_SIZE * BLOCK_SIZE, BLOCK_SIZE, 1};
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size_t localSize[] = {BLOCK_SIZE, BLOCK_SIZE, 1};
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@ -121,7 +120,6 @@ template < int BLOCK_SIZE/*, typename Mask*/ >
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void match(const oclMat &query, const oclMat &train, const oclMat &/*mask*/,
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const oclMat &trainIdx, const oclMat &distance, int distType)
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{
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assert(query.type() == CV_32F);
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cv::ocl::Context *ctx = query.clCxt;
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size_t globalSize[] = {(query.rows + BLOCK_SIZE - 1) / BLOCK_SIZE * BLOCK_SIZE, BLOCK_SIZE, 1};
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size_t localSize[] = {BLOCK_SIZE, BLOCK_SIZE, 1};
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@ -164,7 +162,6 @@ template < int BLOCK_SIZE, int MAX_DESC_LEN/*, typename Mask*/ >
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void matchUnrolledCached(const oclMat &query, const oclMat &train, float maxDistance, const oclMat &/*mask*/,
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const oclMat &trainIdx, const oclMat &distance, const oclMat &nMatches, int distType)
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{
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assert(query.type() == CV_32F);
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cv::ocl::Context *ctx = query.clCxt;
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size_t globalSize[] = {(train.rows + BLOCK_SIZE - 1) / BLOCK_SIZE * BLOCK_SIZE, (query.rows + BLOCK_SIZE - 1) / BLOCK_SIZE * BLOCK_SIZE, 1};
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size_t localSize[] = {BLOCK_SIZE, BLOCK_SIZE, 1};
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@ -207,7 +204,6 @@ template < int BLOCK_SIZE/*, typename Mask*/ >
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void radius_match(const oclMat &query, const oclMat &train, float maxDistance, const oclMat &/*mask*/,
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const oclMat &trainIdx, const oclMat &distance, const oclMat &nMatches, int distType)
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{
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assert(query.type() == CV_32F);
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cv::ocl::Context *ctx = query.clCxt;
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size_t globalSize[] = {(train.rows + BLOCK_SIZE - 1) / BLOCK_SIZE * BLOCK_SIZE, (query.rows + BLOCK_SIZE - 1) / BLOCK_SIZE * BLOCK_SIZE, 1};
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size_t localSize[] = {BLOCK_SIZE, BLOCK_SIZE, 1};
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@ -566,17 +562,6 @@ void cv::ocl::BruteForceMatcher_OCL_base::matchSingle(const oclMat &query, const
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if (query.empty() || train.empty())
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return;
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// match1 doesn't support signed char type, match2 only support float, hamming support uchar, ushort and int
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int callType = query.depth();
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if (callType != 5)
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CV_Error(CV_UNSUPPORTED_FORMAT_ERR, "BruteForceMatch OpenCL only support float type query!\n");
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if ((distType == 0 && callType == 1 ) || (distType == 1 && callType != 5) || (distType == 2 && (callType != 0
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|| callType != 2 || callType != 4)))
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{
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CV_Error(CV_UNSUPPORTED_DEPTH_ERR, "BruteForceMatch OpenCL only support float type query!\n");
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}
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CV_Assert(query.channels() == 1 && query.depth() < CV_64F);
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CV_Assert(train.cols == query.cols && train.type() == query.type());
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@ -687,17 +672,6 @@ void cv::ocl::BruteForceMatcher_OCL_base::matchCollection(const oclMat &query, c
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if (query.empty() || trainCollection.empty())
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return;
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// match1 doesn't support signed char type, match2 only support float, hamming support uchar, ushort and int
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int callType = query.depth();
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if (callType != 5)
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CV_Error(CV_UNSUPPORTED_FORMAT_ERR, "BruteForceMatch OpenCL only support float type query!\n");
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if ((distType == 0 && callType == 1 ) || (distType == 1 && callType != 5) || (distType == 2 && (callType != 0
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|| callType != 2 || callType != 4)))
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{
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CV_Error(CV_UNSUPPORTED_DEPTH_ERR, "BruteForceMatch OpenCL only support float type query!\n");
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}
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CV_Assert(query.channels() == 1 && query.depth() < CV_64F);
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const int nQuery = query.rows;
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@ -706,7 +680,6 @@ void cv::ocl::BruteForceMatcher_OCL_base::matchCollection(const oclMat &query, c
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ensureSizeIsEnough(1, nQuery, CV_32S, imgIdx);
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ensureSizeIsEnough(1, nQuery, CV_32F, distance);
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matchDispatcher(query, (const oclMat *)trainCollection.ptr(), trainCollection.cols, masks, trainIdx, imgIdx, distance, distType);
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return;
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@ -778,18 +751,6 @@ void cv::ocl::BruteForceMatcher_OCL_base::knnMatchSingle(const oclMat &query, co
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if (query.empty() || train.empty())
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return;
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// match1 doesn't support signed char type, match2 only support float, hamming support uchar, ushort and int
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int callType = query.depth();
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if (callType != 5)
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CV_Error(CV_UNSUPPORTED_FORMAT_ERR, "BruteForceMatch OpenCL only support float type query!\n");
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if ((distType == 0 && callType == 1 ) || (distType == 1 && callType != 5) || (distType == 2 && (callType != 0
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|| callType != 2 || callType != 4)))
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{
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CV_Error(CV_UNSUPPORTED_DEPTH_ERR, "BruteForceMatch OpenCL only support float type query!\n");
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}
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CV_Assert(query.channels() == 1 && query.depth() < CV_64F);
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CV_Assert(train.type() == query.type() && train.cols == query.cols);
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@ -886,26 +847,7 @@ void cv::ocl::BruteForceMatcher_OCL_base::knnMatch2Collection(const oclMat &quer
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typedef void (*caller_t)(const oclMat & query, const oclMat & trains, const oclMat & masks,
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const oclMat & trainIdx, const oclMat & imgIdx, const oclMat & distance);
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#if 0
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static const caller_t callers[3][6] =
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{
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{
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ocl_match2L1_gpu<unsigned char>, 0/*match2L1_gpu<signed char>*/,
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ocl_match2L1_gpu<unsigned short>, ocl_match2L1_gpu<short>,
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ocl_match2L1_gpu<int>, ocl_match2L1_gpu<float>
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},
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{
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0/*match2L2_gpu<unsigned char>*/, 0/*match2L2_gpu<signed char>*/,
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0/*match2L2_gpu<unsigned short>*/, 0/*match2L2_gpu<short>*/,
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0/*match2L2_gpu<int>*/, ocl_match2L2_gpu<float>
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},
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{
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ocl_match2Hamming_gpu<unsigned char>, 0/*match2Hamming_gpu<signed char>*/,
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ocl_match2Hamming_gpu<unsigned short>, 0/*match2Hamming_gpu<short>*/,
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ocl_match2Hamming_gpu<int>, 0/*match2Hamming_gpu<float>*/
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}
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};
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#endif
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CV_Assert(query.channels() == 1 && query.depth() < CV_64F);
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const int nQuery = query.rows;
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@ -1051,23 +993,11 @@ void cv::ocl::BruteForceMatcher_OCL_base::knnMatch(const oclMat &query, vector<
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// radiusMatchSingle
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void cv::ocl::BruteForceMatcher_OCL_base::radiusMatchSingle(const oclMat &query, const oclMat &train,
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oclMat &trainIdx, oclMat &distance, oclMat &nMatches, float maxDistance, const oclMat &mask)
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oclMat &trainIdx, oclMat &distance, oclMat &nMatches, float maxDistance, const oclMat &mask)
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{
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if (query.empty() || train.empty())
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return;
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// match1 doesn't support signed char type, match2 only support float, hamming support uchar, ushort and int
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int callType = query.depth();
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if (callType != 5)
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CV_Error(CV_UNSUPPORTED_FORMAT_ERR, "BruteForceMatch OpenCL only support float type query!\n");
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if ((distType == 0 && callType == 1 ) || (distType == 1 && callType != 5) || (distType == 2 && (callType != 0
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|| callType != 2 || callType != 4)))
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{
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CV_Error(CV_UNSUPPORTED_DEPTH_ERR, "BruteForceMatch OpenCL only support float type query!\n");
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}
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const int nQuery = query.rows;
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const int nTrain = train.rows;
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@ -65,11 +65,10 @@
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int bit1Count(int x)
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{
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int c = 0;
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int ix = x;
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for (int i = 0 ; i < 32 ; i++)
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{
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c += ix & 0x1;
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ix >>= 1;
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c += x & 1;
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x >>= 1;
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}
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return c;
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}
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@ -85,14 +84,17 @@ int bit1Count(int x)
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typedef int value_type;
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typedef int result_type;
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# endif
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#define DIST_RES(x) (x)
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#elif (DIST_TYPE == 1) // L2Dist
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#define DIST(x, y) (((x) - (y)) * ((x) - (y)))
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typedef float value_type;
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typedef float result_type;
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#define DIST_RES(x) sqrt(x)
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#elif (DIST_TYPE == 2) // Hamming
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#define DIST(x, y) bit1Count(((x) ^ (y))
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#define DIST(x, y) bit1Count( (x) ^ (y) )
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typedef int value_type;
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typedef int result_type;
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#define DIST_RES(x) (x)
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#endif
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result_type reduce_block(
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@ -107,10 +109,10 @@ result_type reduce_block(
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for (int j = 0 ; j < BLOCK_SIZE ; j++)
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{
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result += DIST(
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s_query[lidy * BLOCK_SIZE + j],
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s_query[lidy * BLOCK_SIZE + j],
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s_train[j * BLOCK_SIZE + lidx]);
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}
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return result;
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return DIST_RES(result);
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}
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result_type reduce_multi_block(
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@ -126,10 +128,10 @@ result_type reduce_multi_block(
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for (int j = 0 ; j < BLOCK_SIZE ; j++)
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{
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result += DIST(
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s_query[lidy * MAX_DESC_LEN + block_index * BLOCK_SIZE + j],
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s_query[lidy * MAX_DESC_LEN + block_index * BLOCK_SIZE + j],
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s_train[j * BLOCK_SIZE + lidx]);
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}
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return result;
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return DIST_RES(result);
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}
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/* 2dim launch, global size: dim0 is (query rows + BLOCK_SIZE - 1) / BLOCK_SIZE * BLOCK_SIZE, dim1 is BLOCK_SIZE
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@ -153,8 +155,8 @@ __kernel void BruteForceMatch_UnrollMatch(
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const int lidy = get_local_id(1);
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const int groupidx = get_group_id(0);
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__local value_type *s_query = sharebuffer;
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__local value_type *s_train = sharebuffer + BLOCK_SIZE * MAX_DESC_LEN;
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__local value_type *s_query = (__local value_type *)sharebuffer;
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__local value_type *s_train = (__local value_type *)sharebuffer + BLOCK_SIZE * MAX_DESC_LEN;
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int queryIdx = groupidx * BLOCK_SIZE + lidy;
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// load the query into local memory.
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@ -251,8 +253,8 @@ __kernel void BruteForceMatch_Match(
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float myBestDistance = MAX_FLOAT;
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int myBestTrainIdx = -1;
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__local value_type *s_query = sharebuffer;
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__local value_type *s_train = sharebuffer + BLOCK_SIZE * BLOCK_SIZE;
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__local value_type *s_query = (__local value_type *)sharebuffer;
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__local value_type *s_train = (__local value_type *)sharebuffer + BLOCK_SIZE * BLOCK_SIZE;
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// loop
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for (int t = 0 ; t < (train_rows + BLOCK_SIZE - 1) / BLOCK_SIZE ; t++)
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@ -345,8 +347,8 @@ __kernel void BruteForceMatch_RadiusUnrollMatch(
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const int queryIdx = groupidy * BLOCK_SIZE + lidy;
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const int trainIdx = groupidx * BLOCK_SIZE + lidx;
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__local value_type *s_query = sharebuffer;
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__local value_type *s_train = sharebuffer + BLOCK_SIZE * BLOCK_SIZE;
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__local value_type *s_query = (__local value_type *)sharebuffer;
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__local value_type *s_train = (__local value_type *)sharebuffer + BLOCK_SIZE * BLOCK_SIZE;
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result_type result = 0;
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for (int i = 0 ; i < MAX_DESC_LEN / BLOCK_SIZE ; ++i)
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@ -365,7 +367,8 @@ __kernel void BruteForceMatch_RadiusUnrollMatch(
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barrier(CLK_LOCAL_MEM_FENCE);
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}
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if (queryIdx < query_rows && trainIdx < train_rows && result < maxDistance/* && mask(queryIdx, trainIdx)*/)
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if (queryIdx < query_rows && trainIdx < train_rows &&
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convert_float(result) < maxDistance/* && mask(queryIdx, trainIdx)*/)
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{
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unsigned int ind = atom_inc(nMatches + queryIdx/*, (unsigned int) -1*/);
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@ -405,8 +408,8 @@ __kernel void BruteForceMatch_RadiusMatch(
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const int queryIdx = groupidy * BLOCK_SIZE + lidy;
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const int trainIdx = groupidx * BLOCK_SIZE + lidx;
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__local value_type *s_query = sharebuffer;
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__local value_type *s_train = sharebuffer + BLOCK_SIZE * BLOCK_SIZE;
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__local value_type *s_query = (__local value_type *)sharebuffer;
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__local value_type *s_train = (__local value_type *)sharebuffer + BLOCK_SIZE * BLOCK_SIZE;
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result_type result = 0;
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for (int i = 0 ; i < (query_cols + BLOCK_SIZE - 1) / BLOCK_SIZE ; ++i)
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@ -425,7 +428,8 @@ __kernel void BruteForceMatch_RadiusMatch(
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barrier(CLK_LOCAL_MEM_FENCE);
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}
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if (queryIdx < query_rows && trainIdx < train_rows && result < maxDistance/* && mask(queryIdx, trainIdx)*/)
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if (queryIdx < query_rows && trainIdx < train_rows &&
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convert_float(result) < maxDistance/* && mask(queryIdx, trainIdx)*/)
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{
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unsigned int ind = atom_inc(nMatches + queryIdx);
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@ -458,8 +462,8 @@ __kernel void BruteForceMatch_knnUnrollMatch(
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const int groupidx = get_group_id(0);
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const int queryIdx = groupidx * BLOCK_SIZE + lidy;
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local value_type *s_query = sharebuffer;
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local value_type *s_train = sharebuffer + BLOCK_SIZE * MAX_DESC_LEN;
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__local value_type *s_query = (__local value_type *)sharebuffer;
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__local value_type *s_train = (__local value_type *)sharebuffer + BLOCK_SIZE * MAX_DESC_LEN;
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// load the query into local memory.
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for (int i = 0 ; i < MAX_DESC_LEN / BLOCK_SIZE; i ++)
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@ -480,7 +484,6 @@ __kernel void BruteForceMatch_knnUnrollMatch(
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result_type result = 0;
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for (int i = 0 ; i < MAX_DESC_LEN / BLOCK_SIZE ; i++)
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{
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const int loadX = lidx + i * BLOCK_SIZE;
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//load a BLOCK_SIZE * BLOCK_SIZE block into local train.
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const int loadx = lidx + i * BLOCK_SIZE;
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s_train[lidx * BLOCK_SIZE + lidy] = loadx < train_cols ? train[min(t * BLOCK_SIZE + lidy, train_rows - 1) * (step / sizeof(float)) + loadx] : 0;
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@ -514,8 +517,8 @@ __kernel void BruteForceMatch_knnUnrollMatch(
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barrier(CLK_LOCAL_MEM_FENCE);
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local float *s_distance = (local float *)sharebuffer;
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local int *s_trainIdx = (local int *)(sharebuffer + BLOCK_SIZE * BLOCK_SIZE);
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__local float *s_distance = (local float *)sharebuffer;
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__local int *s_trainIdx = (local int *)(sharebuffer + BLOCK_SIZE * BLOCK_SIZE);
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// find BestMatch
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s_distance += lidy * BLOCK_SIZE;
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@ -604,8 +607,8 @@ __kernel void BruteForceMatch_knnMatch(
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const int groupidx = get_group_id(0);
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const int queryIdx = groupidx * BLOCK_SIZE + lidy;
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local value_type *s_query = sharebuffer;
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local value_type *s_train = sharebuffer + BLOCK_SIZE * BLOCK_SIZE;
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__local value_type *s_query = (__local value_type *)sharebuffer;
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__local value_type *s_train = (__local value_type *)sharebuffer + BLOCK_SIZE * BLOCK_SIZE;
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float myBestDistance1 = MAX_FLOAT;
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float myBestDistance2 = MAX_FLOAT;
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@ -766,4 +769,4 @@ kernel void BruteForceMatch_findBestMatch(
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)
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{
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/* Todo */
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}
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}
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@ -158,11 +158,7 @@ namespace
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TEST_P(BruteForceMatcher, RadiusMatch_Single)
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{
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float radius;
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if(distType == cv::ocl::BruteForceMatcher_OCL_base::L2Dist)
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radius = 1.f / countFactor / countFactor;
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else
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radius = 1.f / countFactor;
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float radius = 1.f / countFactor;
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cv::ocl::BruteForceMatcher_OCL_base matcher(distType);
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@ -193,8 +189,8 @@ namespace
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testing::Combine(
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testing::Values(
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DistType(cv::ocl::BruteForceMatcher_OCL_base::L1Dist),
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DistType(cv::ocl::BruteForceMatcher_OCL_base::L2Dist),
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DistType(cv::ocl::BruteForceMatcher_OCL_base::HammingDist)
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DistType(cv::ocl::BruteForceMatcher_OCL_base::L2Dist)/*,
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DistType(cv::ocl::BruteForceMatcher_OCL_base::HammingDist)*/
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),
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testing::Values(
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DescriptorSize(57),
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