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提交 6b6b1c9c 编写于 作者: P Peng Xiao
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Allow more query/train types for ocl::bfmatcher

上级 1db20099
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Showing with 34 addition and 105 deletion
modules/ocl/src/brute_force_matcher.cpp
浏览文件 @ 6b6b1c9c
......@@ -77,7 +77,6 @@ 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};
......@@ -121,7 +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};
......@@ -164,7 +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};
......@@ -207,7 +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};
......@@ -566,17 +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());
......@@ -687,17 +672,6 @@ 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;
......@@ -706,7 +680,6 @@ void cv::ocl::BruteForceMatcher_OCL_base::matchCollection(const oclMat &query, c
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;
......@@ -778,18 +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);
......@@ -886,26 +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<unsigned char>, 0/*match2L1_gpu<signed char>*/,
ocl_match2L1_gpu<unsigned short>, ocl_match2L1_gpu<short>,
ocl_match2L1_gpu<int>, ocl_match2L1_gpu<float>
},
{
0/*match2L2_gpu<unsigned char>*/, 0/*match2L2_gpu<signed char>*/,
0/*match2L2_gpu<unsigned short>*/, 0/*match2L2_gpu<short>*/,
0/*match2L2_gpu<int>*/, ocl_match2L2_gpu<float>
},
{
ocl_match2Hamming_gpu<unsigned char>, 0/*match2Hamming_gpu<signed char>*/,
ocl_match2Hamming_gpu<unsigned short>, 0/*match2Hamming_gpu<short>*/,
ocl_match2Hamming_gpu<int>, 0/*match2Hamming_gpu<float>*/
}
};
#endif
CV_Assert(query.channels() == 1 && query.depth() < CV_64F);
const int nQuery = query.rows;
......@@ -1051,23 +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;
......
modules/ocl/src/opencl/brute_force_match.cl
浏览文件 @ 6b6b1c9c
......@@ -65,11 +65,10 @@
int bit1Count(int x)
{
int c = 0;
int ix = x;
for (int i = 0 ; i < 32 ; i++)
{
c += ix & 0x1;
ix >>= 1;
c += x & 1;
x >>= 1;
}
return c;
}
......@@ -85,14 +84,17 @@ int bit1Count(int x)
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))
#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(
......@@ -107,10 +109,10 @@ result_type reduce_block(
for (int j = 0 ; j < BLOCK_SIZE ; j++)
{
result += DIST(
s_query[lidy * BLOCK_SIZE + j],
s_query[lidy * BLOCK_SIZE + j],
s_train[j * BLOCK_SIZE + lidx]);
}
return result;
return DIST_RES(result);
}
result_type reduce_multi_block(
......@@ -126,10 +128,10 @@ result_type reduce_multi_block(
for (int j = 0 ; j < BLOCK_SIZE ; j++)
{
result += DIST(
s_query[lidy * MAX_DESC_LEN + block_index * BLOCK_SIZE + j],
s_query[lidy * MAX_DESC_LEN + block_index * BLOCK_SIZE + j],
s_train[j * BLOCK_SIZE + lidx]);
}
return result;
return DIST_RES(result);
}
/* 2dim launch, global size: dim0 is (query rows + BLOCK_SIZE - 1) / BLOCK_SIZE * BLOCK_SIZE, dim1 is BLOCK_SIZE
......@@ -153,8 +155,8 @@ __kernel void BruteForceMatch_UnrollMatch(
const int lidy = get_local_id(1);
const int groupidx = get_group_id(0);
__local value_type *s_query = sharebuffer;
__local value_type *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.
......@@ -251,8 +253,8 @@ __kernel void BruteForceMatch_Match(
float myBestDistance = MAX_FLOAT;
int myBestTrainIdx = -1;
__local value_type *s_query = sharebuffer;
__local value_type *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++)
......@@ -345,8 +347,8 @@ __kernel void BruteForceMatch_RadiusUnrollMatch(
const int queryIdx = groupidy * BLOCK_SIZE + lidy;
const int trainIdx = groupidx * BLOCK_SIZE + lidx;
__local value_type *s_query = sharebuffer;
__local value_type *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;
result_type result = 0;
for (int i = 0 ; i < MAX_DESC_LEN / BLOCK_SIZE ; ++i)
......@@ -365,7 +367,8 @@ __kernel void BruteForceMatch_RadiusUnrollMatch(
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*/);
......@@ -405,8 +408,8 @@ __kernel void BruteForceMatch_RadiusMatch(
const int queryIdx = groupidy * BLOCK_SIZE + lidy;
const int trainIdx = groupidx * BLOCK_SIZE + lidx;
__local value_type *s_query = sharebuffer;
__local value_type *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;
result_type result = 0;
for (int i = 0 ; i < (query_cols + BLOCK_SIZE - 1) / BLOCK_SIZE ; ++i)
......@@ -425,7 +428,8 @@ __kernel void BruteForceMatch_RadiusMatch(
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);
......@@ -458,8 +462,8 @@ __kernel void BruteForceMatch_knnUnrollMatch(
const int groupidx = get_group_id(0);
const int queryIdx = groupidx * BLOCK_SIZE + lidy;
local value_type *s_query = sharebuffer;
local value_type *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 ++)
......@@ -480,7 +484,6 @@ __kernel void BruteForceMatch_knnUnrollMatch(
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;
......@@ -514,8 +517,8 @@ __kernel void BruteForceMatch_knnUnrollMatch(
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;
......@@ -604,8 +607,8 @@ __kernel void BruteForceMatch_knnMatch(
const int groupidx = get_group_id(0);
const int queryIdx = groupidx * BLOCK_SIZE + lidy;
local value_type *s_query = sharebuffer;
local value_type *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;
......@@ -766,4 +769,4 @@ kernel void BruteForceMatch_findBestMatch(
)
{
/* Todo */
}
\ No newline at end of file
}
modules/ocl/test/test_brute_force_matcher.cpp
浏览文件 @ 6b6b1c9c
......@@ -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);
......@@ -193,8 +189,8 @@ namespace
testing::Combine(
testing::Values(
DistType(cv::ocl::BruteForceMatcher_OCL_base::L1Dist),
DistType(cv::ocl::BruteForceMatcher_OCL_base::L2Dist),
DistType(cv::ocl::BruteForceMatcher_OCL_base::HammingDist)
DistType(cv::ocl::BruteForceMatcher_OCL_base::L2Dist)/*,
DistType(cv::ocl::BruteForceMatcher_OCL_base::HammingDist)*/
),
testing::Values(
DescriptorSize(57),
......
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