Chiebot-Mirror
/
opencv
mirror of https://github.com/opencv/opencv.git
8
0
Fork 0
Code Issues Projects Releases Wiki Activity

implement optimized version of gpu::BruteForceMatcher::knnMatch when k == 2

Browse Source
pull/13383/head
Vladislav Vinogradov 13 years ago
parent c92b040c48
commit 6e3a1f7b49
4 changed files with 239 additions and 72 deletions
Whitespace
Show all changes Ignore whitespace when comparing lines Ignore changes in amount of whitespace Ignore changes in whitespace at EOL
Split View
Diff Options
Show Stats Download Patch File Download Diff File
  1. 15
      modules/gpu/src/brute_force_matcher.cpp
  2. 278
      modules/gpu/src/cuda/brute_force_matcher.cu
  3. 2
      modules/gpu/test/test_features2d.cpp
  4. 6
      samples/gpu/performance/tests.cpp

15
modules/gpu/src/brute_force_matcher.cpp
Unescape View File

@ -105,13 +105,13 @@ namespace cv { namespace gpu { namespace bfmatcher
template <typename T>
void knnMatchL1_gpu(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn,
const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, cudaStream_t stream);
const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, bool cc_12, cudaStream_t stream);
template <typename T>
void knnMatchL2_gpu(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn,
const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, cudaStream_t stream);
const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, bool cc_12, cudaStream_t stream);
template <typename T>
void knnMatchHamming_gpu(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn,
const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, cudaStream_t stream);
const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, bool cc_12, cudaStream_t stream);
template <typename T>
void radiusMatchL1_gpu(const DevMem2D& queryDescs, const DevMem2D& trainDescs, float maxDistance,
@ -428,7 +428,7 @@ void cv::gpu::BruteForceMatcher_GPU_base::knnMatch(const GpuMat& queryDescs, con
using namespace cv::gpu::bfmatcher;
typedef void (*match_caller_t)(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn,
const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, cudaStream_t stream);
const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, bool cc_12, cudaStream_t stream);
static const match_caller_t match_callers[3][8] =
{
@ -454,23 +454,28 @@ void cv::gpu::BruteForceMatcher_GPU_base::knnMatch(const GpuMat& queryDescs, con
ensureSizeIsEnough(nQuery, k, CV_32S, trainIdx);
ensureSizeIsEnough(nQuery, k, CV_32F, distance);
if (k != 2)
ensureSizeIsEnough(nQuery, nTrain, CV_32FC1, allDist);
if (stream)
{
stream.enqueueMemSet(trainIdx, Scalar::all(-1));
if (k != 2)
stream.enqueueMemSet(allDist, Scalar::all(numeric_limits<float>::max()));
}
else
{
trainIdx.setTo(Scalar::all(-1));
if (k != 2)
allDist.setTo(Scalar::all(numeric_limits<float>::max()));
}
match_caller_t func = match_callers[distType][queryDescs.depth()];
CV_Assert(func != 0);
func(queryDescs, trainDescs, k, mask, trainIdx, distance, allDist, StreamAccessor::getStream(stream));
bool cc_12 = TargetArchs::builtWith(FEATURE_SET_COMPUTE_12) && DeviceInfo().supports(FEATURE_SET_COMPUTE_12);
func(queryDescs, trainDescs, k, mask, trainIdx, distance, allDist, cc_12, StreamAccessor::getStream(stream));
}
void cv::gpu::BruteForceMatcher_GPU_base::knnMatchDownload(const GpuMat& trainIdx, const GpuMat& distance,

278
modules/gpu/src/cuda/brute_force_matcher.cu
Unescape View File

@ -87,9 +87,8 @@ namespace cv { namespace gpu { namespace bfmatcher
PtrStep curMask;
};
class WithOutMask
struct WithOutMask
{
public:
__device__ __forceinline__ void nextMask() const
{
}
@ -105,18 +104,16 @@ namespace cv { namespace gpu { namespace bfmatcher
template <int BLOCK_DIM_X> struct SumReductor;
template <> struct SumReductor<16>
{
template <typename T> static __device__ void reduce(T* sdiff_row, T& mySum)
template <typename T> static __device__ void reduce(volatile T* sdiff_row, T& mySum)
{
volatile T* smem = sdiff_row;
smem[threadIdx.x] = mySum;
sdiff_row[threadIdx.x] = mySum;
if (threadIdx.x < 8)
{
smem[threadIdx.x] = mySum += smem[threadIdx.x + 8];
smem[threadIdx.x] = mySum += smem[threadIdx.x + 4];
smem[threadIdx.x] = mySum += smem[threadIdx.x + 2];
smem[threadIdx.x] = mySum += smem[threadIdx.x + 1];
sdiff_row[threadIdx.x] = mySum += sdiff_row[threadIdx.x + 8];
sdiff_row[threadIdx.x] = mySum += sdiff_row[threadIdx.x + 4];
sdiff_row[threadIdx.x] = mySum += sdiff_row[threadIdx.x + 2];
sdiff_row[threadIdx.x] = mySum += sdiff_row[threadIdx.x + 1];
}
}
};
@ -435,6 +432,7 @@ namespace cv { namespace gpu { namespace bfmatcher
__device__ __forceinline__ void prepare(const T* queryDescs, int desc_len, U* smem)
{
loadDescsVals<BLOCK_DIM_X, MAX_DESCRIPTORS_LEN>(queryDescs, desc_len, queryVals, smem);
__syncthreads();
}
template <typename Dist>
@ -779,6 +777,173 @@ namespace cv { namespace gpu { namespace bfmatcher
//////////////////////////////////// Knn Match ////////////////////////////////////
///////////////////////////////////////////////////////////////////////////////////
template <int BLOCK_DIM_X, int BLOCK_DIM_Y, typename Dist, typename ReduceDescCalculator, typename T, typename Mask>
__device__ void distanceCalcLoop(const PtrStep_<T>& query, const DevMem2D_<T>& train, const Mask& m, int queryIdx,
typename Dist::ResultType& distMin1, typename Dist::ResultType& distMin2, int& bestTrainIdx1, int& bestTrainIdx2,
typename Dist::ResultType* smem)
{
ReduceDescCalculator reduceDescCalc;
reduceDescCalc.prepare(query.ptr(queryIdx), train.cols, (typename Dist::ValueType*)smem);
typename Dist::ResultType* sdiffRow = smem + BLOCK_DIM_X * threadIdx.y;
for (int trainIdx = threadIdx.y; trainIdx < train.rows; trainIdx += BLOCK_DIM_Y)
{
if (m(queryIdx, trainIdx))
{
Dist dist;
const T* trainRow = train.ptr(trainIdx);
reduceDescCalc.calc(trainRow, train.cols, dist, sdiffRow);
if (threadIdx.x == 0)
{
typename Dist::ResultType val = dist;
if (val < distMin1)
{
distMin1 = val;
bestTrainIdx1 = trainIdx;
}
else if (val < distMin2)
{
distMin2 = val;
bestTrainIdx2 = trainIdx;
}
}
}
}
}
template <int BLOCK_DIM_X, int BLOCK_DIM_Y, typename Dist, typename ReduceDescCalculator, typename T, typename Mask>
__global__ void knnMatch2(const PtrStep_<T> query, const DevMem2D_<T> train, const Mask m, PtrStep_<int2> trainIdx, PtrStep_<float2> distance)
{
typedef typename Dist::ResultType ResultType;
typedef typename Dist::ValueType ValueType;
__shared__ ResultType smem[BLOCK_DIM_X * BLOCK_DIM_Y];
const int queryIdx = blockIdx.x;
ResultType distMin1 = numeric_limits<ResultType>::max();
ResultType distMin2 = numeric_limits<ResultType>::max();
int bestTrainIdx1 = -1;
int bestTrainIdx2 = -1;
distanceCalcLoop<BLOCK_DIM_X, BLOCK_DIM_Y, Dist, ReduceDescCalculator>(query, train, m, queryIdx,
distMin1, distMin2, bestTrainIdx1, bestTrainIdx2, smem);
__syncthreads();
volatile ResultType* sdistMinRow = smem;
volatile int* sbestTrainIdxRow = (int*)(sdistMinRow + 2 * BLOCK_DIM_Y);
if (threadIdx.x == 0)
{
sdistMinRow[threadIdx.y] = distMin1;
sdistMinRow[threadIdx.y + BLOCK_DIM_Y] = distMin2;
sbestTrainIdxRow[threadIdx.y] = bestTrainIdx1;
sbestTrainIdxRow[threadIdx.y + BLOCK_DIM_Y] = bestTrainIdx2;
}
__syncthreads();
if (threadIdx.x == 0 && threadIdx.y == 0)
{
distMin1 = numeric_limits<ResultType>::max();
distMin2 = numeric_limits<ResultType>::max();
bestTrainIdx1 = -1;
bestTrainIdx2 = -1;
#pragma unroll
for (int i = 0; i < BLOCK_DIM_Y; ++i)
{
ResultType val = sdistMinRow[i];
if (val < distMin1)
{
distMin1 = val;
bestTrainIdx1 = sbestTrainIdxRow[i];
}
else if (val < distMin2)
{
distMin2 = val;
bestTrainIdx2 = sbestTrainIdxRow[i];
}
}
#pragma unroll
for (int i = BLOCK_DIM_Y; i < 2 * BLOCK_DIM_Y; ++i)
{
ResultType val = sdistMinRow[i];
if (val < distMin2)
{
distMin2 = val;
bestTrainIdx2 = sbestTrainIdxRow[i];
}
}
trainIdx.ptr(queryIdx)[0] = make_int2(bestTrainIdx1, bestTrainIdx2);
distance.ptr(queryIdx)[0] = make_float2(distMin1, distMin2);
}
}
template <int BLOCK_DIM_X, int BLOCK_DIM_Y, typename Dist, typename T, typename Mask>
void knnMatch2Simple_caller(const DevMem2D_<T>& queryDescs, const DevMem2D_<T>& trainDescs, const Mask& mask,
const DevMem2D_<int2>& trainIdx, const DevMem2D_<float2>& distance, cudaStream_t stream)
{
dim3 grid(queryDescs.rows, 1, 1);
dim3 threads(BLOCK_DIM_X, BLOCK_DIM_Y, 1);
knnMatch2<BLOCK_DIM_X, BLOCK_DIM_Y, Dist, ReduceDescCalculatorSimple<BLOCK_DIM_X, T>, T>
<<<grid, threads, 0, stream>>>(queryDescs, trainDescs, mask, trainIdx, distance);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaDeviceSynchronize() );
}
template <int BLOCK_DIM_X, int BLOCK_DIM_Y, int MAX_DESCRIPTORS_LEN, bool DESC_LEN_EQ_MAX_LEN, typename Dist, typename T, typename Mask>
void knnMatch2Cached_caller(const DevMem2D_<T>& queryDescs, const DevMem2D_<T>& trainDescs, const Mask& mask,
const DevMem2D_<int2>& trainIdx, const DevMem2D_<float2>& distance, cudaStream_t stream)
{
StaticAssert<BLOCK_DIM_X * BLOCK_DIM_Y >= MAX_DESCRIPTORS_LEN>::check(); // block size must be greter than descriptors length
StaticAssert<MAX_DESCRIPTORS_LEN % BLOCK_DIM_X == 0>::check(); // max descriptors length must divide to blockDimX
dim3 grid(queryDescs.rows, 1, 1);
dim3 threads(BLOCK_DIM_X, BLOCK_DIM_Y, 1);
knnMatch2<BLOCK_DIM_X, BLOCK_DIM_Y, Dist, ReduceDescCalculatorCached<BLOCK_DIM_X, MAX_DESCRIPTORS_LEN, DESC_LEN_EQ_MAX_LEN, T, typename Dist::ValueType>, T>
<<<grid, threads, 0, stream>>>(queryDescs, trainDescs, mask, trainIdx, distance);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaDeviceSynchronize() );
}
template <typename Dist, typename T, typename Mask>
void knnMatch2Dispatcher(const DevMem2D_<T>& query, const DevMem2D_<T>& train, const Mask& mask,
const DevMem2D_<int2>& trainIdx, const DevMem2D_<float2>& distance, bool cc_12, cudaStream_t stream)
{
if (query.cols < 64)
knnMatch2Cached_caller<16, 16, 64, false, Dist>(query, train, mask, trainIdx, distance, stream);
else if (query.cols == 64)
knnMatch2Cached_caller<16, 16, 64, true, Dist>(query, train, mask, trainIdx, distance, stream);
else if (query.cols < 128)
knnMatch2Cached_caller<16, 16, 128, false, Dist>(query, train, mask, trainIdx, distance, stream);
else if (query.cols == 128 && cc_12)
knnMatch2Cached_caller<16, 16, 128, true, Dist>(query, train, mask, trainIdx, distance, stream);
else if (query.cols < 256 && cc_12)
knnMatch2Cached_caller<16, 16, 256, false, Dist>(query, train, mask, trainIdx, distance, stream);
else if (query.cols == 256 && cc_12)
knnMatch2Cached_caller<16, 16, 256, true, Dist>(query, train, mask, trainIdx, distance, stream);
else
knnMatch2Simple_caller<16, 16, Dist>(query, train, mask, trainIdx, distance, stream);
}
///////////////////////////////////////////////////////////////////////////////
// Calc distance kernel
@ -1026,77 +1191,74 @@ namespace cv { namespace gpu { namespace bfmatcher
findKnnMatch_caller<256>(knn, trainIdx, distance, allDist, stream);
}
template <typename T>
void knnMatchL1_gpu(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn,
const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, cudaStream_t stream)
template < typename Dist, typename T >
void knnMatchDispatcher(const DevMem2D_<T>& queryDescs, const DevMem2D_<T>& trainDescs, int knn,
const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, bool cc_12, cudaStream_t stream)
{
if (mask.data)
{
calcDistanceDispatcher< L1Dist<T> >((DevMem2D_<T>)queryDescs, (DevMem2D_<T>)trainDescs, SingleMask(mask), allDist, stream);
}
else
if (knn == 2)
{
calcDistanceDispatcher< L1Dist<T> >((DevMem2D_<T>)queryDescs, (DevMem2D_<T>)trainDescs, WithOutMask(), allDist, stream);
knnMatch2Dispatcher<Dist>(queryDescs, trainDescs, SingleMask(mask), (DevMem2D_<int2>)trainIdx, (DevMem2D_<float2>)distance, cc_12, stream);
return;
}
findKnnMatchDispatcher(knn, trainIdx, distance, allDist, stream);
calcDistanceDispatcher<Dist>(queryDescs, trainDescs, SingleMask(mask), allDist, stream);
}
template void knnMatchL1_gpu<uchar >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, cudaStream_t stream);
template void knnMatchL1_gpu<schar >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, cudaStream_t stream);
template void knnMatchL1_gpu<ushort>(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, cudaStream_t stream);
template void knnMatchL1_gpu<short >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, cudaStream_t stream);
template void knnMatchL1_gpu<int >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, cudaStream_t stream);
template void knnMatchL1_gpu<float >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, cudaStream_t stream);
template <typename T>
void knnMatchL2_gpu(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn,
const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, cudaStream_t stream)
else
{
if (mask.data)
if (knn == 2)
{
calcDistanceDispatcher<L2Dist>((DevMem2D_<T>)queryDescs, (DevMem2D_<T>)trainDescs,
SingleMask(mask), allDist, stream);
knnMatch2Dispatcher<Dist>(queryDescs, trainDescs, WithOutMask(), (DevMem2D_<int2>)trainIdx, (DevMem2D_<float2>)distance, cc_12, stream);
return;
}
else
{
calcDistanceDispatcher<L2Dist>((DevMem2D_<T>)queryDescs, (DevMem2D_<T>)trainDescs,
WithOutMask(), allDist, stream);
calcDistanceDispatcher<Dist>(queryDescs, trainDescs, WithOutMask(), allDist, stream);
}
findKnnMatchDispatcher(knn, trainIdx, distance, allDist, stream);
}
template void knnMatchL2_gpu<uchar >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, cudaStream_t stream);
template void knnMatchL2_gpu<schar >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, cudaStream_t stream);
template void knnMatchL2_gpu<ushort>(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, cudaStream_t stream);
template void knnMatchL2_gpu<short >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, cudaStream_t stream);
template void knnMatchL2_gpu<int >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, cudaStream_t stream);
template void knnMatchL2_gpu<float >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, cudaStream_t stream);
template <typename T>
void knnMatchHamming_gpu(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn,
const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, cudaStream_t stream)
{
if (mask.data)
void knnMatchL1_gpu(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn,
const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, bool cc_12, cudaStream_t stream)
{
calcDistanceDispatcher<HammingDist>((DevMem2D_<T>)queryDescs, (DevMem2D_<T>)trainDescs,
SingleMask(mask), allDist, stream);
knnMatchDispatcher< L1Dist<T> >((DevMem2D_<T>)queryDescs, (DevMem2D_<T>)trainDescs, knn, mask, trainIdx, distance, allDist, cc_12, stream);
}
else
template void knnMatchL1_gpu<uchar >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, bool cc_12, cudaStream_t stream);
template void knnMatchL1_gpu<schar >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, bool cc_12, cudaStream_t stream);
template void knnMatchL1_gpu<ushort>(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, bool cc_12, cudaStream_t stream);
template void knnMatchL1_gpu<short >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, bool cc_12, cudaStream_t stream);
template void knnMatchL1_gpu<int >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, bool cc_12, cudaStream_t stream);
template void knnMatchL1_gpu<float >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, bool cc_12, cudaStream_t stream);
template <typename T>
void knnMatchL2_gpu(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn,
const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, bool cc_12, cudaStream_t stream)
{
calcDistanceDispatcher<HammingDist>((DevMem2D_<T>)queryDescs, (DevMem2D_<T>)trainDescs,
WithOutMask(), allDist, stream);
knnMatchDispatcher<L2Dist>((DevMem2D_<T>)queryDescs, (DevMem2D_<T>)trainDescs, knn, mask, trainIdx, distance, allDist, cc_12, stream);
}
findKnnMatchDispatcher(knn, trainIdx, distance, allDist, stream);
template void knnMatchL2_gpu<uchar >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, bool cc_12, cudaStream_t stream);
template void knnMatchL2_gpu<schar >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, bool cc_12, cudaStream_t stream);
template void knnMatchL2_gpu<ushort>(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, bool cc_12, cudaStream_t stream);
template void knnMatchL2_gpu<short >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, bool cc_12, cudaStream_t stream);
template void knnMatchL2_gpu<int >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, bool cc_12, cudaStream_t stream);
template void knnMatchL2_gpu<float >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, bool cc_12, cudaStream_t stream);
template <typename T>
void knnMatchHamming_gpu(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn,
const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, bool cc_12, cudaStream_t stream)
{
knnMatchDispatcher<HammingDist>((DevMem2D_<T>)queryDescs, (DevMem2D_<T>)trainDescs, knn, mask, trainIdx, distance, allDist, cc_12, stream);
}
template void knnMatchHamming_gpu<uchar >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, cudaStream_t stream);
template void knnMatchHamming_gpu<schar >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, cudaStream_t stream);
template void knnMatchHamming_gpu<ushort>(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, cudaStream_t stream);
template void knnMatchHamming_gpu<short >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, cudaStream_t stream);
template void knnMatchHamming_gpu<int >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, cudaStream_t stream);
template void knnMatchHamming_gpu<uchar >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, bool cc_12, cudaStream_t stream);
template void knnMatchHamming_gpu<schar >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, bool cc_12, cudaStream_t stream);
template void knnMatchHamming_gpu<ushort>(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, bool cc_12, cudaStream_t stream);
template void knnMatchHamming_gpu<short >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, bool cc_12, cudaStream_t stream);
template void knnMatchHamming_gpu<int >(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn, const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Df& distance, const DevMem2Df& allDist, bool cc_12, cudaStream_t stream);
///////////////////////////////////////////////////////////////////////////////////
/////////////////////////////////// Radius Match //////////////////////////////////

2
modules/gpu/test/test_features2d.cpp
Unescape View File

@ -320,7 +320,7 @@ TEST_P(BruteForceMatcher, KnnMatch)
PRINT_PARAM(distStr);
PRINT_PARAM(dim);
const int knn = 3;
const int knn = 2;
std::vector< std::vector<cv::DMatch> > matches;

6
samples/gpu/performance/tests.cpp
Unescape View File

@ -286,7 +286,7 @@ TEST(BruteForceMatcher)
{
// Init CPU matcher
int desc_len = 128;
int desc_len = 64;
BruteForceMatcher< L2<float> > matcher;
@ -328,7 +328,7 @@ TEST(BruteForceMatcher)
d_matcher.knnMatch(d_query, d_train, d_matches, knn);
GPU_OFF;
SUBTEST << "radiusMatch";
/*SUBTEST << "radiusMatch";
float max_distance = 3.8f;
CPU_ON;
@ -337,7 +337,7 @@ TEST(BruteForceMatcher)
GPU_ON;
d_matcher.radiusMatch(d_query, d_train, d_matches, max_distance);
GPU_OFF;
GPU_OFF;*/
}

Write Preview
Loading…
Cancel
Save