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Commit deac5d97 authored by Vladislav Vinogradov's avatar Vladislav Vinogradov
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fixed errors in gpu on old video cards (SURF_GPU, BruteForceMatcher_GPU, min/max, setTo, convertTo) 

added assertion after all kernels calls
parent 5f175f95
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Showing with 442 additions and 298 deletions
modules/gpu/include/opencv2/gpu/gpu.hpp
View file @ deac5d97
......@@ -435,8 +435,8 @@ namespace cv
void enqueueCopy(const GpuMat& src, GpuMat& dst);
void enqueueMemSet(const GpuMat& src, Scalar val);
void enqueueMemSet(const GpuMat& src, Scalar val, const GpuMat& mask);
void enqueueMemSet(GpuMat& src, Scalar val);
void enqueueMemSet(GpuMat& src, Scalar val, const GpuMat& mask);
// converts matrix type, ex from float to uchar depending on type
void enqueueConvert(const GpuMat& src, GpuMat& dst, int type, double a = 1, double b = 0);
......
modules/gpu/src/brute_force_matcher.cpp
View file @ deac5d97
......@@ -76,18 +76,22 @@ namespace cv { namespace gpu { namespace bfmatcher
{
template <typename T>
void matchSingleL1_gpu(const DevMem2D& queryDescs, const DevMem2D& trainDescs,
const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance);
const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance,
bool cc_12);
template <typename T>
void matchSingleL2_gpu(const DevMem2D& queryDescs, const DevMem2D& trainDescs,
const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance);
const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance,
bool cc_12);
template <typename T>
void matchCollectionL1_gpu(const DevMem2D& queryDescs, const DevMem2D& trainCollection,
const DevMem2D_<PtrStep>& maskCollection, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx,
const DevMem2Df& distance);
const DevMem2Df& distance,
bool cc_12);
template <typename T>
void matchCollectionL2_gpu(const DevMem2D& queryDescs, const DevMem2D& trainCollection,
const DevMem2D_<PtrStep>& maskCollection, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx,
const DevMem2Df& distance);
const DevMem2Df& distance,
bool cc_12);
template <typename T>
void knnMatchL1_gpu(const DevMem2D& queryDescs, const DevMem2D& trainDescs, int knn,
......@@ -160,17 +164,20 @@ void cv::gpu::BruteForceMatcher_GPU_base::matchSingle(const GpuMat& queryDescs,
using namespace cv::gpu::bfmatcher;
typedef void (*match_caller_t)(const DevMem2D& queryDescs, const DevMem2D& trainDescs,
const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance);
const DevMem2D& mask, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx, const DevMem2Df& distance,
bool cc_12);
static const match_caller_t match_callers[2][8] =
{
{
matchSingleL1_gpu<unsigned char>, matchSingleL1_gpu<char>, matchSingleL1_gpu<unsigned short>,
matchSingleL1_gpu<short>, matchSingleL1_gpu<int>, matchSingleL1_gpu<float>, 0, 0
matchSingleL1_gpu<unsigned char>, matchSingleL1_gpu<signed char>,
matchSingleL1_gpu<unsigned short>, matchSingleL1_gpu<short>,
matchSingleL1_gpu<int>, matchSingleL1_gpu<float>, 0, 0
},
{
matchSingleL2_gpu<unsigned char>, matchSingleL2_gpu<char>, matchSingleL2_gpu<unsigned short>,
matchSingleL2_gpu<short>, matchSingleL2_gpu<int>, matchSingleL2_gpu<float>, 0, 0
matchSingleL2_gpu<unsigned char>, matchSingleL2_gpu<signed char>,
matchSingleL2_gpu<unsigned short>, matchSingleL2_gpu<short>,
matchSingleL2_gpu<int>, matchSingleL2_gpu<float>, 0, 0
}
};
......@@ -185,9 +192,11 @@ void cv::gpu::BruteForceMatcher_GPU_base::matchSingle(const GpuMat& queryDescs,
match_caller_t func = match_callers[distType][queryDescs.depth()];
CV_Assert(func != 0);
bool cc_12 = TargetArchs::builtWith(COMPUTE_12) && DeviceInfo().supports(COMPUTE_12);
// For single train there is no need to save imgIdx, so we just save imgIdx to trainIdx.
// trainIdx store after imgIdx, so we doesn't lose it value.
func(queryDescs, trainDescs, mask, trainIdx, trainIdx, distance);
func(queryDescs, trainDescs, mask, trainIdx, trainIdx, distance, cc_12);
}
void cv::gpu::BruteForceMatcher_GPU_base::matchDownload(const GpuMat& trainIdx, const GpuMat& distance,
......@@ -284,17 +293,17 @@ void cv::gpu::BruteForceMatcher_GPU_base::matchCollection(const GpuMat& queryDes
typedef void (*match_caller_t)(const DevMem2D& queryDescs, const DevMem2D& trainCollection,
const DevMem2D_<PtrStep>& maskCollection, const DevMem2Di& trainIdx, const DevMem2Di& imgIdx,
const DevMem2Df& distance);
const DevMem2Df& distance, bool cc_12);
static const match_caller_t match_callers[2][8] =
{
{
matchCollectionL1_gpu<unsigned char>, matchCollectionL1_gpu<char>,
matchCollectionL1_gpu<unsigned char>, matchCollectionL1_gpu<signed char>,
matchCollectionL1_gpu<unsigned short>, matchCollectionL1_gpu<short>,
matchCollectionL1_gpu<int>, matchCollectionL1_gpu<float>, 0, 0
},
{
matchCollectionL2_gpu<unsigned char>, matchCollectionL2_gpu<char>,
matchCollectionL2_gpu<unsigned char>, matchCollectionL2_gpu<signed char>,
matchCollectionL2_gpu<unsigned short>, matchCollectionL2_gpu<short>,
matchCollectionL2_gpu<int>, matchCollectionL2_gpu<float>, 0, 0
}
......@@ -311,7 +320,9 @@ void cv::gpu::BruteForceMatcher_GPU_base::matchCollection(const GpuMat& queryDes
match_caller_t func = match_callers[distType][queryDescs.depth()];
CV_Assert(func != 0);
func(queryDescs, trainCollection, maskCollection, trainIdx, imgIdx, distance);
bool cc_12 = TargetArchs::builtWith(COMPUTE_12) && DeviceInfo().supports(COMPUTE_12);
func(queryDescs, trainCollection, maskCollection, trainIdx, imgIdx, distance, cc_12);
}
void cv::gpu::BruteForceMatcher_GPU_base::matchDownload(const GpuMat& trainIdx, const GpuMat& imgIdx,
......@@ -383,11 +394,11 @@ void cv::gpu::BruteForceMatcher_GPU_base::knnMatch(const GpuMat& queryDescs, con
static const match_caller_t match_callers[2][8] =
{
{
knnMatchL1_gpu<unsigned char>, knnMatchL1_gpu<char>, knnMatchL1_gpu<unsigned short>,
knnMatchL1_gpu<unsigned char>, knnMatchL1_gpu<signed char>, knnMatchL1_gpu<unsigned short>,
knnMatchL1_gpu<short>, knnMatchL1_gpu<int>, knnMatchL1_gpu<float>, 0, 0
},
{
knnMatchL2_gpu<unsigned char>, knnMatchL2_gpu<char>, knnMatchL2_gpu<unsigned short>,
knnMatchL2_gpu<unsigned char>, knnMatchL2_gpu<signed char>, knnMatchL2_gpu<unsigned short>,
knnMatchL2_gpu<short>, knnMatchL2_gpu<int>, knnMatchL2_gpu<float>, 0, 0
}
};
......@@ -522,11 +533,11 @@ void cv::gpu::BruteForceMatcher_GPU_base::radiusMatch(const GpuMat& queryDescs,
static const radiusMatch_caller_t radiusMatch_callers[2][8] =
{
{
radiusMatchL1_gpu<unsigned char>, radiusMatchL1_gpu<char>, radiusMatchL1_gpu<unsigned short>,
radiusMatchL1_gpu<unsigned char>, radiusMatchL1_gpu<signed char>, radiusMatchL1_gpu<unsigned short>,
radiusMatchL1_gpu<short>, radiusMatchL1_gpu<int>, radiusMatchL1_gpu<float>, 0, 0
},
{
radiusMatchL2_gpu<unsigned char>, radiusMatchL2_gpu<char>, radiusMatchL2_gpu<unsigned short>,
radiusMatchL2_gpu<unsigned char>, radiusMatchL2_gpu<signed char>, radiusMatchL2_gpu<unsigned short>,
radiusMatchL2_gpu<short>, radiusMatchL2_gpu<int>, radiusMatchL2_gpu<float>, 0, 0
}
};
......
modules/gpu/src/cuda/brute_force_matcher.cu
View file @ deac5d97
This diff is collapsed.
modules/gpu/src/cuda/color.cu
View file @ deac5d97
......@@ -43,6 +43,7 @@
#include "internal_shared.hpp"
#include "opencv2/gpu/device/saturate_cast.hpp"
#include "opencv2/gpu/device/vecmath.hpp"
#include "opencv2/gpu/device/limits_gpu.hpp"
using namespace cv::gpu;
using namespace cv::gpu::device;
......@@ -51,13 +52,9 @@ using namespace cv::gpu::device;
#define CV_DESCALE(x, n) (((x) + (1 << ((n)-1))) >> (n))
#endif
#ifndef FLT_EPSILON
#define FLT_EPSILON 1.192092896e-07F
#endif
namespace cv { namespace gpu { namespace color
{
template<typename T> struct ColorChannel {};
template<typename T> struct ColorChannel;
template<> struct ColorChannel<uchar>
{
typedef float worktype_f;
......@@ -133,6 +130,7 @@ namespace cv { namespace gpu { namespace color
RGB2RGB<SRCCN, DSTCN, T><<<grid, threads, 0, stream>>>(src.data, src.step,
dst.data, dst.step, src.rows, src.cols, bidx);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaThreadSynchronize() );
......@@ -276,6 +274,7 @@ namespace cv { namespace gpu { namespace color
RGB5x52RGB<GREEN_BITS, DSTCN><<<grid, threads, 0, stream>>>(src.data, src.step,
dst.data, dst.step, src.rows, src.cols, bidx);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaThreadSynchronize() );
......@@ -304,6 +303,7 @@ namespace cv { namespace gpu { namespace color
RGB2RGB5x5<SRCCN, GREEN_BITS><<<grid, threads, 0, stream>>>(src.data, src.step,
dst.data, dst.step, src.rows, src.cols, bidx);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaThreadSynchronize() );
......@@ -385,6 +385,7 @@ namespace cv { namespace gpu { namespace color
Gray2RGB<DSTCN, T><<<grid, threads, 0, stream>>>(src.data, src.step,
dst.data, dst.step, src.rows, src.cols);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaThreadSynchronize() );
......@@ -425,6 +426,7 @@ namespace cv { namespace gpu { namespace color
Gray2RGB5x5<GREEN_BITS><<<grid, threads, 0, stream>>>(src.data, src.step,
dst.data, dst.step, src.rows, src.cols);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaThreadSynchronize() );
......@@ -533,6 +535,7 @@ namespace cv { namespace gpu { namespace color
RGB2Gray<SRCCN, T><<<grid, threads, 0, stream>>>(src.data, src.step,
dst.data, dst.step, src.rows, src.cols, bidx);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaThreadSynchronize() );
......@@ -573,6 +576,7 @@ namespace cv { namespace gpu { namespace color
RGB5x52Gray<GREEN_BITS><<<grid, threads, 0, stream>>>(src.data, src.step,
dst.data, dst.step, src.rows, src.cols);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaThreadSynchronize() );
......@@ -698,6 +702,7 @@ namespace cv { namespace gpu { namespace color
RGB2YCrCb<SRCCN, DSTCN, T><<<grid, threads, 0, stream>>>(src.data, src.step,
dst.data, dst.step, src.rows, src.cols, bidx);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaThreadSynchronize() );
......@@ -756,6 +761,7 @@ namespace cv { namespace gpu { namespace color
YCrCb2RGB<SRCCN, DSTCN, T><<<grid, threads, 0, stream>>>(src.data, src.step,
dst.data, dst.step, src.rows, src.cols, bidx);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaThreadSynchronize() );
......@@ -902,6 +908,7 @@ namespace cv { namespace gpu { namespace color
RGB2XYZ<SRCCN, DSTCN, T><<<grid, threads, 0, stream>>>(src.data, src.step,
dst.data, dst.step, src.rows, src.cols);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaThreadSynchronize() );
......@@ -960,6 +967,7 @@ namespace cv { namespace gpu { namespace color
XYZ2RGB<SRCCN, DSTCN, T><<<grid, threads, 0, stream>>>(src.data, src.step,
dst.data, dst.step, src.rows, src.cols);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaThreadSynchronize() );
......@@ -1063,8 +1071,8 @@ namespace cv { namespace gpu { namespace color
vmin = fmin(vmin, b);
diff = v - vmin;
s = diff / (float)(fabs(v) + FLT_EPSILON);
diff = (float)(60. / (diff + FLT_EPSILON));
s = diff / (float)(fabs(v) + numeric_limits_gpu<float>::epsilon());
diff = (float)(60. / (diff + numeric_limits_gpu<float>::epsilon()));
if (v == r)
h = (g - b) * diff;
......@@ -1199,6 +1207,8 @@ namespace cv { namespace gpu { namespace color
RGB2HSV<SRCCN, DSTCN, 255, T><<<grid, threads, 0, stream>>>(src.data, src.step,
dst.data, dst.step, src.rows, src.cols, bidx);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaThreadSynchronize() );
}
......@@ -1281,6 +1291,8 @@ namespace cv { namespace gpu { namespace color
HSV2RGB<SRCCN, DSTCN, 255, T><<<grid, threads, 0, stream>>>(src.data, src.step,
dst.data, dst.step, src.rows, src.cols, bidx);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaThreadSynchronize() );
}
......@@ -1342,7 +1354,7 @@ namespace cv { namespace gpu { namespace color
diff = vmax - vmin;
l = (vmax + vmin) * 0.5f;
if (diff > FLT_EPSILON)
if (diff > numeric_limits_gpu<float>::epsilon())
{
s = l < 0.5f ? diff / (vmax + vmin) : diff / (2.0f - vmax - vmin);
diff = 60.f / diff;
......@@ -1550,6 +1562,8 @@ namespace cv { namespace gpu { namespace color
HLS2RGB<SRCCN, DSTCN, 255, T><<<grid, threads, 0, stream>>>(src.data, src.step,
dst.data, dst.step, src.rows, src.cols, bidx);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaThreadSynchronize() );
}
......
modules/gpu/src/cuda/element_operations.cu
View file @ deac5d97
This diff is collapsed.
modules/gpu/src/cuda/filters.cu
View file @ deac5d97
......@@ -44,6 +44,7 @@
#include "opencv2/gpu/device/saturate_cast.hpp"
#include "opencv2/gpu/device/vecmath.hpp"
#include "opencv2/gpu/device/limits_gpu.hpp"
#include "opencv2/gpu/device/border_interpolate.hpp"
#include "safe_call.hpp"
#include "internal_shared.hpp"
......@@ -51,192 +52,6 @@
using namespace cv::gpu;
using namespace cv::gpu::device;
namespace cv
{
namespace gpu
{
namespace device
{
struct BrdReflect101
{
explicit BrdReflect101(int len): last(len - 1) {}
__device__ int idx_low(int i) const
{
return abs(i);
}
__device__ int idx_high(int i) const
{
return last - abs(last - i);
}
__device__ int idx(int i) const
{
return abs(idx_high(i));
}
bool is_range_safe(int mini, int maxi) const
{
return -last <= mini && maxi <= 2 * last;
}
int last;
};
template <typename D>
struct BrdRowReflect101: BrdReflect101
{
explicit BrdRowReflect101(int len): BrdReflect101(len) {}
template <typename T>
__device__ D at_low(int i, const T* data) const
{
return saturate_cast<D>(data[idx_low(i)]);
}
template <typename T>
__device__ D at_high(int i, const T* data) const
{
return saturate_cast<D>(data[idx_high(i)]);
}
};
template <typename D>
struct BrdColReflect101: BrdReflect101
{
BrdColReflect101(int len, int step): BrdReflect101(len), step(step) {}
template <typename T>
__device__ D at_low(int i, const T* data) const
{
return saturate_cast<D>(data[idx_low(i) * step]);
}
template <typename T>
__device__ D at_high(int i, const T* data) const
{
return saturate_cast<D>(data[idx_high(i) * step]);
}
int step;
};
struct BrdReplicate
{
explicit BrdReplicate(int len): last(len - 1) {}
__device__ int idx_low(int i) const
{
return max(i, 0);
}
__device__ int idx_high(int i) const
{
return min(i, last);
}
__device__ int idx(int i) const
{
return max(min(i, last), 0);
}
bool is_range_safe(int mini, int maxi) const
{
return true;
}
int last;
};
template <typename D>
struct BrdRowReplicate: BrdReplicate
{
explicit BrdRowReplicate(int len): BrdReplicate(len) {}
template <typename T>
__device__ D at_low(int i, const T* data) const
{
return saturate_cast<D>(data[idx_low(i)]);
}
template <typename T>
__device__ D at_high(int i, const T* data) const
{
return saturate_cast<D>(data[idx_high(i)]);
}
};
template <typename D>
struct BrdColReplicate: BrdReplicate
{
BrdColReplicate(int len, int step): BrdReplicate(len), step(step) {}
template <typename T>
__device__ D at_low(int i, const T* data) const
{
return saturate_cast<D>(data[idx_low(i) * step]);
}
template <typename T>
__device__ D at_high(int i, const T* data) const
{
return saturate_cast<D>(data[idx_high(i) * step]);
}
int step;
};
template <typename D>
struct BrdRowConstant
{
explicit BrdRowConstant(int len_, const D& val_ = VecTraits<D>::all(0)): len(len_), val(val_) {}
template <typename T>
__device__ D at_low(int i, const T* data) const
{
return i >= 0 ? saturate_cast<D>(data[i]) : val;
}
template <typename T>
__device__ D at_high(int i, const T* data) const
{
return i < len ? saturate_cast<D>(data[i]) : val;
}
bool is_range_safe(int mini, int maxi) const
{
return true;
}
int len;
D val;
};
template <typename D>
struct BrdColConstant
{
BrdColConstant(int len_, int step_, const D& val_ = VecTraits<D>::all(0)): len(len_), step(step_), val(val_) {}
template <typename T>
__device__ D at_low(int i, const T* data) const
{
return i >= 0 ? saturate_cast<D>(data[i * step]) : val;
}
template <typename T>
__device__ D at_high(int i, const T* data) const
{
return i < len ? saturate_cast<D>(data[i * step]) : val;
}
bool is_range_safe(int mini, int maxi) const
{
return true;
}
int len;
int step;
D val;
};
}
}
}
/////////////////////////////////////////////////////////////////////////////////////////////////
// Linear filters
......@@ -329,6 +144,7 @@ namespace cv { namespace gpu { namespace filters
}
filter_krnls::linearRowFilter<ksize, T, D><<<grid, threads>>>(src, dst, anchor, b);
cudaSafeCall( cudaGetLastError() );
cudaSafeCall( cudaThreadSynchronize() );
}
......@@ -467,6 +283,7 @@ namespace cv { namespace gpu { namespace filters
}
filter_krnls::linearColumnFilter<ksize, T, D><<<grid, threads>>>(src, dst, anchor, b);
cudaSafeCall( cudaGetLastError() );
cudaSafeCall( cudaThreadSynchronize() );
}
......@@ -705,14 +522,18 @@ namespace cv { namespace gpu { namespace bf
for (int i = 0; i < iters; ++i)
{
bf_krnls::bilateral_filter<1><<<grid, threads, 0, stream>>>(0, disp.data, disp.step/sizeof(T), img.data, img.step, disp.rows, disp.cols);
cudaSafeCall( cudaGetLastError() );
bf_krnls::bilateral_filter<1><<<grid, threads, 0, stream>>>(1, disp.data, disp.step/sizeof(T), img.data, img.step, disp.rows, disp.cols);
cudaSafeCall( cudaGetLastError() );
}
break;
case 3:
for (int i = 0; i < iters; ++i)
{
bf_krnls::bilateral_filter<3><<<grid, threads, 0, stream>>>(0, disp.data, disp.step/sizeof(T), img.data, img.step, disp.rows, disp.cols);
cudaSafeCall( cudaGetLastError() );
bf_krnls::bilateral_filter<3><<<grid, threads, 0, stream>>>(1, disp.data, disp.step/sizeof(T), img.data, img.step, disp.rows, disp.cols);
cudaSafeCall( cudaGetLastError() );
}
break;
default:
......
modules/gpu/src/cuda/hog.cu
View file @ deac5d97
......@@ -222,6 +222,7 @@ void compute_hists(int nbins, int block_stride_x, int block_stride_y,
int smem = hists_size + final_hists_size;
compute_hists_kernel_many_blocks<nblocks><<<grid, threads, smem>>>(
img_block_width, grad, qangle, scale, block_hists);
cudaSafeCall( cudaGetLastError() );
cudaSafeCall(cudaThreadSynchronize());
}
......@@ -325,6 +326,8 @@ void normalize_hists(int nbins, int block_stride_x, int block_stride_y,
else
cv::gpu::error("normalize_hists: histogram's size is too big, try to decrease number of bins", __FILE__, __LINE__);
cudaSafeCall( cudaGetLastError() );
cudaSafeCall(cudaThreadSynchronize());
}
......@@ -421,6 +424,8 @@ void classify_hists(int win_height, int win_width, int block_stride_y, int block
classify_hists_kernel_many_blocks<nthreads, nblocks><<<grid, threads>>>(
img_win_width, img_block_width, win_block_stride_x, win_block_stride_y,
block_hists, coefs, free_coef, threshold, labels);
cudaSafeCall( cudaGetLastError() );
cudaSafeCall(cudaThreadSynchronize());
}
......@@ -467,6 +472,8 @@ void extract_descrs_by_rows(int win_height, int win_width, int block_stride_y, i
block_stride_x;
extract_descrs_by_rows_kernel<nthreads><<<grid, threads>>>(
img_block_width, win_block_stride_x, win_block_stride_y, block_hists, descriptors);
cudaSafeCall( cudaGetLastError() );
cudaSafeCall(cudaThreadSynchronize());
}
......@@ -515,6 +522,8 @@ void extract_descrs_by_cols(int win_height, int win_width, int block_stride_y, i
block_stride_x;
extract_descrs_by_cols_kernel<nthreads><<<grid, threads>>>(
img_block_width, win_block_stride_x, win_block_stride_y, block_hists, descriptors);
cudaSafeCall( cudaGetLastError() );
cudaSafeCall(cudaThreadSynchronize());
}
......@@ -640,6 +649,8 @@ void compute_gradients_8UC4(int nbins, int height, int width, const DevMem2D& im
compute_gradients_8UC4_kernel<nthreads, 0><<<gdim, bdim>>>(
height, width, img, angle_scale, grad, qangle);
cudaSafeCall( cudaGetLastError() );
cudaSafeCall(cudaThreadSynchronize());
}
......@@ -713,6 +724,8 @@ void compute_gradients_8UC1(int nbins, int height, int width, const DevMem2D& im
compute_gradients_8UC1_kernel<nthreads, 0><<<gdim, bdim>>>(
height, width, img, angle_scale, grad, qangle);
cudaSafeCall( cudaGetLastError() );
cudaSafeCall(cudaThreadSynchronize());
}
......@@ -749,6 +762,8 @@ void resize_8UC4(const DevMem2D& src, DevMem2D dst)
float sx = (float)src.cols / dst.cols;
float sy = (float)src.rows / dst.rows;
resize_8UC4_kernel<<<grid, threads>>>(sx, sy, dst);
cudaSafeCall( cudaGetLastError() );
cudaSafeCall(cudaThreadSynchronize());
cudaSafeCall(cudaUnbindTexture(resize8UC4_tex));
......@@ -776,6 +791,8 @@ void resize_8UC1(const DevMem2D& src, DevMem2D dst)
float sx = (float)src.cols / dst.cols;
float sy = (float)src.rows / dst.rows;
resize_8UC1_kernel<<<grid, threads>>>(sx, sy, dst);
cudaSafeCall( cudaGetLastError() );
cudaSafeCall(cudaThreadSynchronize());
cudaSafeCall(cudaUnbindTexture(resize8UC1_tex));
......
modules/gpu/src/cuda/imgproc.cu
View file @ deac5d97
......@@ -137,6 +137,7 @@ namespace cv { namespace gpu { namespace imgproc
cudaSafeCall( cudaBindTexture2D(0, tex_remap, src.data, desc, src.cols, src.rows, src.step) );
remap_1c<<<grid, threads>>>(xmap.data, ymap.data, xmap.step, dst.data, dst.step, dst.cols, dst.rows);
cudaSafeCall( cudaGetLastError() );
cudaSafeCall( cudaThreadSynchronize() );
cudaSafeCall( cudaUnbindTexture(tex_remap) );
......@@ -150,6 +151,7 @@ namespace cv { namespace gpu { namespace imgproc
grid.y = divUp(dst.rows, threads.y);
remap_3c<<<grid, threads>>>(src.data, src.step, xmap.data, ymap.data, xmap.step, dst.data, dst.step, dst.cols, dst.rows);
cudaSafeCall( cudaGetLastError() );
cudaSafeCall( cudaThreadSynchronize() );
}
......@@ -259,6 +261,8 @@ namespace cv { namespace gpu { namespace imgproc
cudaSafeCall( cudaBindTexture2D( 0, tex_meanshift, src.data, desc, src.cols, src.rows, src.step ) );
meanshift_kernel<<< grid, threads >>>( dst.data, dst.step, dst.cols, dst.rows, sp, sr, maxIter, eps );
cudaSafeCall( cudaGetLastError() );
cudaSafeCall( cudaThreadSynchronize() );
cudaSafeCall( cudaUnbindTexture( tex_meanshift ) );
}
......@@ -273,6 +277,8 @@ namespace cv { namespace gpu { namespace imgproc
cudaSafeCall( cudaBindTexture2D( 0, tex_meanshift, src.data, desc, src.cols, src.rows, src.step ) );
meanshiftproc_kernel<<< grid, threads >>>( dstr.data, dstr.step, dstsp.data, dstsp.step, dstr.cols, dstr.rows, sp, sr, maxIter, eps );
cudaSafeCall( cudaGetLastError() );
cudaSafeCall( cudaThreadSynchronize() );
cudaSafeCall( cudaUnbindTexture( tex_meanshift ) );
}
......@@ -388,6 +394,7 @@ namespace cv { namespace gpu { namespace imgproc
grid.y = divUp(src.rows, threads.y);
drawColorDisp<<<grid, threads, 0, stream>>>(src.data, src.step, dst.data, dst.step, src.cols, src.rows, ndisp);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaThreadSynchronize() );
......@@ -401,6 +408,7 @@ namespace cv { namespace gpu { namespace imgproc
grid.y = divUp(src.rows, threads.y);
drawColorDisp<<<grid, threads, 0, stream>>>(src.data, src.step / sizeof(short), dst.data, dst.step, src.cols, src.rows, ndisp);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaThreadSynchronize() );
......@@ -451,6 +459,7 @@ namespace cv { namespace gpu { namespace imgproc
cudaSafeCall( cudaMemcpyToSymbol(cq, q, 16 * sizeof(float)) );
reprojectImageTo3D<<<grid, threads, 0, stream>>>(disp.data, disp.step / sizeof(T), xyzw.data, xyzw.step / sizeof(float), disp.rows, disp.cols);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaThreadSynchronize() );
......@@ -491,6 +500,8 @@ namespace cv { namespace gpu { namespace imgproc
dim3 grid(divUp(Dx.cols, threads.x), divUp(Dx.rows, threads.y));
extractCovData_kernel<<<grid, threads>>>(Dx.cols, Dx.rows, Dx, Dy, dst);
cudaSafeCall( cudaGetLastError() );
cudaSafeCall(cudaThreadSynchronize());
}
......@@ -598,6 +609,8 @@ namespace cv { namespace gpu { namespace imgproc
break;
}
cudaSafeCall( cudaGetLastError() );
cudaSafeCall(cudaThreadSynchronize());
cudaSafeCall(cudaUnbindTexture(harrisDxTex));
cudaSafeCall(cudaUnbindTexture(harrisDyTex));
......@@ -712,6 +725,8 @@ namespace cv { namespace gpu { namespace imgproc
break;
}
cudaSafeCall( cudaGetLastError() );
cudaSafeCall(cudaThreadSynchronize());
cudaSafeCall(cudaUnbindTexture(minEigenValDxTex));
cudaSafeCall(cudaUnbindTexture(minEigenValDyTex));
......@@ -746,6 +761,8 @@ namespace cv { namespace gpu { namespace imgproc
dim3 grid(divUp(src.cols, threads.x));
column_sumKernel_32F<<<grid, threads>>>(src.cols, src.rows, src, dst);
cudaSafeCall( cudaGetLastError() );
cudaSafeCall(cudaThreadSynchronize());
}
......@@ -772,6 +789,8 @@ namespace cv { namespace gpu { namespace imgproc
dim3 grid(divUp(c.cols, threads.x), divUp(c.rows, threads.y));
mulSpectrumsKernel<<<grid, threads>>>(a, b, c);
cudaSafeCall( cudaGetLastError() );
cudaSafeCall(cudaThreadSynchronize());
}
......@@ -799,6 +818,8 @@ namespace cv { namespace gpu { namespace imgproc
dim3 grid(divUp(c.cols, threads.x), divUp(c.rows, threads.y));
mulSpectrumsKernel_CONJ<<<grid, threads>>>(a, b, c);
cudaSafeCall( cudaGetLastError() );
cudaSafeCall(cudaThreadSynchronize());
}
......@@ -827,6 +848,8 @@ namespace cv { namespace gpu { namespace imgproc
dim3 grid(divUp(c.cols, threads.x), divUp(c.rows, threads.y));
mulAndScaleSpectrumsKernel<<<grid, threads>>>(a, b, scale, c);
cudaSafeCall( cudaGetLastError() );
cudaSafeCall(cudaThreadSynchronize());
}
......@@ -855,6 +878,8 @@ namespace cv { namespace gpu { namespace imgproc
dim3 grid(divUp(c.cols, threads.x), divUp(c.rows, threads.y));
mulAndScaleSpectrumsKernel_CONJ<<<grid, threads>>>(a, b, scale, c);
cudaSafeCall( cudaGetLastError() );
cudaSafeCall(cudaThreadSynchronize());
}
......
modules/gpu/src/cuda/match_template.cu
View file @ deac5d97
......@@ -132,6 +132,8 @@ void matchTemplateNaive_CCORR_32F(const DevMem2D image, const DevMem2D templ,
templ.cols, templ.rows, image, templ, result);
break;
}
cudaSafeCall( cudaGetLastError() );
cudaSafeCall(cudaThreadSynchronize());
}
......@@ -161,6 +163,8 @@ void matchTemplateNaive_CCORR_8U(const DevMem2D image, const DevMem2D templ,
templ.cols, templ.rows, image, templ, result);
break;
}
cudaSafeCall( cudaGetLastError() );
cudaSafeCall(cudaThreadSynchronize());
}
......@@ -222,6 +226,8 @@ void matchTemplateNaive_SQDIFF_32F(const DevMem2D image, const DevMem2D templ,
templ.cols, templ.rows, image, templ, result);
break;
}
cudaSafeCall( cudaGetLastError() );
cudaSafeCall(cudaThreadSynchronize());
}
......@@ -251,6 +257,8 @@ void matchTemplateNaive_SQDIFF_8U(const DevMem2D image, const DevMem2D templ,
templ.cols, templ.rows, image, templ, result);
break;
}
cudaSafeCall( cudaGetLastError() );
cudaSafeCall(cudaThreadSynchronize());
}
......@@ -299,6 +307,8 @@ void matchTemplatePrepared_SQDIFF_8U(
w, h, image_sqsum, templ_sqsum, result);
break;
}
cudaSafeCall( cudaGetLastError() );
cudaSafeCall(cudaThreadSynchronize());
}
......@@ -348,6 +358,8 @@ void matchTemplatePrepared_SQDIFF_NORMED_8U(
w, h, image_sqsum, templ_sqsum, result);
break;
}
cudaSafeCall( cudaGetLastError() );
cudaSafeCall(cudaThreadSynchronize());
}
......@@ -378,6 +390,8 @@ void matchTemplatePrepared_CCOFF_8U(
dim3 grid(divUp(result.cols, threads.x), divUp(result.rows, threads.y));
matchTemplatePreparedKernel_CCOFF_8U<<<grid, threads>>>(
w, h, (float)templ_sum / (w * h), image_sum, result);
cudaSafeCall( cudaGetLastError() );
cudaSafeCall(cudaThreadSynchronize());
}
......@@ -418,6 +432,8 @@ void matchTemplatePrepared_CCOFF_8UC2(
matchTemplatePreparedKernel_CCOFF_8UC2<<<grid, threads>>>(
w, h, (float)templ_sum_r / (w * h), (float)templ_sum_g / (w * h),
image_sum_r, image_sum_g, result);
cudaSafeCall( cudaGetLastError() );
cudaSafeCall(cudaThreadSynchronize());
}
......@@ -472,6 +488,8 @@ void matchTemplatePrepared_CCOFF_8UC3(
(float)templ_sum_g / (w * h),
(float)templ_sum_b / (w * h),
image_sum_r, image_sum_g, image_sum_b, result);
cudaSafeCall( cudaGetLastError() );
cudaSafeCall(cudaThreadSynchronize());
}
......@@ -536,6 +554,8 @@ void matchTemplatePrepared_CCOFF_8UC4(
(float)templ_sum_a / (w * h),
image_sum_r, image_sum_g, image_sum_b, image_sum_a,
result);
cudaSafeCall( cudaGetLastError() );
cudaSafeCall(cudaThreadSynchronize());
}
......@@ -580,6 +600,8 @@ void matchTemplatePrepared_CCOFF_NORMED_8U(
matchTemplatePreparedKernel_CCOFF_NORMED_8U<<<grid, threads>>>(
w, h, weight, templ_sum_scale, templ_sqsum_scale,
image_sum, image_sqsum, result);
cudaSafeCall( cudaGetLastError() );
cudaSafeCall(cudaThreadSynchronize());
}
......@@ -641,6 +663,8 @@ void matchTemplatePrepared_CCOFF_NORMED_8UC2(
image_sum_r, image_sqsum_r,
image_sum_g, image_sqsum_g,
result);
cudaSafeCall( cudaGetLastError() );
cudaSafeCall(cudaThreadSynchronize());
}
......@@ -716,6 +740,8 @@ void matchTemplatePrepared_CCOFF_NORMED_8UC3(
image_sum_g, image_sqsum_g,
image_sum_b, image_sqsum_b,
result);
cudaSafeCall( cudaGetLastError() );
cudaSafeCall(cudaThreadSynchronize());
}
......@@ -805,6 +831,8 @@ void matchTemplatePrepared_CCOFF_NORMED_8UC4(
image_sum_b, image_sqsum_b,
image_sum_a, image_sqsum_a,
result);
cudaSafeCall( cudaGetLastError() );
cudaSafeCall(cudaThreadSynchronize());
}
......@@ -847,6 +875,8 @@ void normalize_8U(int w, int h, const DevMem2D_<unsigned long long> image_sqsum,
normalizeKernel_8U<4><<<grid, threads>>>(w, h, image_sqsum, templ_sqsum, result);
break;
}
cudaSafeCall( cudaGetLastError() );
cudaSafeCall(cudaThreadSynchronize());
}
......@@ -887,6 +917,8 @@ void extractFirstChannel_32F(const DevMem2D image, DevMem2Df result, int cn)
extractFirstChannel_32F<4><<<grid, threads>>>(image, result);
break;
}
cudaSafeCall( cudaGetLastError() );
cudaSafeCall(cudaThreadSynchronize());
}
......
modules/gpu/src/cuda/mathfunc.cu
View file @ deac5d97
......@@ -150,6 +150,7 @@ namespace cv { namespace gpu { namespace mathfunc
cartToPolar<Mag, Angle><<<grid, threads, 0, stream>>>(
x.data, x.step/x.elemSize(), y.data, y.step/y.elemSize(),
mag.data, mag.step/mag.elemSize(), angle.data, angle.step/angle.elemSize(), scale, x.cols, x.rows);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaThreadSynchronize() );
......@@ -198,6 +199,7 @@ namespace cv { namespace gpu { namespace mathfunc
polarToCart<Mag><<<grid, threads, 0, stream>>>(mag.data, mag.step/mag.elemSize(),
angle.data, angle.step/angle.elemSize(), scale, x.data, x.step/x.elemSize(), y.data, y.step/y.elemSize(), mag.cols, mag.rows);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaThreadSynchronize() );
......
modules/gpu/src/cuda/matrix_operations.cu
View file @ deac5d97
This diff is collapsed.
modules/gpu/src/cuda/matrix_reductions.cu
View file @ deac5d97
This diff is collapsed.
modules/gpu/src/cuda/split_merge.cu
View file @ deac5d97
......@@ -233,6 +233,8 @@ namespace cv { namespace gpu { namespace split_merge {
src[0].data, src[0].step,
src[1].data, src[1].step,
dst.rows, dst.cols, dst.data, dst.step);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall(cudaThreadSynchronize());
}
......@@ -248,6 +250,8 @@ namespace cv { namespace gpu { namespace split_merge {
src[1].data, src[1].step,
src[2].data, src[2].step,
dst.rows, dst.cols, dst.data, dst.step);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall(cudaThreadSynchronize());
}
......@@ -264,6 +268,8 @@ namespace cv { namespace gpu { namespace split_merge {
src[2].data, src[2].step,
src[3].data, src[3].step,
dst.rows, dst.cols, dst.data, dst.step);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall(cudaThreadSynchronize());
}
......@@ -436,6 +442,8 @@ namespace cv { namespace gpu { namespace split_merge {
src.data, src.step, src.rows, src.cols,
dst[0].data, dst[0].step,
dst[1].data, dst[1].step);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall(cudaThreadSynchronize());
}
......@@ -451,6 +459,8 @@ namespace cv { namespace gpu { namespace split_merge {
dst[0].data, dst[0].step,
dst[1].data, dst[1].step,
dst[2].data, dst[2].step);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall(cudaThreadSynchronize());
}
......@@ -467,6 +477,8 @@ namespace cv { namespace gpu { namespace split_merge {
dst[1].data, dst[1].step,
dst[2].data, dst[2].step,
dst[3].data, dst[3].step);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall(cudaThreadSynchronize());
}
......
modules/gpu/src/cuda/stereobm.cu
View file @ deac5d97
......@@ -325,6 +325,8 @@ template<int RADIUS> void kernel_caller(const DevMem2D& left, const DevMem2D& ri
size_t smem_size = (BLOCK_W + N_DISPARITIES * (BLOCK_W + 2 * RADIUS)) * sizeof(unsigned int);
stereoKernel<RADIUS><<<grid, threads, smem_size, stream>>>(left.data, right.data, left.step, disp, maxdisp);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaThreadSynchronize() );
};
......@@ -402,6 +404,7 @@ extern "C" void prefilter_xsobel(const DevMem2D& input, const DevMem2D& output,
grid.y = divUp(input.rows, threads.y);
prefilter_kernel<<<grid, threads, 0, stream>>>(output, prefilterCap);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaThreadSynchronize() );
......@@ -526,6 +529,7 @@ extern "C" void postfilter_textureness(const DevMem2D& input, int winsz, float a
size_t smem_size = (threads.x + threads.x + (winsz/2) * 2 ) * sizeof(float);
textureness_kernel<<<grid, threads, smem_size, stream>>>(disp, winsz, avgTexturenessThreshold);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaThreadSynchronize() );
......
modules/gpu/src/cuda/stereobp.cu
View file @ deac5d97
......@@ -172,6 +172,7 @@ namespace cv { namespace gpu { namespace bp
grid.y = divUp(left.rows, threads.y);
comp_data<1, short><<<grid, threads, 0, stream>>>(left, right, (DevMem2D_<short>)data);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaThreadSynchronize() );
......@@ -185,6 +186,7 @@ namespace cv { namespace gpu { namespace bp
grid.y = divUp(left.rows, threads.y);
comp_data<1, float><<<grid, threads, 0, stream>>>(left, right, (DevMem2D_<float>)data);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaThreadSynchronize() );
......@@ -199,6 +201,7 @@ namespace cv { namespace gpu { namespace bp
grid.y = divUp(left.rows, threads.y);
comp_data<3, short><<<grid, threads, 0, stream>>>(left, right, (DevMem2D_<short>)data);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaThreadSynchronize() );
......@@ -212,6 +215,7 @@ namespace cv { namespace gpu { namespace bp
grid.y = divUp(left.rows, threads.y);
comp_data<3, float><<<grid, threads, 0, stream>>>(left, right, (DevMem2D_<float>)data);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaThreadSynchronize() );
......@@ -226,6 +230,7 @@ namespace cv { namespace gpu { namespace bp
grid.y = divUp(left.rows, threads.y);
comp_data<4, short><<<grid, threads, 0, stream>>>(left, right, (DevMem2D_<short>)data);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaThreadSynchronize() );
......@@ -239,6 +244,7 @@ namespace cv { namespace gpu { namespace bp
grid.y = divUp(left.rows, threads.y);
comp_data<4, float><<<grid, threads, 0, stream>>>(left, right, (DevMem2D_<float>)data);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaThreadSynchronize() );
......@@ -278,6 +284,7 @@ namespace cv { namespace gpu { namespace bp
grid.y = divUp(dst_rows, threads.y);
data_step_down<T><<<grid, threads, 0, stream>>>(dst_cols, dst_rows, src_rows, (DevMem2D_<T>)src, (DevMem2D_<T>)dst);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaThreadSynchronize() );
......@@ -321,9 +328,13 @@ namespace cv { namespace gpu { namespace bp
int src_idx = (dst_idx + 1) & 1;
level_up_message<T><<<grid, threads, 0, stream>>>(dst_cols, dst_rows, src_rows, (DevMem2D_<T>)mus[src_idx], (DevMem2D_<T>)mus[dst_idx]);
cudaSafeCall( cudaGetLastError() );
level_up_message<T><<<grid, threads, 0, stream>>>(dst_cols, dst_rows, src_rows, (DevMem2D_<T>)mds[src_idx], (DevMem2D_<T>)mds[dst_idx]);
cudaSafeCall( cudaGetLastError() );
level_up_message<T><<<grid, threads, 0, stream>>>(dst_cols, dst_rows, src_rows, (DevMem2D_<T>)mls[src_idx], (DevMem2D_<T>)mls[dst_idx]);
cudaSafeCall( cudaGetLastError() );
level_up_message<T><<<grid, threads, 0, stream>>>(dst_cols, dst_rows, src_rows, (DevMem2D_<T>)mrs[src_idx], (DevMem2D_<T>)mrs[dst_idx]);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaThreadSynchronize() );
......@@ -443,6 +454,7 @@ namespace cv { namespace gpu { namespace bp
for(int t = 0; t < iters; ++t)
{
one_iteration<T><<<grid, threads, 0, stream>>>(t, (DevMem2D_<T>)u, (T*)d.data, (T*)l.data, (T*)r.data, (DevMem2D_<T>)data, cols, rows);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaThreadSynchronize() );
......@@ -505,6 +517,7 @@ namespace cv { namespace gpu { namespace bp
grid.y = divUp(disp.rows, threads.y);
output<T><<<grid, threads, 0, stream>>>((DevMem2D_<T>)u, (const T*)d.data, (const T*)l.data, (const T*)r.data, (const T*)data.data, disp);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaThreadSynchronize() );
......
modules/gpu/src/cuda/stereocsbp.cu
View file @ deac5d97
......@@ -382,6 +382,8 @@ namespace cv { namespace gpu { namespace csbp
cudaSafeCall( cudaMemcpyToSymbol(cmsg_step1, &msg_step, sizeof(size_t)) );
init_data_cost_callers[level](rows, cols, h, w, level, ndisp, channels, stream);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaThreadSynchronize() );
......@@ -395,6 +397,9 @@ namespace cv { namespace gpu { namespace csbp
get_first_k_initial_local<<<grid, threads, 0, stream>>> (data_cost_selected, disp_selected_pyr, h, w, nr_plane);
else
get_first_k_initial_global<<<grid, threads, 0, stream>>>(data_cost_selected, disp_selected_pyr, h, w, nr_plane);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaThreadSynchronize() );
}
......@@ -578,6 +583,7 @@ namespace cv { namespace gpu { namespace csbp
cudaSafeCall( cudaMemcpyToSymbol(cmsg_step2, &msg_step2, sizeof(size_t)) );
callers[level](disp_selected_pyr, data_cost, rows, cols, h, w, level, nr_plane, channels, stream);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaThreadSynchronize() );
......@@ -700,10 +706,11 @@ namespace cv { namespace gpu { namespace csbp
grid.y = divUp(h, threads.y);
init_message<<<grid, threads, 0, stream>>>(u_new, d_new, l_new, r_new,
u_cur, d_cur, l_cur, r_cur,
selected_disp_pyr_new, selected_disp_pyr_cur,
data_cost_selected, data_cost,
h, w, nr_plane, h2, w2, nr_plane2);
u_cur, d_cur, l_cur, r_cur,
selected_disp_pyr_new, selected_disp_pyr_cur,
data_cost_selected, data_cost,
h, w, nr_plane, h2, w2, nr_plane2);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaThreadSynchronize() );
......@@ -805,6 +812,7 @@ namespace cv { namespace gpu { namespace csbp
for(int t = 0; t < iters; ++t)
{
compute_message<<<grid, threads, 0, stream>>>(u, d, l, r, data_cost_selected, selected_disp_pyr_cur, h, w, nr_plane, t & 1);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaThreadSynchronize() );
......@@ -873,7 +881,9 @@ namespace cv { namespace gpu { namespace csbp
grid.y = divUp(disp.rows, threads.y);
compute_disp<<<grid, threads, 0, stream>>>(u, d, l, r, data_cost_selected, disp_selected,
disp.data, disp.step / disp.elemSize(), disp.cols, disp.rows, nr_plane);
disp.data, disp.step / disp.elemSize(), disp.cols, disp.rows, nr_plane);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaThreadSynchronize() );
}
......
modules/gpu/src/cuda/surf.cu
View file @ deac5d97
This diff is collapsed.
modules/gpu/src/cudastream.cpp
View file @ deac5d97
......@@ -61,8 +61,8 @@ void cv::gpu::Stream::enqueueDownload(const GpuMat& /*src*/, CudaMem& /*dst*/) {
void cv::gpu::Stream::enqueueUpload(const CudaMem& /*src*/, GpuMat& /*dst*/) { throw_nogpu(); }
void cv::gpu::Stream::enqueueUpload(const Mat& /*src*/, GpuMat& /*dst*/) { throw_nogpu(); }
void cv::gpu::Stream::enqueueCopy(const GpuMat& /*src*/, GpuMat& /*dst*/) { throw_nogpu(); }
void cv::gpu::Stream::enqueueMemSet(const GpuMat& /*src*/, Scalar /*val*/) { throw_nogpu(); }
void cv::gpu::Stream::enqueueMemSet(const GpuMat& /*src*/, Scalar /*val*/, const GpuMat& /*mask*/) { throw_nogpu(); }
void cv::gpu::Stream::enqueueMemSet(GpuMat& /*src*/, Scalar /*val*/) { throw_nogpu(); }
void cv::gpu::Stream::enqueueMemSet(GpuMat& /*src*/, Scalar /*val*/, const GpuMat& /*mask*/) { throw_nogpu(); }
void cv::gpu::Stream::enqueueConvert(const GpuMat& /*src*/, GpuMat& /*dst*/, int /*type*/, double /*a*/, double /*b*/) { throw_nogpu(); }
#else /* !defined (HAVE_CUDA) */
......@@ -77,8 +77,10 @@ namespace cv
{
void copy_to_with_mask(const DevMem2D& src, DevMem2D dst, int depth, const DevMem2D& mask, int channels, const cudaStream_t & stream = 0);
void set_to_without_mask (DevMem2D dst, int depth, const double *scalar, int channels, const cudaStream_t & stream = 0);
void set_to_with_mask (DevMem2D dst, int depth, const double *scalar, const DevMem2D& mask, int channels, const cudaStream_t & stream = 0);
template <typename T>
void set_to_gpu(const DevMem2D& mat, const T* scalar, int channels, cudaStream_t stream);
template <typename T>
void set_to_gpu(const DevMem2D& mat, const T* scalar, const DevMem2D& mask, int channels, cudaStream_t stream);
void convert_gpu(const DevMem2D& src, int sdepth, const DevMem2D& dst, int ddepth, double alpha, double beta, cudaStream_t stream = 0);
}
......@@ -99,6 +101,20 @@ namespace
size_t bwidth = src.cols * src.elemSize();
cudaSafeCall( cudaMemcpy2DAsync(dst.data, dst.step, src.data, src.step, bwidth, src.rows, k, s) );
};
template <typename T>
void kernelSet(GpuMat& src, const Scalar& s, cudaStream_t stream)
{
Scalar_<T> sf = s;
matrix_operations::set_to_gpu(src, sf.val, src.channels(), stream);
}
template <typename T>
void kernelSetMask(GpuMat& src, const Scalar& s, const GpuMat& mask, cudaStream_t stream)
{
Scalar_<T> sf = s;
matrix_operations::set_to_gpu(src, sf.val, mask, src.channels(), stream);
}
}
CV_EXPORTS cudaStream_t cv::gpu::StreamAccessor::getStream(const Stream& stream) { return stream.impl->stream; };
......@@ -172,14 +188,26 @@ void cv::gpu::Stream::enqueueUpload(const CudaMem& src, GpuMat& dst){ devcopy(sr
void cv::gpu::Stream::enqueueUpload(const Mat& src, GpuMat& dst) { devcopy(src, dst, impl->stream, cudaMemcpyHostToDevice); }
void cv::gpu::Stream::enqueueCopy(const GpuMat& src, GpuMat& dst) { devcopy(src, dst, impl->stream, cudaMemcpyDeviceToDevice); }
void cv::gpu::Stream::enqueueMemSet(const GpuMat& src, Scalar val)
void cv::gpu::Stream::enqueueMemSet(GpuMat& src, Scalar val)
{
matrix_operations::set_to_without_mask(src, src.depth(), val.val, src.channels(), impl->stream);
typedef void (*set_caller_t)(GpuMat& src, const Scalar& s, cudaStream_t stream);
static const set_caller_t set_callers[] =
{
kernelSet<uchar>, kernelSet<schar>, kernelSet<ushort>, kernelSet<short>,
kernelSet<int>, kernelSet<float>, kernelSet<double>
};
set_callers[src.depth()](src, val, impl->stream);
}
void cv::gpu::Stream::enqueueMemSet(const GpuMat& src, Scalar val, const GpuMat& mask)
void cv::gpu::Stream::enqueueMemSet(GpuMat& src, Scalar val, const GpuMat& mask)
{
matrix_operations::set_to_with_mask(src, src.depth(), val.val, mask, src.channels(), impl->stream);
typedef void (*set_caller_t)(GpuMat& src, const Scalar& s, const GpuMat& mask, cudaStream_t stream);
static const set_caller_t set_callers[] =
{
kernelSetMask<uchar>, kernelSetMask<schar>, kernelSetMask<ushort>, kernelSetMask<short>,
kernelSetMask<int>, kernelSetMask<float>, kernelSetMask<double>
};
set_callers[src.depth()](src, val, mask, impl->stream);
}
void cv::gpu::Stream::enqueueConvert(const GpuMat& src, GpuMat& dst, int rtype, double alpha, double beta)
......
modules/gpu/src/element_operations.cpp
View file @ deac5d97
This diff is collapsed.
modules/gpu/src/imgproc_gpu.cpp
View file @ deac5d97
......@@ -128,6 +128,8 @@ void cv::gpu::remap(const GpuMat& src, GpuMat& dst, const GpuMat& xmap, const Gp
void cv::gpu::meanShiftFiltering(const GpuMat& src, GpuMat& dst, int sp, int sr, TermCriteria criteria)
{
CV_Assert(TargetArchs::builtWith(COMPUTE_12) && DeviceInfo().supports(COMPUTE_12));
if( src.empty() )
CV_Error( CV_StsBadArg, "The input image is empty" );
......@@ -154,6 +156,8 @@ void cv::gpu::meanShiftFiltering(const GpuMat& src, GpuMat& dst, int sp, int sr,
void cv::gpu::meanShiftProc(const GpuMat& src, GpuMat& dstr, GpuMat& dstsp, int sp, int sr, TermCriteria criteria)
{
CV_Assert(TargetArchs::builtWith(COMPUTE_12) && DeviceInfo().supports(COMPUTE_12));
if( src.empty() )
CV_Error( CV_StsBadArg, "The input image is empty" );
......
modules/gpu/src/matrix_operations.cpp
View file @ deac5d97
......@@ -87,8 +87,10 @@ namespace cv
{
void copy_to_with_mask(const DevMem2D& src, DevMem2D dst, int depth, const DevMem2D& mask, int channels, const cudaStream_t & stream = 0);
void set_to_without_mask (DevMem2D dst, int depth, const double *scalar, int channels, const cudaStream_t & stream = 0);
void set_to_with_mask (DevMem2D dst, int depth, const double *scalar, const DevMem2D& mask, int channels, const cudaStream_t & stream = 0);
template <typename T>
void set_to_gpu(const DevMem2D& mat, const T* scalar, int channels, cudaStream_t stream);
template <typename T>
void set_to_gpu(const DevMem2D& mat, const T* scalar, const DevMem2D& mask, int channels, cudaStream_t stream);
void convert_gpu(const DevMem2D& src, int sdepth, const DevMem2D& dst, int ddepth, double alpha, double beta, cudaStream_t stream = 0);
}
......@@ -363,9 +365,11 @@ namespace
}
};
template <typename T>
void kernelSet(GpuMat& src, const Scalar& s)
{
matrix_operations::set_to_without_mask(src, src.depth(), s.val, src.channels());
Scalar_<T> sf = s;
matrix_operations::set_to_gpu(src, sf.val, src.channels(), 0);
}
template<int SDEPTH, int SCN> struct NppSetMaskFunc
......@@ -412,9 +416,11 @@ namespace
}
};
template <typename T>
void kernelSetMask(GpuMat& src, const Scalar& s, const GpuMat& mask)
{
matrix_operations::set_to_with_mask(src, src.depth(), s.val, mask, src.channels());
Scalar_<T> sf = s;
matrix_operations::set_to_gpu(src, sf.val, mask, src.channels(), 0);
}
}
......@@ -433,13 +439,13 @@ GpuMat& GpuMat::setTo(const Scalar& s, const GpuMat& mask)
typedef void (*set_caller_t)(GpuMat& src, const Scalar& s);
static const set_caller_t set_callers[8][4] =
{
{NppSet<CV_8U, 1, nppiSet_8u_C1R>::set,kernelSet,kernelSet,NppSet<CV_8U, 4, nppiSet_8u_C4R>::set},
{kernelSet,kernelSet,kernelSet,kernelSet},
{NppSet<CV_16U, 1, nppiSet_16u_C1R>::set,kernelSet,kernelSet,NppSet<CV_16U, 4, nppiSet_16u_C4R>::set},
{NppSet<CV_16S, 1, nppiSet_16s_C1R>::set,kernelSet,kernelSet,NppSet<CV_16S, 4, nppiSet_16s_C4R>::set},
{NppSet<CV_32S, 1, nppiSet_32s_C1R>::set,kernelSet,kernelSet,NppSet<CV_32S, 4, nppiSet_32s_C4R>::set},
{NppSet<CV_32F, 1, nppiSet_32f_C1R>::set,kernelSet,kernelSet,NppSet<CV_32F, 4, nppiSet_32f_C4R>::set},
{kernelSet,kernelSet,kernelSet,kernelSet},
{NppSet<CV_8U, 1, nppiSet_8u_C1R>::set,kernelSet<uchar>,kernelSet<uchar>,NppSet<CV_8U, 4, nppiSet_8u_C4R>::set},
{kernelSet<schar>,kernelSet<schar>,kernelSet<schar>,kernelSet<schar>},
{NppSet<CV_16U, 1, nppiSet_16u_C1R>::set,kernelSet<ushort>,kernelSet<ushort>,NppSet<CV_16U, 4, nppiSet_16u_C4R>::set},
{NppSet<CV_16S, 1, nppiSet_16s_C1R>::set,kernelSet<short>,kernelSet<short>,NppSet<CV_16S, 4, nppiSet_16s_C4R>::set},
{NppSet<CV_32S, 1, nppiSet_32s_C1R>::set,kernelSet<int>,kernelSet<int>,NppSet<CV_32S, 4, nppiSet_32s_C4R>::set},
{NppSet<CV_32F, 1, nppiSet_32f_C1R>::set,kernelSet<float>,kernelSet<float>,NppSet<CV_32F, 4, nppiSet_32f_C4R>::set},
{kernelSet<double>,kernelSet<double>,kernelSet<double>,kernelSet<double>},
{0,0,0,0}
};
set_callers[depth()][channels()-1](*this, s);
......@@ -449,13 +455,13 @@ GpuMat& GpuMat::setTo(const Scalar& s, const GpuMat& mask)
typedef void (*set_caller_t)(GpuMat& src, const Scalar& s, const GpuMat& mask);
static const set_caller_t set_callers[8][4] =
{
{NppSetMask<CV_8U, 1, nppiSet_8u_C1MR>::set,kernelSetMask,kernelSetMask,NppSetMask<CV_8U, 4, nppiSet_8u_C4MR>::set},
{kernelSetMask,kernelSetMask,kernelSetMask,kernelSetMask},
{NppSetMask<CV_16U, 1, nppiSet_16u_C1MR>::set,kernelSetMask,kernelSetMask,NppSetMask<CV_16U, 4, nppiSet_16u_C4MR>::set},
{NppSetMask<CV_16S, 1, nppiSet_16s_C1MR>::set,kernelSetMask,kernelSetMask,NppSetMask<CV_16S, 4, nppiSet_16s_C4MR>::set},
{NppSetMask<CV_32S, 1, nppiSet_32s_C1MR>::set,kernelSetMask,kernelSetMask,NppSetMask<CV_32S, 4, nppiSet_32s_C4MR>::set},
{NppSetMask<CV_32F, 1, nppiSet_32f_C1MR>::set,kernelSetMask,kernelSetMask,NppSetMask<CV_32F, 4, nppiSet_32f_C4MR>::set},
{kernelSetMask,kernelSetMask,kernelSetMask,kernelSetMask},
{NppSetMask<CV_8U, 1, nppiSet_8u_C1MR>::set,kernelSetMask<uchar>,kernelSetMask<uchar>,NppSetMask<CV_8U, 4, nppiSet_8u_C4MR>::set},
{kernelSetMask<schar>,kernelSetMask<schar>,kernelSetMask<schar>,kernelSetMask<schar>},
{NppSetMask<CV_16U, 1, nppiSet_16u_C1MR>::set,kernelSetMask<ushort>,kernelSetMask<ushort>,NppSetMask<CV_16U, 4, nppiSet_16u_C4MR>::set},
{NppSetMask<CV_16S, 1, nppiSet_16s_C1MR>::set,kernelSetMask<short>,kernelSetMask<short>,NppSetMask<CV_16S, 4, nppiSet_16s_C4MR>::set},
{NppSetMask<CV_32S, 1, nppiSet_32s_C1MR>::set,kernelSetMask<int>,kernelSetMask<int>,NppSetMask<CV_32S, 4, nppiSet_32s_C4MR>::set},
{NppSetMask<CV_32F, 1, nppiSet_32f_C1MR>::set,kernelSetMask<float>,kernelSetMask<float>,NppSetMask<CV_32F, 4, nppiSet_32f_C4MR>::set},
{kernelSetMask<double>,kernelSetMask<double>,kernelSetMask<double>,kernelSetMask<double>},
{0,0,0,0}
};
set_callers[depth()][channels()-1](*this, s, mask);
......
modules/gpu/src/mssegmentation.cpp
View file @ deac5d97
......@@ -227,6 +227,8 @@ inline int dist2(const cv::Vec2s& lhs, const cv::Vec2s& rhs)
void cv::gpu::meanShiftSegmentation(const GpuMat& src, Mat& dst, int sp, int sr, int minsize, TermCriteria criteria)
{
CV_Assert(TargetArchs::builtWith(COMPUTE_12) && DeviceInfo().supports(COMPUTE_12));
CV_Assert(src.type() == CV_8UC4);
const int nrows = src.rows;
const int ncols = src.cols;
......
modules/gpu/src/opencv2/gpu/device/border_interpolate.hpp
View file @ deac5d97
......@@ -40,6 +40,9 @@
//
//M*/
#include "opencv2/gpu/device/saturate_cast.hpp"
#include "opencv2/gpu/device/vecmath.hpp"
namespace cv
{
namespace gpu
......@@ -48,7 +51,7 @@ namespace cv
{
struct BrdReflect101
{
BrdReflect101(int len): last(len - 1) {}
explicit BrdReflect101(int len): last(len - 1) {}
__device__ int idx_low(int i) const
{
......@@ -62,7 +65,7 @@ namespace cv
__device__ int idx(int i) const
{
return abs(idx_high(i));
return idx_low(idx_high(i));
}
bool is_range_safe(int mini, int maxi) const
......@@ -70,49 +73,55 @@ namespace cv
return -last <= mini && maxi <= 2 * last;
}
private:
int last;
};
template <typename T>
template <typename D>
struct BrdRowReflect101: BrdReflect101
{
BrdRowReflect101(int len): BrdReflect101(len) {}
explicit BrdRowReflect101(int len): BrdReflect101(len) {}
__device__ float at_low(int i, const T* data) const
template <typename T>
__device__ D at_low(int i, const T* data) const
{
return data[idx_low(i)];
return saturate_cast<D>(data[idx_low(i)]);
}
__device__ float at_high(int i, const T* data) const
template <typename T>
__device__ D at_high(int i, const T* data) const
{
return data[idx_high(i)];
return saturate_cast<D>(data[idx_high(i)]);
}
};
template <typename T>
template <typename D>
struct BrdColReflect101: BrdReflect101
{
BrdColReflect101(int len, int step): BrdReflect101(len), step(step) {}
__device__ float at_low(int i, const T* data) const
template <typename T>
__device__ D at_low(int i, const T* data) const
{
return data[idx_low(i) * step];
return saturate_cast<D>(data[idx_low(i) * step]);
}
__device__ float at_high(int i, const T* data) const
template <typename T>
__device__ D at_high(int i, const T* data) const
{
return data[idx_high(i) * step];
return saturate_cast<D>(data[idx_high(i) * step]);
}
private:
int step;
};
struct BrdReplicate
{
BrdReplicate(int len): last(len - 1) {}
explicit BrdReplicate(int len): last(len - 1) {}
__device__ int idx_low(int i) const
{
......@@ -126,7 +135,7 @@ namespace cv
__device__ int idx(int i) const
{
return max(min(i, last), 0);
return idx_low(idx_high(i));
}
bool is_range_safe(int mini, int maxi) const
......@@ -134,42 +143,104 @@ namespace cv
return true;
}
private:
int last;
};
template <typename T>
template <typename D>
struct BrdRowReplicate: BrdReplicate
{
BrdRowReplicate(int len): BrdReplicate(len) {}
explicit BrdRowReplicate(int len): BrdReplicate(len) {}
__device__ float at_low(int i, const T* data) const
template <typename T>
__device__ D at_low(int i, const T* data) const
{
return data[idx_low(i)];
return saturate_cast<D>(data[idx_low(i)]);
}
__device__ float at_high(int i, const T* data) const
template <typename T>
__device__ D at_high(int i, const T* data) const
{
return data[idx_high(i)];
return saturate_cast<D>(data[idx_high(i)]);
}
};
template <typename T>
template <typename D>
struct BrdColReplicate: BrdReplicate
{
BrdColReplicate(int len, int step): BrdReplicate(len), step(step) {}
__device__ float at_low(int i, const T* data) const
template <typename T>
__device__ D at_low(int i, const T* data) const
{
return data[idx_low(i) * step];
return saturate_cast<D>(data[idx_low(i) * step]);
}
__device__ float at_high(int i, const T* data) const
template <typename T>
__device__ D at_high(int i, const T* data) const
{
return saturate_cast<D>(data[idx_high(i) * step]);
}
private:
int step;
};
template <typename D>
struct BrdRowConstant
{
explicit BrdRowConstant(int len_, const D& val_ = VecTraits<D>::all(0)): len(len_), val(val_) {}
template <typename T>
__device__ D at_low(int i, const T* data) const
{
return data[idx_high(i) * step];
return i >= 0 ? saturate_cast<D>(data[i]) : val;
}
template <typename T>
__device__ D at_high(int i, const T* data) const
{
return i < len ? saturate_cast<D>(data[i]) : val;
}
bool is_range_safe(int mini, int maxi) const
{
return true;
}
private:
int len;
D val;
};
template <typename D>
struct BrdColConstant
{
BrdColConstant(int len_, int step_, const D& val_ = VecTraits<D>::all(0)): len(len_), step(step_), val(val_) {}
template <typename T>
__device__ D at_low(int i, const T* data) const
{
return i >= 0 ? saturate_cast<D>(data[i * step]) : val;
}
template <typename T>
__device__ D at_high(int i, const T* data) const
{
return i < len ? saturate_cast<D>(data[i * step]) : val;
}
bool is_range_safe(int mini, int maxi) const
{
return true;
}
private:
int len;
int step;
D val;
};
}
}
......
modules/gpu/src/opencv2/gpu/device/transform.hpp
View file @ deac5d97
......@@ -329,6 +329,7 @@ namespace cv
grid.y = divUp(src.rows, threads.y);
device::transformSimple<T, D><<<grid, threads, 0, stream>>>(src, dst, mask, op);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaThreadSynchronize() );
......@@ -345,6 +346,7 @@ namespace cv
grid.y = divUp(src1.rows, threads.y);
device::transformSimple<T1, T2, D><<<grid, threads, 0, stream>>>(src1, src2, dst, mask, op);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaThreadSynchronize() );
......@@ -365,6 +367,7 @@ namespace cv
grid.y = divUp(src.rows, threads.y);
device::transformSmart<T, D><<<grid, threads, 0, stream>>>(src, dst, mask, op);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaThreadSynchronize() );
......@@ -383,6 +386,7 @@ namespace cv
grid.y = divUp(src1.rows, threads.y);
device::transformSmart<T1, T2, D><<<grid, threads, 0, stream>>>(src1, src2, dst, mask, op);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaThreadSynchronize() );
......
modules/gpu/src/surf.cpp
View file @ deac5d97
......@@ -65,6 +65,7 @@ namespace cv { namespace gpu { namespace surf
dim3 calcBlockSize(int nIntervals);
void fasthessian_gpu(PtrStepf hessianBuffer, int x_size, int y_size, const dim3& threads);
void fasthessian_gpu_old(PtrStepf hessianBuffer, int x_size, int y_size, const dim3& threadsOld);
void nonmaxonly_gpu(PtrStepf hessianBuffer, int4* maxPosBuffer, unsigned int& maxCounter,
int x_size, int y_size, bool use_mask, const dim3& threads);
......@@ -75,6 +76,7 @@ namespace cv { namespace gpu { namespace surf
void find_orientation_gpu(KeyPoint_GPU* features, int nFeatures);
void compute_descriptors_gpu(const DevMem2Df& descriptors, const KeyPoint_GPU* features, int nFeatures);
void compute_descriptors_gpu_old(const DevMem2Df& descriptors, const KeyPoint_GPU* features, int nFeatures);
}}}
using namespace cv::gpu::surf;
......@@ -170,6 +172,10 @@ namespace
void detectKeypoints(GpuMat& keypoints)
{
typedef void (*fasthessian_t)(PtrStepf hessianBuffer, int x_size, int y_size, const dim3& threads);
const fasthessian_t fasthessian =
DeviceInfo().supports(COMPUTE_13) ? fasthessian_gpu : fasthessian_gpu_old;
dim3 threads = calcBlockSize(nIntervals);
for(int octave = 0; octave < nOctaves; ++octave)
{
......@@ -192,7 +198,7 @@ namespace
uploadConstant("cv::gpu::surf::c_border", border);
uploadConstant("cv::gpu::surf::c_step", step);
fasthessian_gpu(hessianBuffer, x_size, y_size, threads);
fasthessian(hessianBuffer, x_size, y_size, threads);
// Reset the candidate count.
maxCounter = 0;
......@@ -201,10 +207,13 @@ namespace
maxCounter = std::min(maxCounter, static_cast<unsigned int>(max_candidates));
fh_interp_extremum_gpu(hessianBuffer, maxPosBuffer.ptr<int4>(), maxCounter,
featuresBuffer.ptr<KeyPoint_GPU>(), featureCounter);
if (maxCounter > 0)
{
fh_interp_extremum_gpu(hessianBuffer, maxPosBuffer.ptr<int4>(), maxCounter,
featuresBuffer.ptr<KeyPoint_GPU>(), featureCounter);
featureCounter = std::min(featureCounter, static_cast<unsigned int>(max_features));
featureCounter = std::min(featureCounter, static_cast<unsigned int>(max_features));
}
}
if (featureCounter > 0)
......@@ -221,10 +230,16 @@ namespace
void computeDescriptors(const GpuMat& keypoints, GpuMat& descriptors, int descriptorSize)
{
typedef void (*compute_descriptors_t)(const DevMem2Df& descriptors,
const KeyPoint_GPU* features, int nFeatures);
const compute_descriptors_t compute_descriptors =
DeviceInfo().supports(COMPUTE_13) ? compute_descriptors_gpu : compute_descriptors_gpu_old;
if (keypoints.cols > 0)
{
descriptors.create(keypoints.cols, descriptorSize, CV_32F);
compute_descriptors_gpu(descriptors, keypoints.ptr<KeyPoint_GPU>(), keypoints.cols);
compute_descriptors(descriptors, keypoints.ptr<KeyPoint_GPU>(), keypoints.cols);
}
}
......
tests/gpu/src/brute_force_matcher.cpp
View file @ deac5d97
......@@ -384,6 +384,14 @@ void CV_GpuBruteForceMatcherTest::knnMatchTest( const GpuMat& query, const GpuMa
void CV_GpuBruteForceMatcherTest::radiusMatchTest( const GpuMat& query, const GpuMat& train )
{
bool atomics_ok = TargetArchs::builtWith(ATOMICS) && DeviceInfo().supports(ATOMICS);
if (!atomics_ok)
{
ts->printf(CvTS::CONSOLE, "\nCode and device atomics support is required for radiusMatch (CC >= 1.1)");
ts->set_failed_test_info(CvTS::FAIL_GENERIC);
return;
}
dmatcher.clear();
// test const version of match()
{
......@@ -501,15 +509,24 @@ void CV_GpuBruteForceMatcherTest::dataTest(int dim)
void CV_GpuBruteForceMatcherTest::run(int)
{
emptyDataTest();
dataTest(50);
dataTest(64);
dataTest(100);
dataTest(128);
dataTest(200);
dataTest(256);
dataTest(300);
try
{
emptyDataTest();
dataTest(50);
dataTest(64);
dataTest(100);
dataTest(128);
dataTest(200);
dataTest(256);
dataTest(300);
}
catch(cv::Exception& e)
{
if (!check_and_treat_gpu_exception(e, ts))
throw;
return;
}
}
CV_GpuBruteForceMatcherTest CV_GpuBruteForceMatcher_test;
tests/gpu/src/features2d.cpp
View file @ deac5d97
......@@ -154,7 +154,7 @@ void CV_GPU_SURFTest::compareKeypointSets(const vector<KeyPoint>& validKeypoints
return;
}
if (norm(validDescriptors.row(v), calcDescriptors.row(nearestIdx), NORM_L2) > 1.0f)
if (norm(validDescriptors.row(v), calcDescriptors.row(nearestIdx), NORM_L2) > 1.5f)
{
ts->printf(CvTS::LOG, "Bad descriptors accuracy.\n");
ts->set_failed_test_info( CvTS::FAIL_BAD_ACCURACY );
......@@ -221,10 +221,19 @@ void CV_GPU_SURFTest::regressionTest(SURF_GPU& fdetector)
void CV_GPU_SURFTest::run( int /*start_from*/ )
{
SURF_GPU fdetector;
try
{
SURF_GPU fdetector;
emptyDataTest(fdetector);
regressionTest(fdetector);
emptyDataTest(fdetector);
regressionTest(fdetector);
}
catch(cv::Exception& e)
{
if (!check_and_treat_gpu_exception(e, ts))
throw;
return;
}
}
CV_GPU_SURFTest CV_GPU_SURF_test;
tests/gpu/src/gputest_main.cpp
View file @ deac5d97
......@@ -43,15 +43,15 @@
CvTS test_system("gpu");
const char* blacklist[] =
{
"GPU-NppImageCanny", // NPP_TEXTURE_BIND_ERROR
0
};
//const char* blacklist[] =
//{
// "GPU-NVidia",
// 0
//};
int main( int argc, char** argv )
{
return test_system.run( argc, argv, blacklist );
return test_system.run( argc, argv );
}
/* End of file. */
tests/gpu/src/meanshift.cpp
View file @ deac5d97
......@@ -43,6 +43,9 @@
#include <iostream>
#include <string>
using namespace cv;
using namespace cv::gpu;
struct CV_GpuMeanShiftTest : public CvTest
{
......@@ -50,6 +53,14 @@ struct CV_GpuMeanShiftTest : public CvTest
void run(int)
{
bool cc12_ok = TargetArchs::builtWith(COMPUTE_12) && DeviceInfo().supports(COMPUTE_12);
if (!cc12_ok)
{
ts->printf(CvTS::CONSOLE, "\nCompute capability 1.2 is required");
ts->set_failed_test_info(CvTS::FAIL_GENERIC);
return;
}
int spatialRad = 30;
int colorRad = 30;
......@@ -134,6 +145,14 @@ struct CV_GpuMeanShiftProcTest : public CvTest
void run(int)
{
bool cc12_ok = TargetArchs::builtWith(COMPUTE_12) && DeviceInfo().supports(COMPUTE_12);
if (!cc12_ok)
{
ts->printf(CvTS::CONSOLE, "\nCompute capability 1.2 is required");
ts->set_failed_test_info(CvTS::FAIL_GENERIC);
return;
}
int spatialRad = 30;
int colorRad = 30;
......
tests/gpu/src/mssegmentation.cpp
View file @ deac5d97
......@@ -54,6 +54,14 @@ struct CV_GpuMeanShiftSegmentationTest : public CvTest {
{
try
{
bool cc12_ok = TargetArchs::builtWith(COMPUTE_12) && DeviceInfo().supports(COMPUTE_12);
if (!cc12_ok)
{
ts->printf(CvTS::CONSOLE, "\nCompute capability 1.2 is required");
ts->set_failed_test_info(CvTS::FAIL_GENERIC);
return;
}
Mat img_rgb = imread(string(ts->get_data_path()) + "meanshift/cones.png");
if (img_rgb.empty())
{
......
tests/gpu/src/operator_convert_to.cpp
View file @ deac5d97
......@@ -91,14 +91,14 @@ void CV_GpuMatOpConvertToTest::run(int /* start_from */)
Mat cpumatdst;
GpuMat gpumatdst;
cpumatsrc.convertTo(cpumatdst, dst_type);
gpumatsrc.convertTo(gpumatdst, dst_type);
cpumatsrc.convertTo(cpumatdst, dst_type, 0.5, 3.0);
gpumatsrc.convertTo(gpumatdst, dst_type, 0.5, 3.0);
double r = norm(cpumatdst, gpumatdst, NORM_INF);
if (r > 1)
{
ts->printf(CvTS::LOG,
"\nFAILED: SRC_TYPE=%sC%d DST_TYPE=%s NORM = %d\n",
"\nFAILED: SRC_TYPE=%sC%d DST_TYPE=%s NORM = %f\n",
types_str[i], c, types_str[j], r);
passed = false;
}
......
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