提交 39da17a0 编写于 作者: M marina.kolpakova

Merge pull requst #177 from cuda-geek/another-one-integral-fix

......@@ -150,7 +150,7 @@ namespace cv { namespace gpu { namespace device
return true;
}
static __device__ __forceinline__ bool check(int, int, int, uint offset = 0)
static __device__ __forceinline__ bool check(int, int, int)
{
return true;
}
......
......@@ -357,18 +357,19 @@ namespace cv { namespace gpu { namespace device
#endif
}
void shfl_integral_gpu(PtrStepSzb img, PtrStepSz<unsigned int> integral, cudaStream_t stream)
void shfl_integral_gpu(const PtrStepSzb& img, PtrStepSz<unsigned int> integral, cudaStream_t stream)
{
{
// each thread handles 16 values, use 1 block/row
const int block = img.cols / 16;
// save, becouse step is actually can't be less 512 bytes
int block = integral.cols / 16;
// launch 1 block / row
const int grid = img.rows;
cudaSafeCall( cudaFuncSetCacheConfig(shfl_integral_horizontal, cudaFuncCachePreferL1) );
shfl_integral_horizontal<<<grid, block, 0, stream>>>((PtrStepSz<uint4>) img, (PtrStepSz<uint4>) integral);
shfl_integral_horizontal<<<grid, block, 0, stream>>>((const PtrStepSz<uint4>) img, (PtrStepSz<uint4>) integral);
cudaSafeCall( cudaGetLastError() );
}
......
......@@ -185,6 +185,7 @@ namespace cv { namespace gpu { namespace device
void connectedConmonents(PtrStepSz<int4> candidates, int ncandidates, PtrStepSz<int4> objects, int groupThreshold, float grouping_eps, unsigned int* nclasses)
{
if (!ncandidates) return;
int block = ncandidates;
int smem = block * ( sizeof(int) + sizeof(int4) );
disjoin<InSameComponint><<<1, block, smem>>>(candidates, objects, ncandidates, groupThreshold, grouping_eps, nclasses);
......
......@@ -177,7 +177,7 @@ namespace cv { namespace gpu { namespace device
return (HAAR_SIZE0 + HAAR_SIZE_INC * layer) << octave;
}
__global__ void icvCalcLayerDetAndTrace(PtrStepf det, PtrStepf trace, uint sumOffset)
__global__ void icvCalcLayerDetAndTrace(PtrStepf det, PtrStepf trace)
{
// Determine the indices
const int gridDim_y = gridDim.y / (c_nOctaveLayers + 2);
......@@ -198,9 +198,9 @@ namespace cv { namespace gpu { namespace device
if (size <= c_img_rows && size <= c_img_cols && i < samples_i && j < samples_j)
{
const float dx = icvCalcHaarPatternSum<3>(c_DX , 9, size, (i << c_octave), sumOffset + (j << c_octave));
const float dy = icvCalcHaarPatternSum<3>(c_DY , 9, size, (i << c_octave), sumOffset + (j << c_octave));
const float dxy = icvCalcHaarPatternSum<4>(c_DXY, 9, size, (i << c_octave), sumOffset + (j << c_octave));
const float dx = icvCalcHaarPatternSum<3>(c_DX , 9, size, (i << c_octave), (j << c_octave));
const float dy = icvCalcHaarPatternSum<3>(c_DY , 9, size, (i << c_octave), (j << c_octave));
const float dxy = icvCalcHaarPatternSum<4>(c_DXY, 9, size, (i << c_octave), (j << c_octave));
det.ptr(layer * c_layer_rows + i + margin)[j + margin] = dx * dy - 0.81f * dxy * dxy;
trace.ptr(layer * c_layer_rows + i + margin)[j + margin] = dx + dy;
......@@ -208,7 +208,7 @@ namespace cv { namespace gpu { namespace device
}
void icvCalcLayerDetAndTrace_gpu(const PtrStepf& det, const PtrStepf& trace, int img_rows, int img_cols,
int octave, int nOctaveLayers, const size_t sumOffset)
int octave, int nOctaveLayers)
{
const int min_size = calcSize(octave, 0);
const int max_samples_i = 1 + ((img_rows - min_size) >> octave);
......@@ -220,7 +220,7 @@ namespace cv { namespace gpu { namespace device
grid.x = divUp(max_samples_j, threads.x);
grid.y = divUp(max_samples_i, threads.y) * (nOctaveLayers + 2);
icvCalcLayerDetAndTrace<<<grid, threads>>>(det, trace, (uint)sumOffset);
icvCalcLayerDetAndTrace<<<grid, threads>>>(det, trace);
cudaSafeCall( cudaGetLastError() );
cudaSafeCall( cudaDeviceSynchronize() );
......@@ -233,7 +233,7 @@ namespace cv { namespace gpu { namespace device
struct WithMask
{
static __device__ bool check(int sum_i, int sum_j, int size, const uint offset)
static __device__ bool check(int sum_i, int sum_j, int size)
{
float ratio = (float)size / 9.0f;
......@@ -245,10 +245,10 @@ namespace cv { namespace gpu { namespace device
int dy2 = __float2int_rn(ratio * c_DM[3]);
float t = 0;
t += tex2D(maskSumTex, offset + sum_j + dx1, sum_i + dy1);
t -= tex2D(maskSumTex, offset + sum_j + dx1, sum_i + dy2);
t -= tex2D(maskSumTex, offset + sum_j + dx2, sum_i + dy1);
t += tex2D(maskSumTex, offset + sum_j + dx2, sum_i + dy2);
t += tex2D(maskSumTex, sum_j + dx1, sum_i + dy1);
t -= tex2D(maskSumTex, sum_j + dx1, sum_i + dy2);
t -= tex2D(maskSumTex, sum_j + dx2, sum_i + dy1);
t += tex2D(maskSumTex, sum_j + dx2, sum_i + dy2);
d += t * c_DM[4] / ((dx2 - dx1) * (dy2 - dy1));
......@@ -258,7 +258,7 @@ namespace cv { namespace gpu { namespace device
template <typename Mask>
__global__ void icvFindMaximaInLayer(const PtrStepf det, const PtrStepf trace, int4* maxPosBuffer,
unsigned int* maxCounter, const uint maskOffset)
unsigned int* maxCounter)
{
#if __CUDA_ARCH__ && __CUDA_ARCH__ >= 110
......@@ -299,7 +299,7 @@ namespace cv { namespace gpu { namespace device
const int sum_i = (i - ((size >> 1) >> c_octave)) << c_octave;
const int sum_j = (j - ((size >> 1) >> c_octave)) << c_octave;
if (Mask::check(sum_i, sum_j, size, maskOffset))
if (Mask::check(sum_i, sum_j, size))
{
// Check to see if we have a max (in its 26 neighbours)
const bool condmax = val0 > N9[localLin - 1 - blockDim.x - zoff]
......@@ -351,7 +351,7 @@ namespace cv { namespace gpu { namespace device
}
void icvFindMaximaInLayer_gpu(const PtrStepf& det, const PtrStepf& trace, int4* maxPosBuffer, unsigned int* maxCounter,
int img_rows, int img_cols, int octave, bool use_mask, int nOctaveLayers, const size_t maskOffset)
int img_rows, int img_cols, int octave, bool use_mask, int nOctaveLayers)
{
const int layer_rows = img_rows >> octave;
const int layer_cols = img_cols >> octave;
......@@ -367,9 +367,9 @@ namespace cv { namespace gpu { namespace device
const size_t smem_size = threads.x * threads.y * 3 * sizeof(float);
if (use_mask)
icvFindMaximaInLayer<WithMask><<<grid, threads, smem_size>>>(det, trace, maxPosBuffer, maxCounter, (uint)maskOffset);
icvFindMaximaInLayer<WithMask><<<grid, threads, smem_size>>>(det, trace, maxPosBuffer, maxCounter);
else
icvFindMaximaInLayer<WithOutMask><<<grid, threads, smem_size>>>(det, trace, maxPosBuffer, maxCounter, 0);
icvFindMaximaInLayer<WithOutMask><<<grid, threads, smem_size>>>(det, trace, maxPosBuffer, maxCounter);
cudaSafeCall( cudaGetLastError() );
......
......@@ -537,7 +537,7 @@ namespace cv { namespace gpu { namespace device
{
namespace imgproc
{
void shfl_integral_gpu(PtrStepSzb img, PtrStepSz<unsigned int> integral, cudaStream_t stream);
void shfl_integral_gpu(const PtrStepSzb& img, PtrStepSz<unsigned int> integral, cudaStream_t stream);
}
}}}
......@@ -553,44 +553,26 @@ void cv::gpu::integralBuffered(const GpuMat& src, GpuMat& sum, GpuMat& buffer, S
src.locateROI(whole, offset);
if (info.supports(WARP_SHUFFLE_FUNCTIONS) && src.cols <= 2048)
if (info.supports(WARP_SHUFFLE_FUNCTIONS) && src.cols <= 2048
&& offset.x % 16 == 0 && ((src.cols + 63) / 64) * 64 <= (src.step - offset.x))
{
GpuMat srcAlligned;
ensureSizeIsEnough(((src.rows + 7) / 8) * 8, ((src.cols + 63) / 64) * 64, CV_32SC1, buffer);
if (src.cols % 16 == 0 && src.rows % 8 == 0 && offset.x % 16 == 0 && offset.y % 8 == 0)
srcAlligned = src;
else
{
ensureSizeIsEnough(((src.rows + 7) / 8) * 8, ((src.cols + 15) / 16) * 16, src.type(), buffer);
GpuMat inner = buffer(Rect(0, 0, src.cols, src.rows));
if (s)
{
s.enqueueMemSet(buffer, Scalar::all(0));
s.enqueueCopy(src, inner);
}
else
{
buffer.setTo(Scalar::all(0));
src.copyTo(inner);
}
srcAlligned = buffer;
}
sum.create(srcAlligned.rows + 1, srcAlligned.cols + 4, CV_32SC1);
cv::gpu::device::imgproc::shfl_integral_gpu(src, buffer, stream);
sum.create(src.rows + 1, src.cols + 1, CV_32SC1);
if (s)
s.enqueueMemSet(sum, Scalar::all(0));
else
sum.setTo(Scalar::all(0));
GpuMat inner = sum(Rect(4, 1, srcAlligned.cols, srcAlligned.rows));
cv::gpu::device::imgproc::shfl_integral_gpu(srcAlligned, inner, stream);
GpuMat inner = sum(Rect(1, 1, src.cols, src.rows));
GpuMat res = buffer(Rect(0, 0, src.cols, src.rows));
sum = sum(Rect(3, 0, src.cols + 1, src.rows + 1));
if (s)
s.enqueueCopy(res, inner);
else
res.copyTo(inner);
}
else
{
......
......@@ -75,10 +75,10 @@ namespace cv { namespace gpu { namespace device
size_t bindMaskSumTex(PtrStepSz<unsigned int> maskSum);
void icvCalcLayerDetAndTrace_gpu(const PtrStepf& det, const PtrStepf& trace, int img_rows, int img_cols,
int octave, int nOctaveLayers, const size_t sumOffset);
int octave, int nOctaveLayer);
void icvFindMaximaInLayer_gpu(const PtrStepf& det, const PtrStepf& trace, int4* maxPosBuffer, unsigned int* maxCounter,
int img_rows, int img_cols, int octave, bool use_mask, int nLayers, const size_t maskOffset);
int img_rows, int img_cols, int octave, bool use_mask, int nLayers);
void icvInterpolateKeypoint_gpu(const PtrStepf& det, const int4* maxPosBuffer, unsigned int maxCounter,
float* featureX, float* featureY, int* featureLaplacian, int* featureOctave, float* featureSize, float* featureHessian,
......@@ -146,8 +146,8 @@ namespace
loadGlobalConstants(maxCandidates, maxFeatures, img_rows, img_cols, surf_.nOctaveLayers, static_cast<float>(surf_.hessianThreshold));
bindImgTex(img);
integralBuffered(img, surf_.sum, surf_.intBuffer);
integralBuffered(img, surf_.sum, surf_.intBuffer);
sumOffset = bindSumTex(surf_.sum);
if (use_mask)
......@@ -174,10 +174,10 @@ namespace
loadOctaveConstants(octave, layer_rows, layer_cols);
icvCalcLayerDetAndTrace_gpu(surf_.det, surf_.trace, img_rows, img_cols, octave, surf_.nOctaveLayers, sumOffset);
icvCalcLayerDetAndTrace_gpu(surf_.det, surf_.trace, img_rows, img_cols, octave, surf_.nOctaveLayers);
icvFindMaximaInLayer_gpu(surf_.det, surf_.trace, surf_.maxPosBuffer.ptr<int4>(), counters.ptr<unsigned int>() + 1 + octave,
img_rows, img_cols, octave, use_mask, surf_.nOctaveLayers, maskOffset);
img_rows, img_cols, octave, use_mask, surf_.nOctaveLayers);
unsigned int maxCounter;
cudaSafeCall( cudaMemcpy(&maxCounter, counters.ptr<unsigned int>() + 1 + octave, sizeof(unsigned int), cudaMemcpyDeviceToHost) );
......
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