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use fast integral for soft cascade

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This commit is contained in:
marina.kolpakova 2012-11-05 13:52:24 +04:00
parent ac5cd48279
commit df392cc830
4 changed files with 102 additions and 17 deletions
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83
modules/gpu/src/cuda/integral_image.cu
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@ -383,6 +383,89 @@ namespace cv { namespace gpu { namespace device
if (stream == 0)
cudaSafeCall( cudaDeviceSynchronize() );
}
__global__ void shfl_integral_vertical(PtrStepSz<unsigned int> buffer, PtrStepSz<unsigned int> integral)
{
#if defined(__CUDA_ARCH__) && (__CUDA_ARCH__ >= 300)
__shared__ unsigned int sums[32][9];
const int tidx = blockIdx.x * blockDim.x + threadIdx.x;
const int lane_id = tidx % 8;
if (tidx >= integral.cols)
return;
sums[threadIdx.x][threadIdx.y] = 0;
__syncthreads();
unsigned int stepSum = 0;
for (int y = threadIdx.y; y < integral.rows; y += blockDim.y)
{
unsigned int* p = buffer.ptr(y) + tidx;
unsigned int* dst = integral.ptr(y + 1) + tidx + 1;
unsigned int sum = *p;
sums[threadIdx.x][threadIdx.y] = sum;
__syncthreads();
// place into SMEM
// shfl scan reduce the SMEM, reformating so the column
// sums are computed in a warp
// then read out properly
const int j = threadIdx.x % 8;
const int k = threadIdx.x / 8 + threadIdx.y * 4;
int partial_sum = sums[k][j];
for (int i = 1; i <= 8; i *= 2)
{
int n = __shfl_up(partial_sum, i, 32);
if (lane_id >= i)
partial_sum += n;
}
sums[k][j] = partial_sum;
__syncthreads();
if (threadIdx.y > 0)
sum += sums[threadIdx.x][threadIdx.y - 1];
sum += stepSum;
stepSum += sums[threadIdx.x][blockDim.y - 1];
__syncthreads();
*dst = sum;
}
#endif
}
// used for frame preprocessing before Soft Cascade evaluation: no synchronization needed
// ToDo: partial dy
void shfl_integral_gpu_buffered(PtrStepSzb img, PtrStepSz<uint4> buffer, PtrStepSz<unsigned int> integral,
int blockStep, cudaStream_t stream)
{
{
const int block = blockStep;
const int grid = img.rows;
cudaSafeCall( cudaFuncSetCacheConfig(shfl_integral_horizontal, cudaFuncCachePreferL1) );
shfl_integral_horizontal<<<grid, block, 0, stream>>>((PtrStepSz<uint4>) img, buffer);
cudaSafeCall( cudaGetLastError() );
}
{
const dim3 block(32, 8);
const dim3 grid(divUp(integral.cols, block.x), 1);
shfl_integral_vertical<<<grid, block, 0, stream>>>((PtrStepSz<uint>)buffer, integral);
cudaSafeCall( cudaGetLastError() );
}
}
}
}}}

4
modules/gpu/src/cuda/isf-sc.cu
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@ -198,14 +198,14 @@ namespace icf {
Node node = nodes[nId];
float threshold = rescale<isUp>(level, node);
int sum = get<isUp>(x, y + (node.threshold >> 28) * 121, node.rect);
int sum = get<isUp>(x, y + (node.threshold >> 28) * 120, node.rect);
int next = 1 + (int)(sum >= threshold);
dprintf("%d: go: %d (%d >= %f)\n\n" ,threadIdx.x, next, sum, threshold);
node = nodes[nId + next];
threshold = rescale<isUp>(level, node);
sum = get<isUp>(x, y + (node.threshold >> 28) * 121, node.rect);
sum = get<isUp>(x, y + (node.threshold >> 28) * 120, node.rect);
const int lShift = (next - 1) * 2 + (int)(sum >= threshold);
float impact = leaves[(st + threadIdx.x) * 4 + lShift];

31
modules/gpu/src/softcascade.cpp
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@ -76,14 +76,20 @@ cv::gpu::device::icf::Level::Level(int idx, const Octave& oct, const float scale
}
namespace cv { namespace gpu { namespace device {
namespace icf {
void fillBins(cv::gpu::PtrStepSzb hogluv, const cv::gpu::PtrStepSzf& nangle,
const int fw, const int fh, const int bins);
}
namespace imgproc
{
void shfl_integral_gpu(PtrStepSzb img, PtrStepSz<unsigned int> integral, cudaStream_t stream);
namespace imgproc {
void shfl_integral_gpu_buffered(PtrStepSzb, PtrStepSz<uint4>, PtrStepSz<unsigned int>, int, cudaStream_t);
template <typename T>
void resize_gpu(PtrStepSzb src, PtrStepSzb srcWhole, int xoff, int yoff, float fx, float fy,
PtrStepSzb dst, int interpolation, cudaStream_t stream);
}
}}}
struct cv::gpu::SoftCascade::Filds
@ -319,9 +325,13 @@ struct cv::gpu::SoftCascade::Filds
plane.create(FRAME_HEIGHT * (HOG_LUV_BINS + 1), FRAME_WIDTH, CV_8UC1);
fplane.create(FRAME_HEIGHT * 6, FRAME_WIDTH, CV_32FC1);
luv.create(FRAME_HEIGHT, FRAME_WIDTH, CV_8UC3);
shrunk.create(FRAME_HEIGHT / shr * HOG_LUV_BINS, FRAME_WIDTH / shr, CV_8UC1);
integralBuffer.create(1 , (shrunk.rows + 1) * HOG_LUV_BINS * (shrunk.cols + 1), CV_32SC1);
hogluv.create((FRAME_HEIGHT / shr + 1) * HOG_LUV_BINS, FRAME_WIDTH / shr + 64, CV_32SC1);
integralBuffer.create(shrunk.rows, shrunk.cols, CV_32SC1);
hogluv.create((FRAME_HEIGHT / shr) * HOG_LUV_BINS + 1, FRAME_WIDTH / shr + 1, CV_32SC1);
hogluv.setTo(cv::Scalar::all(0));
detCounter.create(1,1, CV_32SC1);
octaves.upload(hoctaves);
@ -432,16 +442,7 @@ private:
GpuMat channels(plane, cv::Rect(0, 0, fw, fh * Filds::HOG_LUV_BINS));
cv::gpu::resize(channels, shrunk, cv::Size(), 0.25, 0.25, CV_INTER_AREA);
fw /= shrinkage;
fh /= shrinkage;
for(int i = 0; i < Filds::HOG_LUV_BINS; ++i)
{
GpuMat channel(shrunk, cv::Rect(0, fh * i, fw, fh ));
GpuMat sum(hogluv, cv::Rect(0, (fh + 1) * i, fw + 1, fh + 1));
cv::gpu::integralBuffered(channel, sum, integralBuffer);
}
device::imgproc::shfl_integral_gpu_buffered(shrunk, integralBuffer, hogluv, 12, 0);
}
public:

1
modules/gpu/test/test_softcascade.cpp
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@ -271,6 +271,7 @@ GPU_TEST_P(SoftCascadeTestAll, detect,
ASSERT_EQ(detections.cols / sizeof(Detection) ,3670U);
}
//ToDo: fix me
GPU_TEST_P(SoftCascadeTestAll, detectOnIntegral,
ALL_DEVICES
)