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add detection storing

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pull/158/head
marina.kolpakova 12 years ago
parent 8108bd30fe
commit 72b499df00
3 changed files with 30 additions and 47 deletions
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  1. 4
      modules/gpu/perf/perf_objdetect.cpp
  2. 59
      modules/gpu/src/cuda/isf-sc.cu
  3. 14
      modules/gpu/src/softcascade.cpp

4
modules/gpu/perf/perf_objdetect.cpp
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@ -104,7 +104,7 @@ PERF_TEST_P(SoftCascade, detect, Values<pair_string>(make_pair("cv/cascadeandhog
cv::gpu::SoftCascade cascade;
ASSERT_TRUE(cascade.load(perf::TestBase::getDataPath(GetParam().first)));
cv::gpu::GpuMat rois, objectBoxes(1, 1000, CV_8UC1);
cv::gpu::GpuMat rois, objectBoxes(1, 1000, CV_8UC4);
cascade.detectMultiScale(colored, rois, objectBoxes);
TEST_CYCLE()
@ -117,7 +117,7 @@ PERF_TEST_P(SoftCascade, detect, Values<pair_string>(make_pair("cv/cascadeandhog
ASSERT_FALSE(colored.empty());
cv::SoftCascade cascade;
ASSERT_TRUE(cascade.load(GetParam().first));
ASSERT_TRUE(cascade.load(getDataPath(GetParam().first)));
std::vector<cv::Rect> rois, objectBoxes;
cascade.detectMultiScale(colored, rois, objectBoxes);

59
modules/gpu/src/cuda/isf-sc.cu
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@ -57,14 +57,6 @@
namespace cv { namespace gpu { namespace device {
namespace icf {
// enum {
// HOG_BINS = 6,
// HOG_LUV_BINS = 10,
// WIDTH = 640,
// HEIGHT = 480,
// GREY_OFFSET = HEIGHT * HOG_LUV_BINS
// };
// ToDo: use textures or ancached load instruction.
__global__ void magToHist(const uchar* __restrict__ mag,
const float* __restrict__ angle, const int angPitch,
@ -94,13 +86,6 @@ namespace icf {
}
texture<int, cudaTextureType2D, cudaReadModeElementType> thogluv;
// ToDo: do it in load time
// __device__ __forceinline__ float rescale(const Level& level, uchar4& scaledRect, const Node& node)
// {
// scaledRect = node.rect;
// return (float)(node.threshold & 0x0FFFFFFFU);
// }
__device__ __forceinline__ float rescale(const Level& level, uchar4& scaledRect, const Node& node)
{
float relScale = level.relScale;
@ -119,17 +104,12 @@ namespace icf {
float sarea = (scaledRect.z - scaledRect.x) * (scaledRect.w - scaledRect.y);
float approx = 1.f;
// if (fabs(farea - 0.f) > FLT_EPSILON && fabs(farea - 0.f) > FLT_EPSILON)
{
const float expected_new_area = farea * relScale * relScale;
approx = sarea / expected_new_area;
}
const float expected_new_area = farea * relScale * relScale;
float approx = sarea / expected_new_area;
dprintf("new rect: %d box %d %d %d %d rel areas %f %f\n", (node.threshold >> 28),
scaledRect.x, scaledRect.y, scaledRect.z, scaledRect.w, farea * relScale * relScale, sarea);
float rootThreshold = (node.threshold & 0x0FFFFFFFU) * approx;
rootThreshold *= level.scaling[(node.threshold >> 28) > 6];
@ -139,7 +119,7 @@ namespace icf {
return rootThreshold;
}
__device__ __forceinline__ int get(const int x, int y, int channel, uchar4 area)
__device__ __forceinline__ int get(const int x, int y, uchar4 area)
{
dprintf("feature box %d %d %d %d ", area.x, area.y, area.z, area.w);
@ -149,9 +129,6 @@ namespace icf {
x + area.x, y + area.w);
dprintf("at point %d %d with offset %d\n", x, y, 0);
int offset = channel * 121;
y += offset;
int a = tex2D(thogluv, x + area.x, y + area.y);
int b = tex2D(thogluv, x + area.z, y + area.y);
int c = tex2D(thogluv, x + area.z, y + area.w);
@ -163,7 +140,7 @@ namespace icf {
}
__global__ void test_kernel(const Level* levels, const Octave* octaves, const float* stages,
const Node* nodes, const float* leaves, PtrStepSz<uchar4> objects)
const Node* nodes, const float* leaves, PtrStepSz<uchar4> objects, uint* ctr)
{
const int y = blockIdx.y * blockDim.y + threadIdx.y;
const int x = blockIdx.x * blockDim.x + threadIdx.x;
@ -179,7 +156,7 @@ namespace icf {
float confidence = 0.f;
// #pragma unroll 8
// #pragma unroll 2
for(; st < stEnd; ++st)
{
dprintf("\n\nstage: %d\n", st);
@ -190,7 +167,7 @@ namespace icf {
node.threshold >> 28, node.threshold & 0x0FFFFFFFU);
float threshold = rescale(level, node.rect, node);
int sum = get(x, y, (node.threshold >> 28), node.rect);
int sum = get(x, y + (node.threshold >> 28) * 121, node.rect);
dprintf("Node: [%d %d %d %d] %f\n", node.rect.x, node.rect.y, node.rect.z,
node.rect.w, threshold);
@ -200,29 +177,30 @@ namespace icf {
node = nodes[nId + next];
threshold = rescale(level, node.rect, node);
sum = get(x, y, (node.threshold >> 28), node.rect);
sum = get(x, y + (node.threshold >> 28) * 121, node.rect);
const int lShift = (next - 1) * 2 + (int)(sum >= threshold);
float impact = leaves[st * 4 + lShift];
confidence += impact;
if (confidence <= stages[st]) st = stEnd + 1;
if (confidence <= stages[st]) st = stEnd + 10;
dprintf("decided: %d (%d >= %f) %d %f\n\n" ,next, sum, threshold, lShift, impact);
dprintf("extracted stage: %f\n", stages[st]);
dprintf("computed score: %f\n\n", confidence);
}
// if (st == stEnd)
// printf("%d %d %d\n", x, y, st);
uchar4 val;
val.x = (int)confidence;
if (x == y) objects(0, threadIdx.x) = val;
if(st == stEnd)
{
int idx = atomicInc(ctr, objects.cols);
uchar4 val;
val.x = x * 4;
objects(0, idx) = val;
}
}
void detect(const PtrStepSzb& levels, const PtrStepSzb& octaves, const PtrStepSzf& stages,
const PtrStepSzb& nodes, const PtrStepSzf& leaves, const PtrStepSzi& hogluv, PtrStepSz<uchar4> objects)
const PtrStepSzb& nodes, const PtrStepSzf& leaves, const PtrStepSzi& hogluv,
PtrStepSz<uchar4> objects, PtrStepSzi counter)
{
int fw = 160;
int fh = 120;
@ -235,11 +213,12 @@ namespace icf {
const float* st = (const float*)stages.ptr();
const Node* nd = (const Node*)nodes.ptr();
const float* lf = (const float*)leaves.ptr();
uint* ctr = (uint*)counter.ptr();
cudaChannelFormatDesc desc = cudaCreateChannelDesc<int>();
cudaSafeCall( cudaBindTexture2D(0, thogluv, hogluv.data, desc, hogluv.cols, hogluv.rows, hogluv.step));
test_kernel<<<grid, block>>>(l, oct, st, nd, lf, objects);
test_kernel<<<grid, block>>>(l, oct, st, nd, lf, objects, ctr);
cudaSafeCall( cudaGetLastError());
cudaSafeCall( cudaDeviceSynchronize());

14
modules/gpu/src/softcascade.cpp
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@ -60,7 +60,8 @@ namespace icf {
void fillBins(cv::gpu::PtrStepSzb hogluv, const cv::gpu::PtrStepSzf& nangle,
const int fw, const int fh, const int bins);
void detect(const PtrStepSzb& levels, const PtrStepSzb& octaves, const PtrStepSzf& stages,
const PtrStepSzb& nodes, const PtrStepSzf& leaves, const PtrStepSzi& hogluv, PtrStepSz<uchar4> objects);
const PtrStepSzb& nodes, const PtrStepSzf& leaves, const PtrStepSzi& hogluv, PtrStepSz<uchar4> objects,
PtrStepSzi counter);
}
}}}
@ -75,6 +76,7 @@ struct cv::gpu::SoftCascade::Filds
shrunk.create(FRAME_HEIGHT / 4 * HOG_LUV_BINS, FRAME_WIDTH / 4, CV_8UC1);
integralBuffer.create(shrunk.rows + 1 * HOG_LUV_BINS, shrunk.cols + 1, CV_32SC1);
hogluv.create((FRAME_HEIGHT / 4 + 1) * HOG_LUV_BINS, FRAME_WIDTH / 4 + 1, CV_32SC1);
detCounter.create(1,1, CV_32SC1);
}
// scales range
@ -90,6 +92,8 @@ struct cv::gpu::SoftCascade::Filds
GpuMat leaves;
GpuMat levels;
GpuMat detCounter;
// preallocated buffer 640x480x10 for hogluv + 640x480 got gray
GpuMat plane;
@ -127,7 +131,8 @@ struct cv::gpu::SoftCascade::Filds
bool fill(const FileNode &root, const float mins, const float maxs);
void detect(cv::gpu::GpuMat objects, cudaStream_t stream) const
{
device::icf::detect(levels, octaves, stages, nodes, leaves, hogluv, objects);
cudaMemset(detCounter.data, 0, detCounter.step * detCounter.rows * sizeof(int));
device::icf::detect(levels, octaves, stages, nodes, leaves, hogluv, objects , detCounter);
}
private:
@ -506,14 +511,13 @@ void cv::gpu::SoftCascade::detectMultiScale(const GpuMat& colored, const GpuMat&
GpuMat sum(flds.hogluv, cv::Rect(0, (fh + 1) * i, fw + 1, fh + 1));
cv::gpu::integralBuffered(channel, sum, flds.integralBuffer);
}
#endif
cudaStream_t stream = StreamAccessor::getStream(s);
// detection
flds.detect(objects, stream);
// // flds.storage.frame(colored, stream);
// cv::Mat out(flds.detCounter);
// std::cout << out << std::endl;
}
#endif
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