Chiebot-Mirror
/
opencv
8
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity

optimize roi loads

Browse Source 
only one thread load roi for all block
pull/158/head
marina.kolpakova 13 years ago
parent fdef0adf95
commit 30bce16ad6
4 changed files with 62 additions and 66 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. 42
      modules/gpu/perf/perf_objdetect.cpp
  2. 62
      modules/gpu/src/cuda/isf-sc.cu
  3. 2
      modules/gpu/src/softcascade.cpp
  4. 22
      modules/gpu/test/test_softcascade.cpp

42
modules/gpu/perf/perf_objdetect.cpp
Unescape View File

@ -176,33 +176,35 @@ PERF_TEST_P(SoftCascadeTest, detect,
{
if (runOnGpu)
{
cv::Mat cpu = readImage (GetParam().second);
cv::Mat cpu = readImage (GET_PARAM(1));
ASSERT_FALSE(cpu.empty());
cv::gpu::GpuMat colored(cpu);
cv::gpu::SoftCascade cascade;
ASSERT_TRUE(cascade.load(perf::TestBase::getDataPath(GetParam().first)));
ASSERT_TRUE(cascade.load(perf::TestBase::getDataPath(GET_PARAM(0))));
cv::gpu::GpuMat objectBoxes(1, 16384, CV_8UC1), rois(cascade.getRoiSize(), CV_8UC1);
rois.setTo(0);
cv::gpu::GpuMat sub(rois, cv::Rect(rois.cols / 4, rois.rows / 4,rois.cols / 2, rois.rows / 2));
sub.setTo(cv::Scalar::all(1));
cascade.detectMultiScale(colored, rois, objectBoxes);
cv::gpu::GpuMat objectBoxes(1, 16384, CV_8UC1), rois(cascade.getRoiSize(), CV_8UC1), trois;
rois.setTo(1);
cv::gpu::transpose(rois, trois);
cascade.detectMultiScale(colored, trois, objectBoxes);
TEST_CYCLE()
{
cascade.detectMultiScale(colored, rois, objectBoxes);
cascade.detectMultiScale(colored, trois, objectBoxes);
}
} else
}
else
{
cv::Mat colored = readImage(GetParam().second);
cv::Mat colored = readImage(GET_PARAM(1));
ASSERT_FALSE(colored.empty());
cv::SoftCascade cascade;
ASSERT_TRUE(cascade.load(getDataPath(GetParam().first)));
ASSERT_TRUE(cascade.load(getDataPath(GET_PARAM(0))));
std::vector<cv::Rect> rois;
std::vector<cv::Rect> rois, objectBoxes;
typedef cv::SoftCascade::Detection Detection;
std::vector<Detection>objectBoxes;
cascade.detectMultiScale(colored, rois, objectBoxes);
TEST_CYCLE()
@ -262,13 +264,16 @@ PERF_TEST_P(SoftCascadeTestRoi, detectInRoi,
sub.setTo(1);
}
cv::gpu::GpuMat trois;
cv::gpu::transpose(rois, trois);
cv::gpu::GpuMat curr = objectBoxes;
cascade.detectMultiScale(colored, rois, curr);
cascade.detectMultiScale(colored, trois, curr);
TEST_CYCLE()
{
curr = objectBoxes;
cascade.detectMultiScale(colored, rois, curr);
cascade.detectMultiScale(colored, trois, curr);
}
}
else
@ -301,7 +306,10 @@ PERF_TEST_P(SoftCascadeTestRoi, detectEachRoi,
sub.setTo(1);
cv::gpu::GpuMat curr = objectBoxes;
cascade.detectMultiScale(colored, rois, curr);
cv::gpu::GpuMat trois;
cv::gpu::transpose(rois, trois);
cascade.detectMultiScale(colored, trois, curr);
TEST_CYCLE()
{
@ -372,7 +380,7 @@ PERF_TEST_P(ImageAndCascade, ObjDetect_LBPClassifier,
cv::Mat img = readImage(GetParam().first, cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(img.empty());
if (PERF_RUN_GPU())
if (runOnGpu)
{
cv::gpu::CascadeClassifier_GPU d_cascade;
ASSERT_TRUE(d_cascade.load(perf::TestBase::getDataPath(GetParam().second)));

62
modules/gpu/src/cuda/isf-sc.cu
Unescape View File

@ -86,7 +86,6 @@ namespace icf {
}
texture<int, cudaTextureType2D, cudaReadModeElementType> thogluv;
texture<char, cudaTextureType2D, cudaReadModeElementType> troi;
template<bool isUp>
__device__ __forceinline__ float rescale(const Level& level, Node& node)
@ -130,11 +129,6 @@ namespace icf {
float relScale = level.relScale;
float farea = scaledRect.z * scaledRect.w;
dprintf("%d: feature %d box %d %d %d %d\n",threadIdx.x, (node.threshold >> 28), scaledRect.x, scaledRect.y,
scaledRect.z, scaledRect.w);
dprintf("%d: rescale: %f [%f %f] selected %f\n",threadIdx.x, level.relScale, level.scaling[0], level.scaling[1],
level.scaling[(node.threshold >> 28) > 6]);
// rescale
scaledRect.x = __float2int_rn(relScale * scaledRect.x);
scaledRect.y = __float2int_rn(relScale * scaledRect.y);
@ -146,15 +140,7 @@ namespace icf {
const float expected_new_area = farea * relScale * relScale;
float approx = __fdividef(sarea, expected_new_area);
dprintf("%d: new rect: %d box %d %d %d %d rel areas %f %f\n",threadIdx.x, (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];
dprintf("%d: approximation %f %d -> %f %f\n",threadIdx.x, approx, (node.threshold & 0x0FFFFFFFU), rootThreshold,
level.scaling[(node.threshold >> 28) > 6]);
float rootThreshold = (node.threshold & 0x0FFFFFFFU) * approx * level.scaling[(node.threshold >> 28) > 6];
return rootThreshold;
}
@ -162,33 +148,17 @@ namespace icf {
template<bool isUp>
__device__ __forceinline__ int get(int x, int y, uchar4 area)
{
dprintf("%d: feature box %d %d %d %d\n",threadIdx.x, area.x, area.y, area.z, area.w);
dprintf("%d: extract feature for: [%d %d] [%d %d] [%d %d] [%d %d]\n",threadIdx.x,
x + area.x, y + area.y, x + area.z, y + area.y, x + area.z,y + area.w,
x + area.x, y + area.w);
dprintf("%d: at point %d %d with offset %d\n", x, y, 0);
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);
int d = tex2D(thogluv, x + area.x, y + area.w);
dprintf("%d retruved integral values: %d %d %d %d\n",threadIdx.x, a, b, c, d);
return (a - b + c - d);
}
template<>
__device__ __forceinline__ int get<true>(int x, int y, uchar4 area)
{
dprintf("%d: feature box %d %d %d %d\n",threadIdx.x, area.x, area.y, area.z, area.w);
dprintf("%d: extract feature for: [%d %d] [%d %d] [%d %d] [%d %d]\n",threadIdx.x,
x + area.x, y + area.y, x + area.z, y + area.y, x + area.z,y + area.w,
x + area.x, y + area.w);
dprintf("%d: at point %d %d with offset %d\n", x, y, 0);
x += area.x;
y += area.y;
int a = tex2D(thogluv, x, y);
@ -196,11 +166,10 @@ namespace icf {
int c = tex2D(thogluv, x + area.z, y + area.w);
int d = tex2D(thogluv, x, y + area.w);
dprintf("%d retruved integral values: %d %d %d %d\n",threadIdx.x, a, b, c, d);
return (a - b + c - d);
}
texture<float2, cudaTextureType2D, cudaReadModeElementType> troi;
#if defined __CUDA_ARCH__ && __CUDA_ARCH__ >= 300
template<bool isUp>
__global__ void test_kernel_warp(const Level* levels, const Octave* octaves, const float* stages,
@ -210,12 +179,21 @@ namespace icf {
const int y = blockIdx.y * blockDim.y + threadIdx.y;
const int x = blockIdx.x;
__shared__ volatile char roiCache[8];
if (!threadIdx.y && !threadIdx.x)
{
((float2*)roiCache)[threadIdx.x] = tex2D(troi, blockIdx.y, x);
}
__syncthreads();
if (!roiCache[threadIdx.y]) return;
Level level = levels[downscales + blockIdx.z];
if(x >= level.workRect.x || y >= level.workRect.y) return;
if (!tex2D(troi, x, y)) return;
Octave octave = octaves[level.octave];
int st = octave.index * octave.stages;
const int stEnd = st + 1024;
@ -282,9 +260,9 @@ namespace icf {
// if (blockIdx.z != 31) return;
if(x >= level.workRect.x || y >= level.workRect.y) return;
int roi = tex2D(troi, x, y);
printf("%d\n", roi);
if (!roi) return;
// int roi = tex2D(troi, x, y);
// printf("%d\n", roi);
// if (!roi) return;
Octave octave = octaves[level.octave];
@ -357,8 +335,8 @@ namespace icf {
cudaChannelFormatDesc desc = cudaCreateChannelDesc<int>();
cudaSafeCall( cudaBindTexture2D(0, thogluv, hogluv.data, desc, hogluv.cols, hogluv.rows, hogluv.step));
cudaChannelFormatDesc desc_roi = cudaCreateChannelDesc<char>();
cudaSafeCall( cudaBindTexture2D(0, troi, roi.data, desc_roi, roi.cols, roi.rows, roi.step));
cudaChannelFormatDesc desc_roi = cudaCreateChannelDesc<float2>();
cudaSafeCall( cudaBindTexture2D(0, troi, roi.data, desc_roi, roi.cols / 8, roi.rows, roi.step));
test_kernel_warp<false><<<grid, block>>>(l, oct, st, nd, lf, det, max_det, ctr, 0);
cudaSafeCall( cudaGetLastError());
@ -391,8 +369,8 @@ namespace icf {
cudaChannelFormatDesc desc = cudaCreateChannelDesc<int>();
cudaSafeCall( cudaBindTexture2D(0, thogluv, hogluv.data, desc, hogluv.cols, hogluv.rows, hogluv.step));
cudaChannelFormatDesc desc_roi = cudaCreateChannelDesc<char>();
cudaSafeCall( cudaBindTexture2D(0, troi, roi.data, desc_roi, roi.cols, roi.rows, roi.step));
cudaChannelFormatDesc desc_roi = cudaCreateChannelDesc<float2>();
cudaSafeCall( cudaBindTexture2D(0, troi, roi.data, desc_roi, roi.cols / 8, roi.rows, roi.step));
if (scale >= downscales)
test_kernel_warp<true><<<grid, block>>>(l, oct, st, nd, lf, det, max_det, ctr, scale);

2
modules/gpu/src/softcascade.cpp
Unescape View File

@ -481,7 +481,7 @@ void cv::gpu::SoftCascade::detectMultiScale(const GpuMat& colored, const GpuMat&
CV_Assert(colored.type() == CV_8UC3);
// we guess user knows about shrincage
CV_Assert((rois.size() == getRoiSize()) && (rois.type() == CV_8UC1));
CV_Assert((rois.size().width == getRoiSize().height) && (rois.type() == CV_8UC1));
// only this window size allowed
CV_Assert(colored.cols == Filds::FRAME_WIDTH && colored.rows == Filds::FRAME_HEIGHT);

22
modules/gpu/test/test_softcascade.cpp
Unescape View File

@ -47,7 +47,7 @@
using cv::gpu::GpuMat;
// show detection results on input image with cv::imshow
//#define SHOW_DETECTIONS
#define SHOW_DETECTIONS
#if defined SHOW_DETECTIONS
# define SHOW(res) \
@ -154,26 +154,30 @@ GPU_TEST_P(SoftCascadeTest, detectInROI,
cv::gpu::SoftCascade cascade;
ASSERT_TRUE(cascade.load(cvtest::TS::ptr()->get_data_path() + GET_PARAM(0)));
GpuMat colored(coloredCpu), objectBoxes(1, 16384, CV_8UC1), rois(cascade.getRoiSize(), CV_8UC1);
GpuMat colored(coloredCpu), objectBoxes(1, 16384, CV_8UC1), rois(cascade.getRoiSize(), CV_8UC1), trois;
rois.setTo(0);
int nroi = GET_PARAM(2);
cv::Mat result(coloredCpu);
cv::RNG rng;
for (int i = 0; i < nroi; ++i)
{
cv::Rect r = getFromTable(rng(10));
GpuMat sub(rois, r);
sub.setTo(1);
r.x *= 4; r.y *= 4; r.width *= 4; r.height *= 4;
cv::rectangle(result, r, cv::Scalar(0, 0, 255, 255), 1);
}
cascade.detectMultiScale(colored, rois, objectBoxes);
cv::gpu::transpose(rois, trois);
cascade.detectMultiScale(colored, trois, objectBoxes);
///
cv::Mat dt(objectBoxes);
typedef cv::gpu::SoftCascade::Detection detection_t;
detection_t* dts = (detection_t*)dt.data;
cv::Mat result(coloredCpu);
printTotal(std::cout, dt.cols);
for (int i = 0; i < (int)(dt.cols / sizeof(detection_t)); ++i)
@ -204,8 +208,11 @@ GPU_TEST_P(SoftCascadeTest, detectInLevel,
GpuMat colored(coloredCpu), objectBoxes(1, 100 * sizeof(detection_t), CV_8UC1), rois(cascade.getRoiSize(), CV_8UC1);
rois.setTo(1);
cv::gpu::GpuMat trois;
cv::gpu::transpose(rois, trois);
int level = GET_PARAM(2);
cascade.detectMultiScale(colored, rois, objectBoxes, 1, level);
cascade.detectMultiScale(colored, trois, objectBoxes, 1, level);
cv::Mat dt(objectBoxes);
@ -246,6 +253,9 @@ TEST(SoftCascadeTest, detect)
GpuMat sub(rois, cv::Rect(rois.cols / 4, rois.rows / 4,rois.cols / 2, rois.rows / 2));
sub.setTo(cv::Scalar::all(1));
cascade.detectMultiScale(colored, rois, objectBoxes);
cv::gpu::GpuMat trois;
cv::gpu::transpose(rois, trois);
cascade.detectMultiScale(colored, trois, objectBoxes);
}
#endif
Write Preview
Loading…
Cancel
Save