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Commit 30bce16a authored by marina.kolpakova's avatar marina.kolpakova
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optimize roi loads 

only one thread load roi for all block
parent fdef0adf
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Showing with 63 additions and 66 deletions
modules/gpu/perf/perf_objdetect.cpp
View file @ 30bce16a
......@@ -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)));
cv::gpu::GpuMat objectBoxes(1, 16384, CV_8UC1), rois(cascade.getRoiSize(), CV_8UC1);
ASSERT_TRUE(cascade.load(perf::TestBase::getDataPath(GET_PARAM(0))));
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, objectBoxes;
std::vector<cv::Rect> rois;
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)));
......
modules/gpu/src/cuda/isf-sc.cu
View file @ 30bce16a
......@@ -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);
......
modules/gpu/src/softcascade.cpp
View file @ 30bce16a
......@@ -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);
......
modules/gpu/test/test_softcascade.cpp
View file @ 30bce16a
......@@ -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
\ No newline at end of file
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