Merge pull request #1061 from bitwangyaoyao:2.4_fix2

pull/1051/merge
Roman Donchenko 12 years ago committed by OpenCV Buildbot
commit c8cd2cf601
  1. 16
      modules/ocl/src/hog.cpp
  2. 20
      modules/ocl/src/opencl/objdetect_hog.cl
  3. 37
      modules/ocl/src/opencl/stereobm.cl
  4. 2
      modules/ocl/test/main.cpp
  5. 6
      modules/ocl/test/test_objdetect.cpp
  6. 2
      samples/ocl/CMakeLists.txt
  7. 108
      samples/ocl/clahe.cpp
  8. 7
      samples/ocl/facedetect.cpp
  9. 10
      samples/ocl/hog.cpp
  10. 16
      samples/ocl/stereo_match.cpp

@ -1816,8 +1816,14 @@ void cv::ocl::device::hog::normalize_hists(int nbins,
openCLExecuteKernel(clCxt, &objdetect_hog, kernelName, globalThreads,
localThreads, args, -1, -1, "-D CPU");
else
{
cl_kernel kernel = openCLGetKernelFromSource(clCxt, &objdetect_hog, kernelName);
int wave_size = queryDeviceInfo<WAVEFRONT_SIZE, int>(kernel);
char opt[32] = {0};
sprintf(opt, "-D WAVE_SIZE=%d", wave_size);
openCLExecuteKernel(clCxt, &objdetect_hog, kernelName, globalThreads,
localThreads, args, -1, -1);
localThreads, args, -1, -1, opt);
}
}
void cv::ocl::device::hog::classify_hists(int win_height, int win_width,
@ -1879,8 +1885,14 @@ void cv::ocl::device::hog::classify_hists(int win_height, int win_width,
openCLExecuteKernel(clCxt, &objdetect_hog, kernelName, globalThreads,
localThreads, args, -1, -1, "-D CPU");
else
{
cl_kernel kernel = openCLGetKernelFromSource(clCxt, &objdetect_hog, kernelName);
int wave_size = queryDeviceInfo<WAVEFRONT_SIZE, int>(kernel);
char opt[32] = {0};
sprintf(opt, "-D WAVE_SIZE=%d", wave_size);
openCLExecuteKernel(clCxt, &objdetect_hog, kernelName, globalThreads,
localThreads, args, -1, -1);
localThreads, args, -1, -1, opt);
}
}
void cv::ocl::device::hog::extract_descrs_by_rows(int win_height, int win_width,

@ -133,7 +133,9 @@ __kernel void compute_hists_lut_kernel(
final_hist[(cell_x * 2 + cell_y) * cnbins + bin_id] =
hist_[0] + hist_[1] + hist_[2];
}
#ifdef CPU
barrier(CLK_LOCAL_MEM_FENCE);
#endif
int tid = (cell_y * CELLS_PER_BLOCK_Y + cell_x) * 12 + cell_thread_x;
if ((tid < cblock_hist_size) && (gid < blocks_total))
@ -225,8 +227,9 @@ __kernel void compute_hists_kernel(
final_hist[(cell_x * 2 + cell_y) * cnbins + bin_id] =
hist_[0] + hist_[1] + hist_[2];
}
#ifdef CPU
barrier(CLK_LOCAL_MEM_FENCE);
#endif
int tid = (cell_y * CELLS_PER_BLOCK_Y + cell_x) * 12 + cell_thread_x;
if ((tid < cblock_hist_size) && (gid < blocks_total))
{
@ -318,6 +321,10 @@ float reduce_smem(volatile __local float* smem, int size)
if (tid < 32)
{
if (size >= 64) smem[tid] = sum = sum + smem[tid + 32];
#if WAVE_SIZE < 32
} barrier(CLK_LOCAL_MEM_FENCE);
if (tid < 16) {
#endif
if (size >= 32) smem[tid] = sum = sum + smem[tid + 16];
if (size >= 16) smem[tid] = sum = sum + smem[tid + 8];
if (size >= 8) smem[tid] = sum = sum + smem[tid + 4];
@ -418,6 +425,9 @@ __kernel void classify_hists_180_kernel(
{
smem[tid] = product = product + smem[tid + 32];
}
#if WAVE_SIZE < 32
barrier(CLK_LOCAL_MEM_FENCE);
#endif
if (tid < 16)
{
smem[tid] = product = product + smem[tid + 16];
@ -487,6 +497,10 @@ __kernel void classify_hists_252_kernel(
if (tid < 32)
{
smem[tid] = product = product + smem[tid + 32];
#if WAVE_SIZE < 32
} barrier(CLK_LOCAL_MEM_FENCE);
if (tid < 16) {
#endif
smem[tid] = product = product + smem[tid + 16];
smem[tid] = product = product + smem[tid + 8];
smem[tid] = product = product + smem[tid + 4];
@ -553,6 +567,10 @@ __kernel void classify_hists_kernel(
if (tid < 32)
{
smem[tid] = product = product + smem[tid + 32];
#if WAVE_SIZE < 32
} barrier(CLK_LOCAL_MEM_FENCE);
if (tid < 16) {
#endif
smem[tid] = product = product + smem[tid + 16];
smem[tid] = product = product + smem[tid + 8];
smem[tid] = product = product + smem[tid + 4];

@ -258,27 +258,13 @@ float sobel(__global unsigned char *input, int x, int y, int rows, int cols)
float CalcSums(__local float *cols, __local float *cols_cache, int winsz)
{
float cache = 0;
float cache2 = 0;
int winsz2 = winsz/2;
int x = get_local_id(0);
int group_size_x = get_local_size(0);
unsigned int cache = cols[0];
for(int i = 1; i <= winsz2; i++)
#pragma unroll
for(int i = 1; i <= winsz; i++)
cache += cols[i];
cols_cache[0] = cache;
barrier(CLK_LOCAL_MEM_FENCE);
if (x < group_size_x - winsz2)
cache2 = cols_cache[winsz2];
else
for(int i = winsz2 + 1; i < winsz; i++)
cache2 += cols[i];
return cols[0] + cache + cache2;
return cache;
}
#define RpT (2 * ROWSperTHREAD) // got experimentally
@ -301,8 +287,7 @@ __kernel void textureness_kernel(__global unsigned char *disp, int disp_rows, in
int beg_row = group_id_y * RpT;
int end_row = min(beg_row + RpT, disp_rows);
// if (x < disp_cols)
// {
int y = beg_row;
float sum = 0;
@ -340,11 +325,15 @@ __kernel void textureness_kernel(__global unsigned char *disp, int disp_rows, in
}
barrier(CLK_LOCAL_MEM_FENCE);
float sum_win = CalcSums(cols, cols_cache + local_id_x, winsz) * 255;
if (sum_win < threshold)
disp[y * disp_step + x] = 0;
if (x < disp_cols)
{
float sum_win = CalcSums(cols, cols_cache + local_id_x, winsz) * 255;
if (sum_win < threshold)
disp[y * disp_step + x] = 0;
}
barrier(CLK_LOCAL_MEM_FENCE);
}
// }
}

@ -118,6 +118,8 @@ int main(int argc, char **argv)
setDevice(oclinfo[pid], device);
setBinaryDiskCache(CACHE_UPDATE);
cout << "Device type:" << type << endl << "Device name:" << oclinfo[pid].DeviceName[device] << endl;
return RUN_ALL_TESTS();
}

@ -146,17 +146,17 @@ TEST_P(HOG, Detect)
if (winSize.width == 48 && winSize.height == 96)
{
// daimler's base
ocl_hog.setSVMDetector(ocl_hog.getPeopleDetector48x96());
ocl_hog.setSVMDetector(hog.getDaimlerPeopleDetector());
hog.setSVMDetector(hog.getDaimlerPeopleDetector());
}
else if (winSize.width == 64 && winSize.height == 128)
{
ocl_hog.setSVMDetector(ocl_hog.getPeopleDetector64x128());
ocl_hog.setSVMDetector(hog.getDefaultPeopleDetector());
hog.setSVMDetector(hog.getDefaultPeopleDetector());
}
else
{
ocl_hog.setSVMDetector(ocl_hog.getDefaultPeopleDetector());
ocl_hog.setSVMDetector(hog.getDefaultPeopleDetector());
hog.setSVMDetector(hog.getDefaultPeopleDetector());
}

@ -27,7 +27,7 @@ if(BUILD_EXAMPLES AND OCV_DEPENDENCIES_FOUND)
target_link_libraries(${the_target} ${OPENCV_LINKER_LIBS} ${OPENCV_OCL_SAMPLES_REQUIRED_DEPS})
set_target_properties(${the_target} PROPERTIES
OUTPUT_NAME "${name}_${project}"
OUTPUT_NAME "${project}-example-${name}"
PROJECT_LABEL "(EXAMPLE_${project_upper}) ${name}")
if(ENABLE_SOLUTION_FOLDERS)

@ -0,0 +1,108 @@
#include <iostream>
#include "opencv2/core/core.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/ocl/ocl.hpp"
using namespace cv;
using namespace std;
Ptr<CLAHE> pFilter;
int tilesize;
int cliplimit;
string outfile;
static void TSize_Callback(int pos)
{
if(pos==0)
{
pFilter->setTilesGridSize(Size(1,1));
}
pFilter->setTilesGridSize(Size(tilesize,tilesize));
}
static void Clip_Callback(int)
{
pFilter->setClipLimit(cliplimit);
}
int main(int argc, char** argv)
{
const char* keys =
"{ i | input | | specify input image }"
"{ c | camera | 0 | specify camera id }"
"{ s | use_cpu | false | use cpu algorithm }"
"{ o | output | clahe_output.jpg | specify output save path}";
CommandLineParser cmd(argc, argv, keys);
string infile = cmd.get<string>("i");
outfile = cmd.get<string>("o");
int camid = cmd.get<int>("c");
bool use_cpu = cmd.get<bool>("s");
CvCapture* capture = 0;
bool running = true;
namedWindow("CLAHE");
createTrackbar("Tile Size", "CLAHE", &tilesize, 32, (TrackbarCallback)TSize_Callback);
createTrackbar("Clip Limit", "CLAHE", &cliplimit, 20, (TrackbarCallback)Clip_Callback);
Mat frame, outframe;
ocl::oclMat d_outframe;
int cur_clip;
Size cur_tilesize;
if(use_cpu)
{
pFilter = createCLAHE();
}
else
{
pFilter = ocl::createCLAHE();
}
cur_clip = (int)pFilter->getClipLimit();
cur_tilesize = pFilter->getTilesGridSize();
setTrackbarPos("Tile Size", "CLAHE", cur_tilesize.width);
setTrackbarPos("Clip Limit", "CLAHE", cur_clip);
if(infile != "")
{
frame = imread(infile);
if(frame.empty())
{
cout << "error read image: " << infile << endl;
return -1;
}
}
else
{
capture = cvCaptureFromCAM(camid);
}
cout << "\nControls:\n"
<< "\to - save output image\n"
<< "\tESC - exit\n";
while(running)
{
if(capture)
frame = cvQueryFrame(capture);
else
frame = imread(infile);
if(frame.empty())
{
continue;
}
if(use_cpu)
{
cvtColor(frame, frame, COLOR_BGR2GRAY);
pFilter->apply(frame, outframe);
}
else
{
ocl::oclMat d_frame(frame);
ocl::cvtColor(d_frame, d_outframe, COLOR_BGR2GRAY);
pFilter->apply(d_outframe, d_outframe);
d_outframe.download(outframe);
}
imshow("CLAHE", outframe);
char key = (char)cvWaitKey(3);
if(key == 'o') imwrite(outfile, outframe);
else if(key == 27) running = false;
}
return 0;
}

@ -252,8 +252,13 @@ void Draw(Mat& img, vector<Rect>& faces, double scale)
radius = cvRound((r->width + r->height)*0.25*scale);
circle( img, center, radius, color, 3, 8, 0 );
}
imshow( "result", img );
imwrite( outputName, img );
if(abs(scale-1.0)>.001)
{
resize(img, img, Size((int)(img.cols/scale), (int)(img.rows/scale)));
}
imshow( "result", img );
}

@ -57,6 +57,7 @@ private:
string vdo_source;
string output;
int camera_id;
bool write_once;
};
int main(int argc, char** argv)
@ -97,6 +98,7 @@ App::App(CommandLineParser& cmd)
<< "\tESC - exit\n"
<< "\tm - change mode GPU <-> CPU\n"
<< "\tg - convert image to gray or not\n"
<< "\to - save output image once, or switch on/off video save\n"
<< "\t1/q - increase/decrease HOG scale\n"
<< "\t2/w - increase/decrease levels count\n"
<< "\t3/e - increase/decrease HOG group threshold\n"
@ -120,6 +122,7 @@ App::App(CommandLineParser& cmd)
hit_threshold = win_width == 48 ? 1.4 : 0.;
scale = 1.05;
gamma_corr = true;
write_once = false;
cout << "Group threshold: " << gr_threshold << endl;
cout << "Levels number: " << nlevels << endl;
@ -254,10 +257,11 @@ void App::run()
workEnd();
if (output!="")
if (output!="" && write_once)
{
if (img_source!="") // wirte image
{
write_once = false;
imwrite(output, img_to_show);
}
else //write video
@ -340,6 +344,10 @@ void App::handleKey(char key)
gamma_corr = !gamma_corr;
cout << "Gamma correction: " << gamma_corr << endl;
break;
case 'o':
case 'O':
write_once = !write_once;
break;
}
}

@ -49,7 +49,7 @@ struct App
return ss.str();
}
private:
bool running;
bool running, write_once;
Mat left_src, right_src;
Mat left, right;
@ -115,6 +115,7 @@ App::App(CommandLineParser& cmd)
cout << "stereo_match_ocl sample\n";
cout << "\nControls:\n"
<< "\tesc - exit\n"
<< "\to - save output image once\n"
<< "\tp - print current parameters\n"
<< "\tg - convert source images into gray\n"
<< "\tm - change stereo match method\n"
@ -132,6 +133,7 @@ App::App(CommandLineParser& cmd)
else cout << "unknown method!\n";
ndisp = cmd.get<int>("n");
out_img = cmd.get<string>("o");
write_once = false;
}
@ -161,10 +163,8 @@ void App::run()
printParams();
running = true;
bool written = false;
while (running)
{
// Prepare disparity map of specified type
Mat disp;
oclMat d_disp;
@ -192,19 +192,21 @@ void App::run()
csbp(d_left, d_right, d_disp);
break;
}
// Show results
d_disp.download(disp);
workEnd();
if (method != BM)
{
disp.convertTo(disp, 0);
}
putText(disp, text(), Point(5, 25), FONT_HERSHEY_SIMPLEX, 1.0, Scalar::all(255));
imshow("disparity", disp);
if(!written)
if(write_once)
{
imwrite(out_img, disp);
written = true;
write_once = false;
}
handleKey((char)waitKey(3));
}
@ -378,6 +380,10 @@ void App::handleKey(char key)
cout << "level_count: " << csbp.levels << endl;
}
break;
case 'o':
case 'O':
write_once = true;
break;
}
}

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