cameracv/libs/opencv/samples/gpu/hog.cpp
2023-05-18 21:39:43 +03:00

552 lines
17 KiB
C++

#include <iostream>
#include <fstream>
#include <string>
#include <sstream>
#include <iomanip>
#include <stdexcept>
#include <opencv2/core/utility.hpp>
#include "opencv2/cudaobjdetect.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/objdetect.hpp"
#include "opencv2/imgproc.hpp"
using namespace std;
using namespace cv;
bool help_showed = false;
class Args
{
public:
Args();
static Args read(int argc, char** argv);
string src;
bool src_is_folder;
bool src_is_video;
bool src_is_camera;
int camera_id;
bool svm_load;
string svm;
bool write_video;
string dst_video;
double dst_video_fps;
bool make_gray;
bool resize_src;
int width, height;
double scale;
int nlevels;
int gr_threshold;
double hit_threshold;
bool hit_threshold_auto;
int win_width;
int win_stride_width, win_stride_height;
int block_width;
int block_stride_width, block_stride_height;
int cell_width;
int nbins;
bool gamma_corr;
};
class App
{
public:
App(const Args& s);
void run();
void handleKey(char key);
void hogWorkBegin();
void hogWorkEnd();
string hogWorkFps() const;
void workBegin();
void workEnd();
string workFps() const;
string message() const;
private:
App operator=(App&);
Args args;
bool running;
bool use_gpu;
bool make_gray;
double scale;
int gr_threshold;
int nlevels;
double hit_threshold;
bool gamma_corr;
int64 hog_work_begin;
double hog_work_fps;
int64 work_begin;
double work_fps;
};
static void printHelp()
{
cout << "Histogram of Oriented Gradients descriptor and detector sample.\n"
<< "\nUsage: hog\n"
<< " (<image>|--video <vide>|--camera <camera_id>) # frames source\n"
<< " or"
<< " (--folder <folder_path>) # load images from folder\n"
<< " [--svm <file> # load svm file"
<< " [--make_gray <true/false>] # convert image to gray one or not\n"
<< " [--resize_src <true/false>] # do resize of the source image or not\n"
<< " [--width <int>] # resized image width\n"
<< " [--height <int>] # resized image height\n"
<< " [--hit_threshold <double>] # classifying plane distance threshold (0.0 usually)\n"
<< " [--scale <double>] # HOG window scale factor\n"
<< " [--nlevels <int>] # max number of HOG window scales\n"
<< " [--win_width <int>] # width of the window\n"
<< " [--win_stride_width <int>] # distance by OX axis between neighbour wins\n"
<< " [--win_stride_height <int>] # distance by OY axis between neighbour wins\n"
<< " [--block_width <int>] # width of the block\n"
<< " [--block_stride_width <int>] # distance by 0X axis between neighbour blocks\n"
<< " [--block_stride_height <int>] # distance by 0Y axis between neighbour blocks\n"
<< " [--cell_width <int>] # width of the cell\n"
<< " [--nbins <int>] # number of bins\n"
<< " [--gr_threshold <int>] # merging similar rects constant\n"
<< " [--gamma_correct <int>] # do gamma correction or not\n"
<< " [--write_video <bool>] # write video or not\n"
<< " [--dst_video <path>] # output video path\n"
<< " [--dst_video_fps <double>] # output video fps\n";
help_showed = true;
}
int main(int argc, char** argv)
{
try
{
Args args;
if (argc < 2)
{
printHelp();
args.camera_id = 0;
args.src_is_camera = true;
}
else
{
args = Args::read(argc, argv);
if (help_showed)
return -1;
}
App app(args);
app.run();
}
catch (const Exception& e) { return cout << "error: " << e.what() << endl, 1; }
catch (const exception& e) { return cout << "error: " << e.what() << endl, 1; }
catch(...) { return cout << "unknown exception" << endl, 1; }
return 0;
}
Args::Args()
{
src_is_video = false;
src_is_camera = false;
src_is_folder = false;
svm_load = false;
camera_id = 0;
write_video = false;
dst_video_fps = 24.;
make_gray = false;
resize_src = false;
width = 640;
height = 480;
scale = 1.05;
nlevels = 13;
gr_threshold = 8;
hit_threshold = 1.4;
hit_threshold_auto = true;
win_width = 48;
win_stride_width = 8;
win_stride_height = 8;
block_width = 16;
block_stride_width = 8;
block_stride_height = 8;
cell_width = 8;
nbins = 9;
gamma_corr = true;
}
Args Args::read(int argc, char** argv)
{
Args args;
for (int i = 1; i < argc; i++)
{
if (string(argv[i]) == "--make_gray") args.make_gray = (string(argv[++i]) == "true");
else if (string(argv[i]) == "--resize_src") args.resize_src = (string(argv[++i]) == "true");
else if (string(argv[i]) == "--width") args.width = atoi(argv[++i]);
else if (string(argv[i]) == "--height") args.height = atoi(argv[++i]);
else if (string(argv[i]) == "--hit_threshold")
{
args.hit_threshold = atof(argv[++i]);
args.hit_threshold_auto = false;
}
else if (string(argv[i]) == "--scale") args.scale = atof(argv[++i]);
else if (string(argv[i]) == "--nlevels") args.nlevels = atoi(argv[++i]);
else if (string(argv[i]) == "--win_width") args.win_width = atoi(argv[++i]);
else if (string(argv[i]) == "--win_stride_width") args.win_stride_width = atoi(argv[++i]);
else if (string(argv[i]) == "--win_stride_height") args.win_stride_height = atoi(argv[++i]);
else if (string(argv[i]) == "--block_width") args.block_width = atoi(argv[++i]);
else if (string(argv[i]) == "--block_stride_width") args.block_stride_width = atoi(argv[++i]);
else if (string(argv[i]) == "--block_stride_height") args.block_stride_height = atoi(argv[++i]);
else if (string(argv[i]) == "--cell_width") args.cell_width = atoi(argv[++i]);
else if (string(argv[i]) == "--nbins") args.nbins = atoi(argv[++i]);
else if (string(argv[i]) == "--gr_threshold") args.gr_threshold = atoi(argv[++i]);
else if (string(argv[i]) == "--gamma_correct") args.gamma_corr = (string(argv[++i]) == "true");
else if (string(argv[i]) == "--write_video") args.write_video = (string(argv[++i]) == "true");
else if (string(argv[i]) == "--dst_video") args.dst_video = argv[++i];
else if (string(argv[i]) == "--dst_video_fps") args.dst_video_fps = atof(argv[++i]);
else if (string(argv[i]) == "--help") printHelp();
else if (string(argv[i]) == "--video") { args.src = argv[++i]; args.src_is_video = true; }
else if (string(argv[i]) == "--camera") { args.camera_id = atoi(argv[++i]); args.src_is_camera = true; }
else if (string(argv[i]) == "--folder") { args.src = argv[++i]; args.src_is_folder = true;}
else if (string(argv[i]) == "--svm") { args.svm = argv[++i]; args.svm_load = true;}
else if (args.src.empty()) args.src = argv[i];
else throw runtime_error((string("unknown key: ") + argv[i]));
}
return args;
}
App::App(const Args& s)
{
cv::cuda::printShortCudaDeviceInfo(cv::cuda::getDevice());
args = s;
cout << "\nControls:\n"
<< "\tESC - exit\n"
<< "\tm - change mode GPU <-> CPU\n"
<< "\tg - convert image to gray or not\n"
<< "\t1/q - increase/decrease HOG scale\n"
<< "\t2/w - increase/decrease levels count\n"
<< "\t3/e - increase/decrease HOG group threshold\n"
<< "\t4/r - increase/decrease hit threshold\n"
<< endl;
use_gpu = true;
make_gray = args.make_gray;
scale = args.scale;
gr_threshold = args.gr_threshold;
nlevels = args.nlevels;
if (args.hit_threshold_auto)
args.hit_threshold = args.win_width == 48 ? 1.4 : 0.;
hit_threshold = args.hit_threshold;
gamma_corr = args.gamma_corr;
cout << "Scale: " << scale << endl;
if (args.resize_src)
cout << "Resized source: (" << args.width << ", " << args.height << ")\n";
cout << "Group threshold: " << gr_threshold << endl;
cout << "Levels number: " << nlevels << endl;
cout << "Win size: (" << args.win_width << ", " << args.win_width*2 << ")\n";
cout << "Win stride: (" << args.win_stride_width << ", " << args.win_stride_height << ")\n";
cout << "Block size: (" << args.block_width << ", " << args.block_width << ")\n";
cout << "Block stride: (" << args.block_stride_width << ", " << args.block_stride_height << ")\n";
cout << "Cell size: (" << args.cell_width << ", " << args.cell_width << ")\n";
cout << "Bins number: " << args.nbins << endl;
cout << "Hit threshold: " << hit_threshold << endl;
cout << "Gamma correction: " << gamma_corr << endl;
cout << endl;
}
void App::run()
{
running = true;
cv::VideoWriter video_writer;
Size win_stride(args.win_stride_width, args.win_stride_height);
Size win_size(args.win_width, args.win_width * 2);
Size block_size(args.block_width, args.block_width);
Size block_stride(args.block_stride_width, args.block_stride_height);
Size cell_size(args.cell_width, args.cell_width);
cv::Ptr<cv::cuda::HOG> gpu_hog = cv::cuda::HOG::create(win_size, block_size, block_stride, cell_size, args.nbins);
cv::HOGDescriptor cpu_hog(win_size, block_size, block_stride, cell_size, args.nbins);
if(args.svm_load) {
std::vector<float> svm_model;
const std::string model_file_name = args.svm;
FileStorage ifs(model_file_name, FileStorage::READ);
if (ifs.isOpened()) {
ifs["svm_detector"] >> svm_model;
} else {
const std::string what =
"could not load model for hog classifier from file: "
+ model_file_name;
throw std::runtime_error(what);
}
// check if the variables are initialized
if (svm_model.empty()) {
const std::string what =
"HoG classifier: svm model could not be loaded from file"
+ model_file_name;
throw std::runtime_error(what);
}
gpu_hog->setSVMDetector(svm_model);
cpu_hog.setSVMDetector(svm_model);
} else {
// Create HOG descriptors and detectors here
Mat detector = gpu_hog->getDefaultPeopleDetector();
gpu_hog->setSVMDetector(detector);
cpu_hog.setSVMDetector(detector);
}
cout << "gpusvmDescriptorSize : " << gpu_hog->getDescriptorSize()
<< endl;
cout << "cpusvmDescriptorSize : " << cpu_hog.getDescriptorSize()
<< endl;
while (running)
{
VideoCapture vc;
Mat frame;
vector<String> filenames;
unsigned int count = 1;
if (args.src_is_video)
{
vc.open(args.src.c_str());
if (!vc.isOpened())
throw runtime_error(string("can't open video file: " + args.src));
vc >> frame;
}
else if (args.src_is_folder) {
String folder = args.src;
cout << folder << endl;
glob(folder, filenames);
frame = imread(filenames[count]); // 0 --> .gitignore
if (!frame.data)
cerr << "Problem loading image from folder!!!" << endl;
}
else if (args.src_is_camera)
{
vc.open(args.camera_id);
if (!vc.isOpened())
{
stringstream msg;
msg << "can't open camera: " << args.camera_id;
throw runtime_error(msg.str());
}
vc >> frame;
}
else
{
frame = imread(args.src);
if (frame.empty())
throw runtime_error(string("can't open image file: " + args.src));
}
Mat img_aux, img, img_to_show;
cuda::GpuMat gpu_img;
// Iterate over all frames
while (running && !frame.empty())
{
workBegin();
// Change format of the image
if (make_gray) cvtColor(frame, img_aux, COLOR_BGR2GRAY);
else if (use_gpu) cvtColor(frame, img_aux, COLOR_BGR2BGRA);
else frame.copyTo(img_aux);
// Resize image
if (args.resize_src) resize(img_aux, img, Size(args.width, args.height));
else img = img_aux;
img_to_show = img;
vector<Rect> found;
// Perform HOG classification
hogWorkBegin();
if (use_gpu)
{
gpu_img.upload(img);
gpu_hog->setNumLevels(nlevels);
gpu_hog->setHitThreshold(hit_threshold);
gpu_hog->setWinStride(win_stride);
gpu_hog->setScaleFactor(scale);
gpu_hog->setGroupThreshold(gr_threshold);
gpu_hog->detectMultiScale(gpu_img, found);
}
else
{
cpu_hog.nlevels = nlevels;
cpu_hog.detectMultiScale(img, found, hit_threshold, win_stride,
Size(0, 0), scale, gr_threshold);
}
hogWorkEnd();
// Draw positive classified windows
for (size_t i = 0; i < found.size(); i++)
{
Rect r = found[i];
rectangle(img_to_show, r.tl(), r.br(), Scalar(0, 255, 0), 3);
}
if (use_gpu)
putText(img_to_show, "Mode: GPU", Point(5, 25), FONT_HERSHEY_SIMPLEX, 1., Scalar(255, 100, 0), 2);
else
putText(img_to_show, "Mode: CPU", Point(5, 25), FONT_HERSHEY_SIMPLEX, 1., Scalar(255, 100, 0), 2);
putText(img_to_show, "FPS HOG: " + hogWorkFps(), Point(5, 65), FONT_HERSHEY_SIMPLEX, 1., Scalar(255, 100, 0), 2);
putText(img_to_show, "FPS total: " + workFps(), Point(5, 105), FONT_HERSHEY_SIMPLEX, 1., Scalar(255, 100, 0), 2);
imshow("opencv_gpu_hog", img_to_show);
if (args.src_is_video || args.src_is_camera) vc >> frame;
if (args.src_is_folder) {
count++;
if (count < filenames.size()) {
frame = imread(filenames[count]);
} else {
Mat empty;
frame = empty;
}
}
workEnd();
if (args.write_video)
{
if (!video_writer.isOpened())
{
video_writer.open(args.dst_video, VideoWriter::fourcc('x','v','i','d'), args.dst_video_fps,
img_to_show.size(), true);
if (!video_writer.isOpened())
throw std::runtime_error("can't create video writer");
}
if (make_gray) cvtColor(img_to_show, img, COLOR_GRAY2BGR);
else cvtColor(img_to_show, img, COLOR_BGRA2BGR);
video_writer << img;
}
handleKey((char)waitKey(3));
}
}
}
void App::handleKey(char key)
{
switch (key)
{
case 27:
running = false;
break;
case 'm':
case 'M':
use_gpu = !use_gpu;
cout << "Switched to " << (use_gpu ? "CUDA" : "CPU") << " mode\n";
break;
case 'g':
case 'G':
make_gray = !make_gray;
cout << "Convert image to gray: " << (make_gray ? "YES" : "NO") << endl;
break;
case '1':
scale *= 1.05;
cout << "Scale: " << scale << endl;
break;
case 'q':
case 'Q':
scale /= 1.05;
cout << "Scale: " << scale << endl;
break;
case '2':
nlevels++;
cout << "Levels number: " << nlevels << endl;
break;
case 'w':
case 'W':
nlevels = max(nlevels - 1, 1);
cout << "Levels number: " << nlevels << endl;
break;
case '3':
gr_threshold++;
cout << "Group threshold: " << gr_threshold << endl;
break;
case 'e':
case 'E':
gr_threshold = max(0, gr_threshold - 1);
cout << "Group threshold: " << gr_threshold << endl;
break;
case '4':
hit_threshold+=0.25;
cout << "Hit threshold: " << hit_threshold << endl;
break;
case 'r':
case 'R':
hit_threshold = max(0.0, hit_threshold - 0.25);
cout << "Hit threshold: " << hit_threshold << endl;
break;
case 'c':
case 'C':
gamma_corr = !gamma_corr;
cout << "Gamma correction: " << gamma_corr << endl;
break;
}
}
inline void App::hogWorkBegin() { hog_work_begin = getTickCount(); }
inline void App::hogWorkEnd()
{
int64 delta = getTickCount() - hog_work_begin;
double freq = getTickFrequency();
hog_work_fps = freq / delta;
}
inline string App::hogWorkFps() const
{
stringstream ss;
ss << hog_work_fps;
return ss.str();
}
inline void App::workBegin() { work_begin = getTickCount(); }
inline void App::workEnd()
{
int64 delta = getTickCount() - work_begin;
double freq = getTickFrequency();
work_fps = freq / delta;
}
inline string App::workFps() const
{
stringstream ss;
ss << work_fps;
return ss.str();
}