Open Source Computer Vision Library https://opencv.org/
You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
 
 
 
 
 
 

335 lines
9.0 KiB

// WARNING: this sample is under construction! Use it on your own risk.
#if defined _MSC_VER && _MSC_VER >= 1400
#pragma warning(disable : 4100)
#endif
#include <iostream>
#include <iomanip>
#include "opencv2/contrib/contrib.hpp"
#include "opencv2/objdetect/objdetect.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/gpu/gpu.hpp"
using namespace std;
using namespace cv;
using namespace cv::gpu;
static void help()
{
cout << "Usage: ./cascadeclassifier_gpu \n\t--cascade <cascade_file>\n\t(<image>|--video <video>|--camera <camera_id>)\n"
"Using OpenCV version " << CV_VERSION << endl << endl;
}
static void convertAndResize(const Mat& src, Mat& gray, Mat& resized, double scale)
{
if (src.channels() == 3)
{
cv::cvtColor( src, gray, COLOR_BGR2GRAY );
}
else
{
gray = src;
}
Size sz(cvRound(gray.cols * scale), cvRound(gray.rows * scale));
if (scale != 1)
{
cv::resize(gray, resized, sz);
}
else
{
resized = gray;
}
}
static void convertAndResize(const GpuMat& src, GpuMat& gray, GpuMat& resized, double scale)
{
if (src.channels() == 3)
{
gpu::cvtColor( src, gray, COLOR_BGR2GRAY );
}
else
{
gray = src;
}
Size sz(cvRound(gray.cols * scale), cvRound(gray.rows * scale));
if (scale != 1)
{
gpu::resize(gray, resized, sz);
}
else
{
resized = gray;
}
}
static void matPrint(Mat &img, int lineOffsY, Scalar fontColor, const string &ss)
{
int fontFace = FONT_HERSHEY_DUPLEX;
double fontScale = 0.8;
int fontThickness = 2;
Size fontSize = cv::getTextSize("T[]", fontFace, fontScale, fontThickness, 0);
Point org;
org.x = 1;
org.y = 3 * fontSize.height * (lineOffsY + 1) / 2;
putText(img, ss, org, fontFace, fontScale, Scalar(0,0,0), 5*fontThickness/2, 16);
putText(img, ss, org, fontFace, fontScale, fontColor, fontThickness, 16);
}
static void displayState(Mat &canvas, bool bHelp, bool bGpu, bool bLargestFace, bool bFilter, double fps)
{
Scalar fontColorRed = Scalar(255,0,0);
Scalar fontColorNV = Scalar(118,185,0);
ostringstream ss;
ss << "FPS = " << setprecision(1) << fixed << fps;
matPrint(canvas, 0, fontColorRed, ss.str());
ss.str("");
ss << "[" << canvas.cols << "x" << canvas.rows << "], " <<
(bGpu ? "GPU, " : "CPU, ") <<
(bLargestFace ? "OneFace, " : "MultiFace, ") <<
(bFilter ? "Filter:ON" : "Filter:OFF");
matPrint(canvas, 1, fontColorRed, ss.str());
// by Anatoly. MacOS fix. ostringstream(const string&) is a private
// matPrint(canvas, 2, fontColorNV, ostringstream("Space - switch GPU / CPU"));
if (bHelp)
{
matPrint(canvas, 2, fontColorNV, "Space - switch GPU / CPU");
matPrint(canvas, 3, fontColorNV, "M - switch OneFace / MultiFace");
matPrint(canvas, 4, fontColorNV, "F - toggle rectangles Filter");
matPrint(canvas, 5, fontColorNV, "H - toggle hotkeys help");
matPrint(canvas, 6, fontColorNV, "1/Q - increase/decrease scale");
}
else
{
matPrint(canvas, 2, fontColorNV, "H - toggle hotkeys help");
}
}
int main(int argc, const char *argv[])
{
if (argc == 1)
{
help();
return -1;
}
if (getCudaEnabledDeviceCount() == 0)
{
return cerr << "No GPU found or the library is compiled without GPU support" << endl, -1;
}
cv::gpu::printShortCudaDeviceInfo(cv::gpu::getDevice());
string cascadeName;
string inputName;
bool isInputImage = false;
bool isInputVideo = false;
bool isInputCamera = false;
for (int i = 1; i < argc; ++i)
{
if (string(argv[i]) == "--cascade")
cascadeName = argv[++i];
else if (string(argv[i]) == "--video")
{
inputName = argv[++i];
isInputVideo = true;
}
else if (string(argv[i]) == "--camera")
{
inputName = argv[++i];
isInputCamera = true;
}
else if (string(argv[i]) == "--help")
{
help();
return -1;
}
else if (!isInputImage)
{
inputName = argv[i];
isInputImage = true;
}
else
{
cout << "Unknown key: " << argv[i] << endl;
return -1;
}
}
CascadeClassifier_GPU cascade_gpu;
if (!cascade_gpu.load(cascadeName))
{
return cerr << "ERROR: Could not load cascade classifier \"" << cascadeName << "\"" << endl, help(), -1;
}
CascadeClassifier cascade_cpu;
if (!cascade_cpu.load(cascadeName))
{
return cerr << "ERROR: Could not load cascade classifier \"" << cascadeName << "\"" << endl, help(), -1;
}
VideoCapture capture;
Mat image;
if (isInputImage)
{
image = imread(inputName);
CV_Assert(!image.empty());
}
else if (isInputVideo)
{
capture.open(inputName);
CV_Assert(capture.isOpened());
}
else
{
capture.open(atoi(inputName.c_str()));
CV_Assert(capture.isOpened());
}
namedWindow("result", 1);
Mat frame, frame_cpu, gray_cpu, resized_cpu, faces_downloaded, frameDisp;
vector<Rect> facesBuf_cpu;
GpuMat frame_gpu, gray_gpu, resized_gpu, facesBuf_gpu;
/* parameters */
bool useGPU = true;
double scaleFactor = 1.0;
bool findLargestObject = false;
bool filterRects = true;
bool helpScreen = false;
int detections_num;
for (;;)
{
if (isInputCamera || isInputVideo)
{
capture >> frame;
if (frame.empty())
{
break;
}
}
(image.empty() ? frame : image).copyTo(frame_cpu);
frame_gpu.upload(image.empty() ? frame : image);
convertAndResize(frame_gpu, gray_gpu, resized_gpu, scaleFactor);
convertAndResize(frame_cpu, gray_cpu, resized_cpu, scaleFactor);
TickMeter tm;
tm.start();
if (useGPU)
{
//cascade_gpu.visualizeInPlace = true;
cascade_gpu.findLargestObject = findLargestObject;
detections_num = cascade_gpu.detectMultiScale(resized_gpu, facesBuf_gpu, 1.2,
(filterRects || findLargestObject) ? 4 : 0);
facesBuf_gpu.colRange(0, detections_num).download(faces_downloaded);
}
else
{
Size minSize = cascade_gpu.getClassifierSize();
cascade_cpu.detectMultiScale(resized_cpu, facesBuf_cpu, 1.2,
(filterRects || findLargestObject) ? 4 : 0,
(findLargestObject ? CASCADE_FIND_BIGGEST_OBJECT : 0)
| CASCADE_SCALE_IMAGE,
minSize);
detections_num = (int)facesBuf_cpu.size();
}
if (!useGPU && detections_num)
{
for (int i = 0; i < detections_num; ++i)
{
rectangle(resized_cpu, facesBuf_cpu[i], Scalar(255));
}
}
if (useGPU)
{
resized_gpu.download(resized_cpu);
for (int i = 0; i < detections_num; ++i)
{
rectangle(resized_cpu, faces_downloaded.ptr<cv::Rect>()[i], Scalar(255));
}
}
tm.stop();
double detectionTime = tm.getTimeMilli();
double fps = 1000 / detectionTime;
//print detections to console
cout << setfill(' ') << setprecision(2);
cout << setw(6) << fixed << fps << " FPS, " << detections_num << " det";
if ((filterRects || findLargestObject) && detections_num > 0)
{
Rect *faceRects = useGPU ? faces_downloaded.ptr<Rect>() : &facesBuf_cpu[0];
for (int i = 0; i < min(detections_num, 2); ++i)
{
cout << ", [" << setw(4) << faceRects[i].x
<< ", " << setw(4) << faceRects[i].y
<< ", " << setw(4) << faceRects[i].width
<< ", " << setw(4) << faceRects[i].height << "]";
}
}
cout << endl;
cv::cvtColor(resized_cpu, frameDisp, COLOR_GRAY2BGR);
displayState(frameDisp, helpScreen, useGPU, findLargestObject, filterRects, fps);
imshow("result", frameDisp);
char key = (char)waitKey(5);
if (key == 27)
{
break;
}
switch (key)
{
case ' ':
useGPU = !useGPU;
break;
case 'm':
case 'M':
findLargestObject = !findLargestObject;
break;
case 'f':
case 'F':
filterRects = !filterRects;
break;
case '1':
scaleFactor *= 1.05;
break;
case 'q':
case 'Q':
scaleFactor /= 1.05;
break;
case 'h':
case 'H':
helpScreen = !helpScreen;
break;
}
}
return 0;
}