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