mirror of
https://github.com/pjreddie/darknet.git
synced 2023-08-10 21:13:14 +03:00
126 lines
3.4 KiB
Plaintext
126 lines
3.4 KiB
Plaintext
#include "cuda_runtime.h"
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#include "curand.h"
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#include "cublas_v2.h"
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extern "C" {
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#include "network.h"
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#include "detection_layer.h"
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#include "cost_layer.h"
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#include "utils.h"
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#include "parser.h"
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#include "box.h"
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#include "image.h"
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#include <sys/time.h>
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}
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#ifdef OPENCV
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#include "opencv2/highgui/highgui.hpp"
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#include "opencv2/imgproc/imgproc.hpp"
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extern "C" image ipl_to_image(IplImage* src);
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extern "C" void convert_yolo_detections(float *predictions, int classes, int num, int square, int side, int w, int h, float thresh, float **probs, box *boxes, int only_objectness);
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extern "C" void draw_yolo(image im, int num, float thresh, box *boxes, float **probs);
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static float **probs;
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static box *boxes;
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static network net;
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static image in ;
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static image in_s ;
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static image det ;
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static image det_s;
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static image disp ;
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static cv::VideoCapture cap;
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static float fps = 0;
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void *fetch_in_thread(void *ptr)
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{
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cv::Mat frame_m;
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cap >> frame_m;
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IplImage frame = frame_m;
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in = ipl_to_image(&frame);
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rgbgr_image(in);
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in_s = resize_image(in, net.w, net.h);
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return 0;
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}
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void *detect_in_thread(void *ptr)
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{
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float nms = .4;
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float thresh = .2;
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detection_layer l = net.layers[net.n-1];
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float *X = det_s.data;
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float *predictions = network_predict(net, X);
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free_image(det_s);
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convert_yolo_detections(predictions, l.classes, l.n, l.sqrt, l.side, 1, 1, thresh, probs, boxes, 0);
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if (nms > 0) do_nms(boxes, probs, l.side*l.side*l.n, l.classes, nms);
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printf("\033[2J");
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printf("\033[1;1H");
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printf("\nFPS:%.0f\n",fps);
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printf("Objects:\n\n");
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draw_yolo(det, l.side*l.side*l.n, thresh, boxes, probs);
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return 0;
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}
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extern "C" void demo_yolo(char *cfgfile, char *weightfile, float thresh, int cam_index)
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{
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printf("YOLO demo\n");
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net = parse_network_cfg(cfgfile);
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if(weightfile){
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load_weights(&net, weightfile);
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}
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set_batch_network(&net, 1);
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srand(2222222);
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cv::VideoCapture cam(cam_index);
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cap = cam;
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if(!cap.isOpened()) error("Couldn't connect to webcam.\n");
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detection_layer l = net.layers[net.n-1];
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int j;
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boxes = (box *)calloc(l.side*l.side*l.n, sizeof(box));
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probs = (float **)calloc(l.side*l.side*l.n, sizeof(float *));
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for(j = 0; j < l.side*l.side*l.n; ++j) probs[j] = (float *)calloc(l.classes, sizeof(float *));
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pthread_t fetch_thread;
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pthread_t detect_thread;
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fetch_in_thread(0);
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det = in;
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det_s = in_s;
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fetch_in_thread(0);
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detect_in_thread(0);
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disp = det;
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det = in;
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det_s = in_s;
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while(1){
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struct timeval tval_before, tval_after, tval_result;
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gettimeofday(&tval_before, NULL);
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if(pthread_create(&fetch_thread, 0, fetch_in_thread, 0)) error("Thread creation failed");
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if(pthread_create(&detect_thread, 0, detect_in_thread, 0)) error("Thread creation failed");
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show_image(disp, "YOLO");
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free_image(disp);
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cvWaitKey(1);
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pthread_join(fetch_thread, 0);
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pthread_join(detect_thread, 0);
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disp = det;
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det = in;
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det_s = in_s;
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gettimeofday(&tval_after, NULL);
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timersub(&tval_after, &tval_before, &tval_result);
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float curr = 1000000.f/((long int)tval_result.tv_usec);
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fps = .9*fps + .1*curr;
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}
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}
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#else
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extern "C" void demo_yolo(char *cfgfile, char *weightfile, float thresh, int cam_index){
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fprintf(stderr, "YOLO demo needs OpenCV for webcam images.\n");
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}
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#endif
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