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| extern "C" {
| #include "network.h"
| #include "detection_layer.h"
| #include "cost_layer.h"
| #include "utils.h"
| #include "parser.h"
| #include "box.h"
| #include "image.h"
| }
|
| #ifdef OPENCV
| #include "opencv2/highgui/highgui.hpp"
| #include "opencv2/imgproc/imgproc.hpp"
| extern "C" image ipl_to_image(IplImage* src);
| 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);
| extern "C" void draw_yolo(image im, int num, float thresh, box *boxes, float **probs, char *label);
|
| extern "C" void demo_yolo(char *cfgfile, char *weightfile, float thresh)
| {
| network net = parse_network_cfg(cfgfile);
| if(weightfile){
| load_weights(&net, weightfile);
| }
| detection_layer l = net.layers[net.n-1];
| cv::VideoCapture cap(0);
|
| set_batch_network(&net, 1);
| srand(2222222);
| float nms = .4;
| int j;
| box *boxes = (box *)calloc(l.side*l.side*l.n, sizeof(box));
| float **probs = (float **)calloc(l.side*l.side*l.n, sizeof(float *));
| for(j = 0; j < l.side*l.side*l.n; ++j) probs[j] = (float *)calloc(l.classes, sizeof(float *));
|
| while(1){
| cv::Mat frame_m;
| cap >> frame_m;
| IplImage frame = frame_m;
| image im = ipl_to_image(&frame);
| rgbgr_image(im);
|
| image sized = resize_image(im, net.w, net.h);
| float *X = sized.data;
| float *predictions = network_predict(net, X);
| convert_yolo_detections(predictions, l.classes, l.n, l.sqrt, l.side, 1, 1, thresh, probs, boxes, 0);
| if (nms > 0) do_nms(boxes, probs, l.side*l.side*l.n, l.classes, nms);
| printf("\033[2J");
| printf("\033[1;1H");
| printf("\nObjects:\n\n");
| draw_yolo(im, l.side*l.side*l.n, thresh, boxes, probs, "predictions");
|
| free_image(im);
| free_image(sized);
| cvWaitKey(1);
| }
| }
| #else
| extern "C" void demo_yolo(char *cfgfile, char *weightfile, float thresh){}
| #endif
|
|
