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https://github.com/pjreddie/darknet.git
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idk
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@ -279,7 +279,7 @@ void test_classifier(char *datacfg, char *cfgfile, char *weightfile, char *filen
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int i;
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int i;
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if (target_layer >= 0){
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if (target_layer >= 0){
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layer l = net.layers[target_layer];
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//layer l = net.layers[target_layer];
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}
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}
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for(i = 0; i < val.X.rows; ++i){
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for(i = 0; i < val.X.rows; ++i){
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@ -32,6 +32,7 @@ static image det_s;
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static image disp ;
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static image disp ;
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static cv::VideoCapture cap;
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static cv::VideoCapture cap;
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static float fps = 0;
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static float fps = 0;
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static int demo_thresh = 0;
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void *fetch_in_thread_coco(void *ptr)
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void *fetch_in_thread_coco(void *ptr)
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{
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{
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@ -47,24 +48,24 @@ void *fetch_in_thread_coco(void *ptr)
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void *detect_in_thread_coco(void *ptr)
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void *detect_in_thread_coco(void *ptr)
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{
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{
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float nms = .4;
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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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detection_layer l = net.layers[net.n-1];
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float *X = det_s.data;
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float *X = det_s.data;
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float *predictions = network_predict(net, X);
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float *predictions = network_predict(net, X);
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free_image(det_s);
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free_image(det_s);
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convert_coco_detections(predictions, l.classes, l.n, l.sqrt, l.side, 1, 1, thresh, probs, boxes, 0);
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convert_coco_detections(predictions, l.classes, l.n, l.sqrt, l.side, 1, 1, demo_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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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[2J");
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printf("\033[1;1H");
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printf("\033[1;1H");
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printf("\nFPS:%.0f\n",fps);
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printf("\nFPS:%.0f\n",fps);
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printf("Objects:\n\n");
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printf("Objects:\n\n");
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draw_detections(det, l.side*l.side*l.n, thresh, boxes, probs, coco_classes, coco_labels, 80);
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draw_detections(det, l.side*l.side*l.n, demo_thresh, boxes, probs, coco_classes, coco_labels, 80);
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return 0;
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return 0;
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}
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}
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extern "C" void demo_coco(char *cfgfile, char *weightfile, float thresh, int cam_index)
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extern "C" void demo_coco(char *cfgfile, char *weightfile, float thresh, int cam_index)
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{
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{
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demo_thresh = thresh;
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printf("YOLO demo\n");
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printf("YOLO demo\n");
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net = parse_network_cfg(cfgfile);
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net = parse_network_cfg(cfgfile);
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if(weightfile){
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if(weightfile){
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@ -33,6 +33,7 @@ static image det_s;
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static image disp ;
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static image disp ;
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static cv::VideoCapture cap;
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static cv::VideoCapture cap;
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static float fps = 0;
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static float fps = 0;
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static int demo_thresh = 0;
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void *fetch_in_thread(void *ptr)
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void *fetch_in_thread(void *ptr)
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{
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{
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@ -48,24 +49,24 @@ void *fetch_in_thread(void *ptr)
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void *detect_in_thread(void *ptr)
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void *detect_in_thread(void *ptr)
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{
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{
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float nms = .4;
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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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detection_layer l = net.layers[net.n-1];
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float *X = det_s.data;
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float *X = det_s.data;
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float *predictions = network_predict(net, X);
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float *predictions = network_predict(net, X);
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free_image(det_s);
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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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convert_yolo_detections(predictions, l.classes, l.n, l.sqrt, l.side, 1, 1, demo_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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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[2J");
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printf("\033[1;1H");
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printf("\033[1;1H");
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printf("\nFPS:%.0f\n",fps);
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printf("\nFPS:%.0f\n",fps);
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printf("Objects:\n\n");
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printf("Objects:\n\n");
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draw_detections(det, l.side*l.side*l.n, thresh, boxes, probs, voc_names, voc_labels, 20);
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draw_detections(det, l.side*l.side*l.n, demo_thresh, boxes, probs, voc_names, voc_labels, 20);
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return 0;
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return 0;
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}
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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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extern "C" void demo_yolo(char *cfgfile, char *weightfile, float thresh, int cam_index)
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{
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{
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demo_thresh = thresh;
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printf("YOLO demo\n");
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printf("YOLO demo\n");
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net = parse_network_cfg(cfgfile);
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net = parse_network_cfg(cfgfile);
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if(weightfile){
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if(weightfile){
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