mirror of
https://github.com/pjreddie/darknet.git
synced 2023-08-10 21:13:14 +03:00
CARLY RAE JEPSEN IS THE BEST POP ARTIST OF ALL TIME DON'T @ ME
This commit is contained in:
@ -44,11 +44,15 @@ void train_classifier(char *datacfg, char *cfgfile, char *weightfile, int *gpus,
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list *options = read_data_cfg(datacfg);
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char *backup_directory = option_find_str(options, "backup", "/backup/");
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int tag = option_find_int_quiet(options, "tag", 0);
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char *label_list = option_find_str(options, "labels", "data/labels.list");
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char *train_list = option_find_str(options, "train", "data/train.list");
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int classes = option_find_int(options, "classes", 2);
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char **labels = get_labels(label_list);
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char **labels;
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if(!tag){
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labels = get_labels(label_list);
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}
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list *plist = get_paths(train_list);
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char **paths = (char **)list_to_array(plist);
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printf("%d\n", plist->size);
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@ -76,7 +80,11 @@ void train_classifier(char *datacfg, char *cfgfile, char *weightfile, int *gpus,
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args.n = imgs;
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args.m = N;
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args.labels = labels;
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args.type = CLASSIFICATION_DATA;
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if (tag){
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args.type = TAG_DATA;
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} else {
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args.type = CLASSIFICATION_DATA;
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}
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data train;
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data buffer;
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@ -385,15 +393,13 @@ void validate_classifier_single(char *datacfg, char *filename, char *weightfile)
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}
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}
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image im = load_image_color(paths[i], 0, 0);
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image resized = resize_min(im, net->w);
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image crop = crop_image(resized, (resized.w - net->w)/2, (resized.h - net->h)/2, net->w, net->h);
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image crop = center_crop_image(im, net->w, net->h);
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//show_image(im, "orig");
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//show_image(crop, "cropped");
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//cvWaitKey(0);
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float *pred = network_predict(net, crop.data);
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if(net->hierarchy) hierarchy_predictions(pred, net->outputs, net->hierarchy, 1, 1);
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if(resized.data != im.data) free_image(resized);
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free_image(im);
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free_image(crop);
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top_k(pred, classes, topk, indexes);
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@ -955,6 +961,8 @@ void gun_classifier(char *datacfg, char *cfgfile, char *weightfile, int cam_inde
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void demo_classifier(char *datacfg, char *cfgfile, char *weightfile, int cam_index, const char *filename)
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{
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#ifdef OPENCV
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char *base = basecfg(cfgfile);
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image **alphabet = load_alphabet();
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printf("Classifier Demo\n");
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network *net = load_network(cfgfile, weightfile, 0);
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set_batch_network(net, 1);
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@ -988,8 +996,8 @@ void demo_classifier(char *datacfg, char *cfgfile, char *weightfile, int cam_ind
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int *indexes = calloc(top, sizeof(int));
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if(!cap) error("Couldn't connect to webcam.\n");
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cvNamedWindow("Classifier", CV_WINDOW_NORMAL);
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cvResizeWindow("Classifier", 512, 512);
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cvNamedWindow(base, CV_WINDOW_NORMAL);
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cvResizeWindow(base, 512, 512);
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float fps = 0;
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int i;
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@ -998,8 +1006,8 @@ void demo_classifier(char *datacfg, char *cfgfile, char *weightfile, int cam_ind
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gettimeofday(&tval_before, NULL);
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image in = get_image_from_stream(cap);
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image in_s = resize_image(in, net->w, net->h);
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show_image(in, "Classifier");
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//image in_s = resize_image(in, net->w, net->h);
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image in_s = letterbox_image(in, net->w, net->h);
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float *predictions = network_predict(net, in_s.data);
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if(net->hierarchy) hierarchy_predictions(predictions, net->outputs, net->hierarchy, 1, 1);
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@ -1009,11 +1017,24 @@ void demo_classifier(char *datacfg, char *cfgfile, char *weightfile, int cam_ind
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printf("\033[1;1H");
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printf("\nFPS:%.0f\n",fps);
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int lh = in.h*.03;
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int toph = 3*lh;
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float rgb[3] = {1,1,1};
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for(i = 0; i < top; ++i){
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printf("%d\n", toph);
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int index = indexes[i];
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printf("%.1f%%: %s\n", predictions[index]*100, names[index]);
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char buff[1024];
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sprintf(buff, "%3.1f%%: %s\n", predictions[index]*100, names[index]);
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image label = get_label(alphabet, buff, lh);
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draw_label(in, toph, lh, label, rgb);
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toph += 2*lh;
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free_image(label);
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}
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show_image(in, base);
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free_image(in_s);
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free_image(in);
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@ -624,6 +624,177 @@ void test_detector(char *datacfg, char *cfgfile, char *weightfile, char *filenam
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}
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}
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void censor_detector(char *datacfg, char *cfgfile, char *weightfile, int cam_index, const char *filename, int class, float thresh, int skip)
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{
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image **alphabet = load_alphabet();
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char *base = basecfg(cfgfile);
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network *net = load_network(cfgfile, weightfile, 0);
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set_batch_network(net, 1);
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list *options = read_data_cfg(datacfg);
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srand(2222222);
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CvCapture * cap;
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int w = 1280;
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int h = 720;
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if(filename){
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cap = cvCaptureFromFile(filename);
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}else{
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cap = cvCaptureFromCAM(cam_index);
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}
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if(w){
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cvSetCaptureProperty(cap, CV_CAP_PROP_FRAME_WIDTH, w);
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}
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if(h){
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cvSetCaptureProperty(cap, CV_CAP_PROP_FRAME_HEIGHT, h);
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}
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int top = option_find_int(options, "top", 1);
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char *label_list = option_find_str(options, "labels", 0);
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char *name_list = option_find_str(options, "names", label_list);
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char **names = get_labels(name_list);
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int *indexes = calloc(top, sizeof(int));
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if(!cap) error("Couldn't connect to webcam.\n");
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cvNamedWindow(base, CV_WINDOW_NORMAL);
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cvResizeWindow(base, 512, 512);
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float fps = 0;
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int i;
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int count = 0;
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float nms = .45;
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while(1){
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image in = get_image_from_stream(cap);
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//image in_s = resize_image(in, net->w, net->h);
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image in_s = letterbox_image(in, net->w, net->h);
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layer l = net->layers[net->n-1];
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int nboxes = num_boxes(net);
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float *X = in_s.data;
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network_predict(net, X);
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detection *dets = get_network_boxes(net, in.w, in.h, thresh, 0, 0, 0);
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//if (nms) do_nms_obj(boxes, probs, l.w*l.h*l.n, l.classes, nms);
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if (nms) do_nms_sort(dets, nboxes, l.classes, nms);
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for(i = 0; i < nboxes; ++i){
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if(dets[i].prob[class] > thresh){
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box b = dets[i].bbox;
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int left = b.x-b.w/2.;
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int top = b.y-b.h/2.;
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censor_image(in, left, top, b.w, b.h);
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}
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}
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show_image(in, base);
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cvWaitKey(10);
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free_detections(dets, num_boxes(net));
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free_image(in_s);
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free_image(in);
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float curr = 0;
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fps = .9*fps + .1*curr;
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for(i = 0; i < skip; ++i){
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image in = get_image_from_stream(cap);
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free_image(in);
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}
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}
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}
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void extract_detector(char *datacfg, char *cfgfile, char *weightfile, int cam_index, const char *filename, int class, float thresh, int skip)
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{
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image **alphabet = load_alphabet();
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char *base = basecfg(cfgfile);
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network *net = load_network(cfgfile, weightfile, 0);
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set_batch_network(net, 1);
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list *options = read_data_cfg(datacfg);
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srand(2222222);
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CvCapture * cap;
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int w = 1280;
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int h = 720;
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if(filename){
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cap = cvCaptureFromFile(filename);
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}else{
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cap = cvCaptureFromCAM(cam_index);
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}
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if(w){
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cvSetCaptureProperty(cap, CV_CAP_PROP_FRAME_WIDTH, w);
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}
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if(h){
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cvSetCaptureProperty(cap, CV_CAP_PROP_FRAME_HEIGHT, h);
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}
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int top = option_find_int(options, "top", 1);
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char *label_list = option_find_str(options, "labels", 0);
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char *name_list = option_find_str(options, "names", label_list);
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char **names = get_labels(name_list);
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int *indexes = calloc(top, sizeof(int));
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if(!cap) error("Couldn't connect to webcam.\n");
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cvNamedWindow(base, CV_WINDOW_NORMAL);
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cvResizeWindow(base, 512, 512);
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float fps = 0;
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int i;
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int count = 0;
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float nms = .45;
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while(1){
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image in = get_image_from_stream(cap);
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//image in_s = resize_image(in, net->w, net->h);
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image in_s = letterbox_image(in, net->w, net->h);
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layer l = net->layers[net->n-1];
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int nboxes = num_boxes(net);
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show_image(in, base);
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float *X = in_s.data;
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network_predict(net, X);
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detection *dets = get_network_boxes(net, in.w, in.h, thresh, 0, 0, 1);
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//if (nms) do_nms_obj(boxes, probs, l.w*l.h*l.n, l.classes, nms);
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if (nms) do_nms_sort(dets, nboxes, l.classes, nms);
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for(i = 0; i < nboxes; ++i){
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if(dets[i].prob[class] > thresh){
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box b = dets[i].bbox;
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int size = b.w*in.w > b.h*in.h ? b.w*in.w : b.h*in.h;
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int dx = b.x*in.w-size/2.;
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int dy = b.y*in.h-size/2.;
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image bim = crop_image(in, dx, dy, size, size);
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char buff[2048];
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sprintf(buff, "results/extract/%07d", count);
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++count;
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save_image(bim, buff);
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free_image(bim);
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}
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}
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free_detections(dets, num_boxes(net));
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free_image(in_s);
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free_image(in);
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float curr = 0;
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fps = .9*fps + .1*curr;
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for(i = 0; i < skip; ++i){
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image in = get_image_from_stream(cap);
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free_image(in);
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}
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}
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}
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void network_detect(network *net, image im, float thresh, float hier_thresh, float nms, detection *dets)
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{
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network_predict_image(net, im);
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@ -674,12 +845,15 @@ void run_detector(int argc, char **argv)
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int width = find_int_arg(argc, argv, "-w", 0);
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int height = find_int_arg(argc, argv, "-h", 0);
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int fps = find_int_arg(argc, argv, "-fps", 0);
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int class = find_int_arg(argc, argv, "-class", 0);
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char *datacfg = argv[3];
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char *cfg = argv[4];
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char *weights = (argc > 5) ? argv[5] : 0;
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char *filename = (argc > 6) ? argv[6]: 0;
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if(0==strcmp(argv[2], "test")) test_detector(datacfg, cfg, weights, filename, thresh, hier_thresh, outfile, fullscreen);
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else if(0==strcmp(argv[2], "extract")) extract_detector(datacfg, cfg, weights, cam_index, filename, class, thresh, frame_skip);
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else if(0==strcmp(argv[2], "censor")) censor_detector(datacfg, cfg, weights, cam_index, filename, class, thresh, frame_skip);
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else if(0==strcmp(argv[2], "train")) train_detector(datacfg, cfg, weights, gpus, ngpus, clear);
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else if(0==strcmp(argv[2], "valid")) validate_detector(datacfg, cfg, weights, outfile);
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else if(0==strcmp(argv[2], "valid2")) validate_detector_flip(datacfg, cfg, weights, outfile);
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@ -32,6 +32,7 @@ void train_regressor(char *datacfg, char *cfgfile, char *weightfile, int *gpus,
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char *backup_directory = option_find_str(options, "backup", "/backup/");
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char *train_list = option_find_str(options, "train", "data/train.list");
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int classes = option_find_int(options, "classes", 1);
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list *plist = get_paths(train_list);
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char **paths = (char **)list_to_array(plist);
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@ -43,9 +44,10 @@ void train_regressor(char *datacfg, char *cfgfile, char *weightfile, int *gpus,
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args.w = net->w;
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args.h = net->h;
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args.threads = 32;
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args.classes = classes;
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args.min = net->min_crop;
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args.max = net->max_crop;
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args.min = net->min_ratio*net->w;
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args.max = net->max_ratio*net->w;
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args.angle = net->angle;
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args.aspect = net->aspect;
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args.exposure = net->exposure;
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@ -160,6 +162,10 @@ void demo_regressor(char *datacfg, char *cfgfile, char *weightfile, int cam_inde
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}else{
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cap = cvCaptureFromCAM(cam_index);
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}
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list *options = read_data_cfg(datacfg);
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int classes = option_find_int(options, "classes", 1);
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char *name_list = option_find_str(options, "names", 0);
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char **names = get_labels(name_list);
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if(!cap) error("Couldn't connect to webcam.\n");
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cvNamedWindow("Regressor", CV_WINDOW_NORMAL);
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@ -171,19 +177,23 @@ void demo_regressor(char *datacfg, char *cfgfile, char *weightfile, int cam_inde
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gettimeofday(&tval_before, NULL);
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image in = get_image_from_stream(cap);
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image in_s = letterbox_image(in, net->w, net->h);
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show_image(in, "Regressor");
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image crop = center_crop_image(in, net->w, net->h);
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grayscale_image_3c(crop);
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show_image(crop, "Regressor");
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float *predictions = network_predict(net, in_s.data);
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float *predictions = network_predict(net, crop.data);
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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("People: %f\n", predictions[0]);
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int i;
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for(i = 0; i < classes; ++i){
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printf("%s: %f\n", names[i], predictions[i]);
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}
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free_image(in_s);
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free_image(in);
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free_image(crop);
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cvWaitKey(10);
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Reference in New Issue
Block a user