| | |
| | | args.n = imgs; |
| | | args.m = plist->size; |
| | | args.classes = classes; |
| | | args.flip = net.flip; |
| | | args.jitter = jitter; |
| | | args.num_boxes = l.max_boxes; |
| | | args.small_object = net.small_object; |
| | |
| | | truth_dif = read_boxes(labelpath_dif, &num_labels_dif); |
| | | } |
| | | |
| | | const int checkpoint_detections_count = detections_count; |
| | | |
| | | for (i = 0; i < nboxes; ++i) { |
| | | |
| | | int class_id; |
| | |
| | | |
| | | // calc avg IoU, true-positives, false-positives for required Threshold |
| | | if (prob > thresh_calc_avg_iou) { |
| | | if (truth_index > -1) { |
| | | int z, found = 0; |
| | | for (z = checkpoint_detections_count; z < detections_count-1; ++z) |
| | | if (detections[z].unique_truth_index == truth_index) { |
| | | found = 1; break; |
| | | } |
| | | |
| | | if(truth_index > -1 && found == 0) { |
| | | avg_iou += max_iou; |
| | | ++tp_for_thresh; |
| | | } |
| | |
| | | } |
| | | } |
| | | |
| | | avg_iou = avg_iou / (tp_for_thresh + fp_for_thresh); |
| | | if((tp_for_thresh + fp_for_thresh) > 0) |
| | | avg_iou = avg_iou / (tp_for_thresh + fp_for_thresh); |
| | | |
| | | |
| | | // SORT(detections) |
| | |
| | | void calc_anchors(char *datacfg, int num_of_clusters, int width, int height, int show) |
| | | { |
| | | printf("\n num_of_clusters = %d, width = %d, height = %d \n", num_of_clusters, width, height); |
| | | if (width < 0 || height < 0) { |
| | | printf("Usage: darknet detector calc_anchors data/voc.data -num_of_clusters 9 -width 416 -height 416 \n"); |
| | | printf("Error: set width and height \n"); |
| | | return; |
| | | } |
| | | |
| | | //float pointsdata[] = { 1,1, 2,2, 6,6, 5,5, 10,10 }; |
| | | float *rel_width_height_array = calloc(1000, sizeof(float)); |
| | |
| | | } |
| | | #endif // OPENCV |
| | | |
| | | void test_detector(char *datacfg, char *cfgfile, char *weightfile, char *filename, float thresh, float hier_thresh, int dont_show) |
| | | void test_detector(char *datacfg, char *cfgfile, char *weightfile, char *filename, float thresh, |
| | | float hier_thresh, int dont_show, int ext_output) |
| | | { |
| | | list *options = read_data_cfg(datacfg); |
| | | char *name_list = option_find_str(options, "names", "data/names.list"); |
| | |
| | | while(1){ |
| | | if(filename){ |
| | | strncpy(input, filename, 256); |
| | | if (input[strlen(input) - 1] == 0x0d) input[strlen(input) - 1] = 0; |
| | | if(strlen(input) > 0) |
| | | if (input[strlen(input) - 1] == 0x0d) input[strlen(input) - 1] = 0; |
| | | } else { |
| | | printf("Enter Image Path: "); |
| | | fflush(stdout); |
| | |
| | | } |
| | | image im = load_image_color(input,0,0); |
| | | int letterbox = 0; |
| | | image sized = resize_image(im, net.w, net.h); |
| | | //image sized = letterbox_image(im, net.w, net.h); letterbox = 1; |
| | | //image sized = resize_image(im, net.w, net.h); |
| | | image sized = letterbox_image(im, net.w, net.h); letterbox = 1; |
| | | layer l = net.layers[net.n-1]; |
| | | |
| | | //box *boxes = calloc(l.w*l.h*l.n, sizeof(box)); |
| | |
| | | |
| | | float *X = sized.data; |
| | | time= what_time_is_it_now(); |
| | | //network_predict(net, X); |
| | | network_predict_image(&net, im); letterbox = 1; |
| | | network_predict(net, X); |
| | | //network_predict_image(&net, im); letterbox = 1; |
| | | printf("%s: Predicted in %f seconds.\n", input, (what_time_is_it_now()-time)); |
| | | //get_region_boxes(l, 1, 1, thresh, probs, boxes, 0, 0); |
| | | // if (nms) do_nms_sort_v2(boxes, probs, l.w*l.h*l.n, l.classes, nms); |
| | |
| | | int nboxes = 0; |
| | | detection *dets = get_network_boxes(&net, im.w, im.h, thresh, hier_thresh, 0, 1, &nboxes, letterbox); |
| | | if (nms) do_nms_sort(dets, nboxes, l.classes, nms); |
| | | draw_detections_v3(im, dets, nboxes, thresh, names, alphabet, l.classes); |
| | | draw_detections_v3(im, dets, nboxes, thresh, names, alphabet, l.classes, ext_output); |
| | | free_detections(dets, nboxes); |
| | | save_image(im, "predictions"); |
| | | if (!dont_show) { |
| | |
| | | int cam_index = find_int_arg(argc, argv, "-c", 0); |
| | | int frame_skip = find_int_arg(argc, argv, "-s", 0); |
| | | int num_of_clusters = find_int_arg(argc, argv, "-num_of_clusters", 5); |
| | | int width = find_int_arg(argc, argv, "-width", 13); |
| | | int height = find_int_arg(argc, argv, "-height", 13); |
| | | int width = find_int_arg(argc, argv, "-width", -1); |
| | | int height = find_int_arg(argc, argv, "-height", -1); |
| | | // extended output in test mode (output of rect bound coords) |
| | | // and for recall mode (extended output table-like format with results for best_class fit) |
| | | int ext_output = find_arg(argc, argv, "-ext_output"); |
| | | if(argc < 4){ |
| | | fprintf(stderr, "usage: %s %s [train/test/valid] [cfg] [weights (optional)]\n", argv[0], argv[1]); |
| | | return; |
| | |
| | | char *cfg = argv[4]; |
| | | char *weights = (argc > 5) ? argv[5] : 0; |
| | | if(weights) |
| | | if (weights[strlen(weights) - 1] == 0x0d) weights[strlen(weights) - 1] = 0; |
| | | if(strlen(weights) > 0) |
| | | if (weights[strlen(weights) - 1] == 0x0d) weights[strlen(weights) - 1] = 0; |
| | | char *filename = (argc > 6) ? argv[6]: 0; |
| | | if(0==strcmp(argv[2], "test")) test_detector(datacfg, cfg, weights, filename, thresh, hier_thresh, dont_show); |
| | | if(0==strcmp(argv[2], "test")) test_detector(datacfg, cfg, weights, filename, thresh, hier_thresh, dont_show, ext_output); |
| | | else if(0==strcmp(argv[2], "train")) train_detector(datacfg, cfg, weights, gpus, ngpus, clear, dont_show); |
| | | else if(0==strcmp(argv[2], "valid")) validate_detector(datacfg, cfg, weights, outfile); |
| | | else if(0==strcmp(argv[2], "recall")) validate_detector_recall(datacfg, cfg, weights); |
| | |
| | | char *name_list = option_find_str(options, "names", "data/names.list"); |
| | | char **names = get_labels(name_list); |
| | | if(filename) |
| | | if (filename[strlen(filename) - 1] == 0x0d) filename[strlen(filename) - 1] = 0; |
| | | if(strlen(filename) > 0) |
| | | if (filename[strlen(filename) - 1] == 0x0d) filename[strlen(filename) - 1] = 0; |
| | | demo(cfg, weights, thresh, hier_thresh, cam_index, filename, names, classes, frame_skip, prefix, out_filename, |
| | | http_stream_port, dont_show); |
| | | } |