Fixed utils.c for short lines.
| | |
| | | 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); |
| | |
| | | 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); |
| | | else if(0==strcmp(argv[2], "train")) train_detector(datacfg, cfg, weights, gpus, ngpus, clear, dont_show); |
| | |
| | | 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); |
| | | } |
| | |
| | | int f; |
| | | for (f = 0; f < l->n; ++f) |
| | | { |
| | | l->biases[f] = l->biases[f] - l->scales[f] * l->rolling_mean[f] / (sqrtf(l->rolling_variance[f]) + .000001f); |
| | | l->biases[f] = l->biases[f] - (double)l->scales[f] * l->rolling_mean[f] / (sqrt((double)l->rolling_variance[f]) + .000001f); |
| | | |
| | | const size_t filter_size = l->size*l->size*l->c; |
| | | int i; |
| | | for (i = 0; i < filter_size; ++i) { |
| | | int w_index = f*filter_size + i; |
| | | |
| | | l->weights[w_index] = l->weights[w_index] * l->scales[f] / (sqrtf(l->rolling_variance[f]) + .000001f); |
| | | l->weights[w_index] = (double)l->weights[w_index] * l->scales[f] / (sqrt((double)l->rolling_variance[f]) + .000001f); |
| | | } |
| | | } |
| | | |
| | |
| | | for (i = 0; i < len; ++i) { |
| | | if (a[i] == ',') ++n; |
| | | } |
| | | for (i = 0; i < n; ++i) { |
| | | for (i = 0; i < n && i < total*2; ++i) { |
| | | float bias = atof(a); |
| | | l.biases[i] = bias; |
| | | a = strchr(a, ',') + 1; |
| | |
| | | for(i = 0; i < len; ++i){ |
| | | if (a[i] == ',') ++n; |
| | | } |
| | | for(i = 0; i < n; ++i){ |
| | | for(i = 0; i < n && i < num*2; ++i){ |
| | | float bias = atof(a); |
| | | l.biases[i] = bias; |
| | | a = strchr(a, ',')+1; |
| | |
| | | fgets(&line[curr], readsize, fp); |
| | | curr = strlen(line); |
| | | } |
| | | if(line[curr-2] == 0x0d) line[curr-2] = 0x00; |
| | | if(line[curr-1] == 0x0a) line[curr-1] = 0x00; |
| | | if(curr >= 2) |
| | | if(line[curr-2] == 0x0d) line[curr-2] = 0x00; |
| | | |
| | | if(curr >= 1) |
| | | if(line[curr-1] == 0x0a) line[curr-1] = 0x00; |
| | | |
| | | return line; |
| | | } |