| | |
| | | int rescore = option_find_int(options, "rescore", 0); |
| | | int joint = option_find_int(options, "joint", 0); |
| | | int objectness = option_find_int(options, "objectness", 0); |
| | | int background = option_find_int(options, "background", 1); |
| | | int background = option_find_int(options, "background", 0); |
| | | detection_layer layer = make_detection_layer(params.batch, params.inputs, classes, coords, joint, rescore, background, objectness); |
| | | option_unused(options); |
| | | return layer; |
| | |
| | | }else{ |
| | | fprintf(stderr, "Type not recognized: %s\n", s->type); |
| | | } |
| | | l.dontload = option_find_int_quiet(options, "dontload", 0); |
| | | net.layers[count] = l; |
| | | free_section(s); |
| | | n = n->next; |
| | |
| | | int i; |
| | | for(i = 0; i < net->n && i < cutoff; ++i){ |
| | | layer l = net->layers[i]; |
| | | if (l.dontload) continue; |
| | | if(l.type == CONVOLUTIONAL){ |
| | | int num = l.n*l.c*l.size*l.size; |
| | | fread(l.biases, sizeof(float), l.n, fp); |