| | |
| | | |
| | | free(boxes); |
| | | free_ptrs((void **)probs, l.w*l.h*l.n); |
| | | |
| | | //correct_region_boxes(dets, l.w*l.h*l.n, w, h, net_w, net_h, relative); |
| | | correct_yolo_boxes(dets, l.w*l.h*l.n, w, h, net_w, net_h, relative, letter); |
| | | } |
| | | |
| | | void fill_network_boxes(network *net, int w, int h, float thresh, float hier, int *map, int relative, detection *dets, int letter) |
| | |
| | | layer *l = &net.layers[j]; |
| | | |
| | | if (l->type == CONVOLUTIONAL) { |
| | | printf(" Fuse Convolutional layer \t\t l->size = %d \n", l->size); |
| | | //printf(" Merges Convolutional-%d and batch_norm \n", j); |
| | | |
| | | if (l->batch_normalize) { |
| | | int f; |
| | |
| | | } |
| | | |
| | | l->batch_normalize = 0; |
| | | push_convolutional_layer(*l); |
| | | #ifdef GPU |
| | | if (gpu_index >= 0) { |
| | | push_convolutional_layer(*l); |
| | | } |
| | | #endif |
| | | } |
| | | } |
| | | else { |
| | | printf(" Skip layer: %d \n", l->type); |
| | | //printf(" Fusion skip layer type: %d \n", l->type); |
| | | } |
| | | } |
| | | } |