| | |
| | | float avg_loss = -1; |
| | | network *nets = calloc(ngpus, sizeof(network)); |
| | | |
| | | int iter_save; |
| | | iter_save = 100; |
| | | |
| | | srand(time(0)); |
| | | int seed = rand(); |
| | | int i; |
| | |
| | | args.small_object = l.small_object; |
| | | args.d = &buffer; |
| | | args.type = DETECTION_DATA; |
| | | args.threads = 4;// 8; |
| | | args.threads = 8; // 64 |
| | | |
| | | args.angle = net.angle; |
| | | args.exposure = net.exposure; |
| | |
| | | if(l.random && count++%10 == 0){ |
| | | printf("Resizing\n"); |
| | | int dim = (rand() % 12 + (init_w/32 - 5)) * 32; // +-160 |
| | | //int dim = (rand() % 10 + 10) * 32; |
| | | //if (get_current_batch(net)+100 > net.max_batches) dim = 544; |
| | | //int dim = (rand() % 4 + 16) * 32; |
| | | printf("%d\n", dim); |
| | |
| | | #endif // OPENCV |
| | | |
| | | //if (i % 1000 == 0 || (i < 1000 && i % 100 == 0)) { |
| | | if (i % 100 == 0) { |
| | | //if (i % 100 == 0) { |
| | | if(i >= iter_save) { |
| | | iter_save += 100; |
| | | #ifdef GPU |
| | | if (ngpus != 1) sync_nets(nets, ngpus, 0); |
| | | #endif |
| | |
| | | float box_h = points->data.fl[i * 2 + 1]; |
| | | //int cluster_idx = labels->data.i[i]; |
| | | int cluster_idx = 0; |
| | | float min_dist = 1000000; |
| | | float min_dist = FLT_MAX; |
| | | for (j = 0; j < num_of_clusters; ++j) { |
| | | float anchor_w = centers->data.fl[j * 2]; |
| | | float anchor_h = centers->data.fl[j * 2 + 1]; |