| | |
| | | |
| | | int init_w = net.w; |
| | | int init_h = net.h; |
| | | int iter_save; |
| | | iter_save = get_current_batch(net); |
| | | |
| | | load_args args = {0}; |
| | | args.w = net.w; |
| | |
| | | args.small_object = l.small_object; |
| | | args.d = &buffer; |
| | | args.type = DETECTION_DATA; |
| | | args.threads = 4;// 8; |
| | | args.threads = 64; // 8 |
| | | |
| | | 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 + 100)) { |
| | | iter_save = i; |
| | | #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]; |
| | |
| | | } |
| | | image im = load_image_color(input,0,0); |
| | | image sized = resize_image(im, net.w, net.h); |
| | | //image sized = letterbox_image(im, net.w, net.h); |
| | | layer l = net.layers[net.n-1]; |
| | | |
| | | box *boxes = calloc(l.w*l.h*l.n, sizeof(box)); |