| model: | |
| num_classes: 80 | |
| input_size: 384 | |
| stem_channels: 32 | |
| backbone_channels: [48, 96, 192, 256] | |
| backbone_depths: [1, 2, 3, 2] | |
| hidden_dim: 192 | |
| fpn_depth: 1 | |
| latent_count: 32 | |
| latent_pool_sizes: [8, 4, 2] | |
| latent_layers: 1 | |
| decoder_layers: 3 | |
| num_queries: 100 | |
| num_heads: 6 | |
| local_points: 4 | |
| dropout: 0.0 | |
| dense_aux: true | |
| loss: | |
| cost_class: 2.0 | |
| cost_bbox: 5.0 | |
| cost_giou: 2.0 | |
| weight_class: 2.0 | |
| weight_bbox: 5.0 | |
| weight_giou: 2.0 | |
| weight_dense: 1.0 | |
| focal_alpha: 0.25 | |
| focal_gamma: 2.0 | |
| aux_weight: 1.0 | |
| dense_topk: 3 | |
| train: | |
| epochs: 20 | |
| batch_size: 8 | |
| workers: 4 | |
| lr: 0.0002 | |
| backbone_lr: 0.0001 | |
| min_lr_ratio: 0.05 | |
| weight_decay: 0.05 | |
| warmup_steps: 200 | |
| clip_grad_norm: 0.1 | |
| amp: true | |
| ema_decay: 0.9998 | |
| seed: 42 | |
| eval_every: 1 | |
| print_freq: 20 | |
| data: | |
| train_image_dir: train2017 | |
| train_annotations: annotations/instances_train2017.json | |
| val_image_dir: val2017 | |
| val_annotations: annotations/instances_val2017.json | |
| hflip_prob: 0.5 | |
| scale_range: [0.7, 1.0] | |
| mean: [0.485, 0.456, 0.406] | |
| std: [0.229, 0.224, 0.225] | |