# Model Registry

Each trained model lives in its own versioned subdirectory:

```
models/registry/<version-id>/
├── weights.pt           ← primary PyTorch checkpoint
├── exports/             ← derived export formats
│   ├── model.onnx
│   ├── model.engine     ← TensorRT (hardware-specific, gitignored)
│   └── pruned_weights.pt
└── metadata.json        ← version info and metrics
```

## Naming convention

`<architecture>-<task>-<variant>-<YYYY-MM-DD>`

Examples:
- `yolo26n-seg-overlap-false-2026-04-12` — yolo26n, segmentation, overlap_mask=False, trained 2026-04-12
- `yolo26n-seg-multiscale-2026-03-16` — yolo26n, segmentation, multi-scale training

## metadata.json schema

| Field | Description |
|---|---|
| `model_id` | Same as directory name |
| `family` | Base architecture (e.g. `yolo26n`) |
| `task` | `segmentation`, `detection`, etc. |
| `training_date` | ISO date of training run |
| `export_formats` | List of available formats |
| `metrics` | mAP, precision, recall, etc. |

## Active production model

See `models/active/production.json` for the currently deployed version.