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Docs: clarify pretrained model configuration, metadata, and backbone usage #37

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22 changes: 22 additions & 0 deletions README.md
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Expand Up @@ -103,3 +103,25 @@ To get more information about the AOC Fruit Detector, please refer to [Wiki page
---

[wiki_page]: https://github.com/LCAS/aoc_fruit_detector/wiki



## Pretrained Models and Configuration

### Model ↔ Class Mapping
Each pretrained model expects a specific number of classes.
When loading a model, `cfg.MODEL.ROI_HEADS.NUM_CLASSES` must match
the number of classes used during training.

| Model file | Task | num_classes | Metadata file |
|----------------------------------|-----------------|-------------|---------------|
| aoc_ripeness.pth | Ripeness | 2 | metadata.pkl |
| aoc_strawberry_class_fruit.pth | Fruit detection | X | Not provided |

⚠️ Currently, metadata files are only provided for the ripeness model.

### Backbone Configuration
The default backbone is:
COCO-InstanceSegmentation/mask_rcnn_R_101_FPN_3x.yaml

Other Detectron2 backbones may work, but have not been officially tested.
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