Update README.md

README.md

@@ -2,6 +2,8 @@
 license: agpl-3.0
 datasets:
 - openfoodfacts/front_image_classification
+base_model:
+- Ultralytics/YOLO11
 ---
 
 # Front image classification model
@@ -39,6 +41,23 @@ v1.0 of the [front_image_classification](https://huggingface.co/datasets/openfoo
 - Image size: 448
 - Albumentation augmentation
 
+[This script](https://github.com/openfoodfacts/openfoodfacts-ai/blob/dbbec40a3d964124cd7c8d838023be4a10d6c0be/front-image-classification/train.py) was used for training the model.
+
+The augmentation pipeline used for prediction:
+
+```python
+A.Compose(
+        [
+            A.LongestMaxSize(max_size=max_size, p=1.0),
+            A.PadIfNeeded(min_height=max_size, min_width=max_size, p=1.0),
+            A.Normalize(mean=DEFAULT_MEAN, std=DEFAULT_STD, p=1.0),
+            ToTensorV2(p=1.0),
+        ]
+    )
+```
+
+For optimal performance, it is advised to keep the same preprocessing pipeline during inference.
+
 ## Evaluation
 
 accuracy: 0.9525