ONNX

Front image classification model

This model classifies Open Food Facts images into two classes:

  • front (ID 0)
  • other (ID 1)

Front images are the "default" image of a product, displayed on Open Food Facts product page. A front image is most of the time a photo of the front side of the product packaging. It's useful to be able to detect front images so that we can update the front image with a newer version (when the packaging changes for example).

Model Details

Model Description

  • Developed by: Raphaël Bournhonesque
  • Model type: Image Classification
  • License: AGPL 3.0
  • Finetuned from model [optional]: Yolo11n-cls

Uses

This model is intended to be used on Open Food Facts images only (images of food packaged products).

Training Details

Training Data

v1.0 of the front_image_classification dataset was used to train the model.

Training Procedure

  • Epochs: 100
  • Image size: 448
  • Albumentation augmentation

This script was used for training the model.

The augmentation pipeline used for prediction:

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

Export

An ONNX export can be found in weights/model.onnx.

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