README.md

---
dataset_info:
  features:
  - name: image_id
    dtype: string
  - name: image
    dtype: image
  - name: width
    dtype: int64
  - name: height
    dtype: int64
  - name: meta
    struct:
    - name: barcode
      dtype: string
    - name: off_image_id
      dtype: string
    - name: image_url
      dtype: string
  - name: objects
    struct:
    - name: bbox
      sequence:
        sequence: float32
    - name: category_id
      sequence: int64
    - name: category_name
      sequence: string
  splits:
  - name: val
    num_bytes: 32285921
    num_examples: 82
  - name: train
    num_bytes: 178448483
    num_examples: 502
  download_size: 352038777
  dataset_size: 210734404
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: val
    path: data/val-*
license: cc-by-sa-3.0
task_categories:
- object-detection
tags:
- food
size_categories:
- n<1K
---
# Open Food Facts Nutriscore detection dataset

This dataset was used to train the Nutri-score object detection model running in production at Open Food Facts.

Images were collected from the Open Food Facts database and labeled manually.
Just like the [original images](https://world.openfoodfacts.org/data), the images in this dataset are licensed under the Creative Commons Attribution Share Alike license (CC-BY-SA 3.0).


## Fields

- `image_id`: Unique identifier for the image, generated from the barcode and the image number.
- `image`: Image data.
- `width`: Image original width in pixels.
- `height`: Image original height in pixels.
- `meta`: Additional metadata.
    - `barcode`: Product barcode.
    - `off_image_id`: Open Food Facts image number.
    - `image_url`: URL to the image on the Open Food Facts website.
- `objects`: Object detection annotations.
    - `bbox`: List of bounding boxes in the format (y_min, x_min, y_max, x_max).
              Coordinates are normalized between 0 and 1, using the top-left corner as the origin.
    - `category_id`: List of category IDs.
    - `category_name`: List of category names.


## Versions

- `1.0`: Original data used to train the [tf-nutriscore-1.0 model](https://github.com/openfoodfacts/robotoff-models/releases/tag/tf-nutriscore-1.0).
- `2.0`: New version of the dataset with improvements over the original version: the bounding boxes are more tightly cropped around the Nutri-score, some labeling errors were corrected, and images for which the model was failing were added to the dataset to improve future versions of the model.