README.md

---
annotations_creators: []
language: en
size_categories:
- 10K<n<100K
task_categories:
- image-classification
task_ids: []
pretty_name: Food101
tags:
- fiftyone
- image
- image-classification
dataset_summary: >




  This is a [FiftyOne](https://github.com/voxel51/fiftyone) dataset with 35000
  samples.


  ## Installation


  If you haven't already, install FiftyOne:


  ```bash

  pip install -U fiftyone

  ```


  ## Usage


  ```python

  import fiftyone as fo

  import fiftyone.utils.huggingface as fouh


  # Load the dataset

  # Note: other available arguments include 'max_samples', etc

  dataset = fouh.load_from_hub("Voxel51/Food101")


  # Launch the App

  session = fo.launch_app(dataset)

  ```
---

# Dataset Card for Food-101

![image](food-101.gif)


This is a [FiftyOne](https://github.com/voxel51/fiftyone) dataset with 35000 samples.

**Note:** This dataset is subset of the full Food101 dataset. The recipe notebook for creating this dataset can be found [here](https://colab.research.google.com/drive/11ZDZxaRTVR3DjANNR4p5CnCYqlTYmpfT)

## Installation

If you haven't already, install FiftyOne:

```bash
pip install -U fiftyone
```

## Usage

```python
import fiftyone as fo
import fiftyone.utils.huggingface as fouh

# Load the dataset
# Note: other available arguments include 'max_samples', etc
dataset = fouh.load_from_hub("Voxel51/Food101")

# Launch the App
session = fo.launch_app(dataset)
```


## Dataset Details

### Dataset Description

The Food-101 dataset is a large-scale dataset for food recognition, consisting of 101,000 images across 101 different food categories. 

Here are the key details:

- Contains a total of 101,000 images
- Each food class has 1,000 images, with 750 training images and 250 test images per class
- All images were rescaled to have a maximum side length of 512 pixels

- **Curated by:** Lukas Bossard, Matthieu Guillaumin, Luc Van Gool
- **Funded by:** Computer Vision Lab, ETH Zurich, Switzerland
- **Shared by:** [Harpreet Sahota](twitter.com/datascienceharp), Hacker-in-Residence at Voxel51
- **Language(s) (NLP):** en
- **License:** The dataset images come from Foodspotting and are not owned by the creators of the Food-101 dataset (ETH Zurich). Any use beyond scientific fair use must be negotiated with the respective picture owners according to the Foodspotting terms of use

### Dataset Sources

- **Repository:** https://huggingface.co/datasets/ethz/food101
- **Website:** https://data.vision.ee.ethz.ch/cvl/datasets_extra/food-101/
- **Paper:** https://data.vision.ee.ethz.ch/cvl/datasets_extra/food-101/static/bossard_eccv14_food-101.pdf

## Citation

**BibTeX:**

```bibtex
@inproceedings{bossard14,
  title = {Food-101 -- Mining Discriminative Components with Random Forests},
  author = {Bossard, Lukas and Guillaumin, Matthieu and Van Gool, Luc},
  booktitle = {European Conference on Computer Vision},
  year = {2014}
}
```