Datasets:
Tasks:
Image Classification
Modalities:
Image
Languages:
English
Size:
10K<n<100K
Libraries:
FiftyOne
File size: 2,915 Bytes
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---
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
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}
}
``` |