The dataset viewer is not available for this dataset.
Error code: ConfigNamesError
Exception: RuntimeError
Message: Dataset scripts are no longer supported, but found food101.py
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 66, in compute_config_names_response
config_names = get_dataset_config_names(
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 161, in get_dataset_config_names
dataset_module = dataset_module_factory(
^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 1207, in dataset_module_factory
raise e1 from None
File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 1167, in dataset_module_factory
raise RuntimeError(f"Dataset scripts are no longer supported, but found {filename}")
RuntimeError: Dataset scripts are no longer supported, but found food101.pyNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Dataset Card for Food-101
Dataset Details
Dataset Description
This is a dataset of 101 food categories, with 101,000 images. For each class, 250 manually reviewed test images are provided as well as 750 training images. On purpose, the training images were not cleaned, and thus still contain some amount of noise. This comes mostly in the form of intense colors and sometimes wrong labels. All images were rescaled to have a maximum side length of 512 pixels.
Dataset Sources
- Homepage: https://data.vision.ee.ethz.ch/cvl/datasets_extra/food-101/
- Paper: Bossard, L., Guillaumin, M., & Van Gool, L. (2014). Food-101–mining discriminative components with random forests. In Computer vision–ECCV 2014: 13th European conference, zurich, Switzerland, September 6-12, 2014, proceedings, part VI 13 (pp. 446-461). Springer International Publishing.
Dataset Structure
Total images: 101,000
Classes: 101 food categories
Splits:
Train: 75,750 images
Test: 25,250 images
Image specs: JPG format, variable resolution (maximum side length of 512), RGB
Example Usage
Below is a quick example of how to load this dataset via the Hugging Face Datasets library.
from datasets import load_dataset
# Load the dataset
dataset = load_dataset("randall-lab/food101", split="train", trust_remote_code=True)
# dataset = load_dataset("randall-lab/food101", split="test", trust_remote_code=True)
# Access a sample from the dataset
example = dataset[0]
image = example["image"]
label = example["label"]
image.show() # Display the image
print(f"Label: {label}")
Citation
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} }
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