Datasets:
Tasks:
Other
Languages:
English
Multilinguality:
monolingual
Size Categories:
10K<n<100K
Language Creators:
crowdsourced
Annotations Creators:
crowdsourced
Source Datasets:
extended|other-foodspotting
License:
unknown
Dataset Preview
Go to dataset viewer
The dataset preview is not available for this dataset.
Cannot get the split names for the dataset.
Error code: SplitsNamesError
Exception: TypeError
Message: __init__() got an unexpected keyword argument 'image_file_path_column'
Traceback: Traceback (most recent call last):
File "/src/workers/datasets_based/src/datasets_based/workers/splits.py", line 119, in compute_splits_response
split_items = get_dataset_split_full_names(dataset=dataset, use_auth_token=use_auth_token)
File "/src/workers/datasets_based/src/datasets_based/workers/splits.py", line 76, in get_dataset_split_full_names
return [
File "/src/workers/datasets_based/src/datasets_based/workers/splits.py", line 79, in <listcomp>
for split in get_dataset_split_names(path=dataset, config_name=config, use_auth_token=use_auth_token)
File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 442, in get_dataset_split_names
info = get_dataset_config_info(
File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 367, in get_dataset_config_info
builder = load_dataset_builder(
File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/load.py", line 1519, in load_dataset_builder
builder_instance: DatasetBuilder = builder_cls(
File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1357, in __init__
super().__init__(*args, **kwargs)
File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/builder.py", line 332, in __init__
info.update(self._info())
File "/tmp/modules-cache/datasets_modules/datasets/nateraw--food101/f2a22ebb9bef11b83a4f38d7f08244a3d4dc00794ca269d224e1875b44d5539a/food101.py", line 165, in _info
task_templates=[ImageClassification(image_file_path_column="image", label_column="label", labels=_NAMES)],
TypeError: __init__() got an unexpected keyword argument 'image_file_path_column'Need help to make the dataset viewer work? Open an discussion for direct support.
YAML Metadata Warning:
The task_ids "other-other-image-classification" is not in the official list: acceptability-classification, entity-linking-classification, fact-checking, intent-classification, language-identification, multi-class-classification, multi-label-classification, multi-input-text-classification, natural-language-inference, semantic-similarity-classification, sentiment-classification, topic-classification, semantic-similarity-scoring, sentiment-scoring, sentiment-analysis, hate-speech-detection, text-scoring, named-entity-recognition, part-of-speech, parsing, lemmatization, word-sense-disambiguation, coreference-resolution, extractive-qa, open-domain-qa, closed-domain-qa, news-articles-summarization, news-articles-headline-generation, dialogue-generation, dialogue-modeling, language-modeling, text-simplification, explanation-generation, abstractive-qa, open-domain-abstractive-qa, closed-domain-qa, open-book-qa, closed-book-qa, slot-filling, masked-language-modeling, keyword-spotting, speaker-identification, audio-intent-classification, audio-emotion-recognition, audio-language-identification, multi-label-image-classification, multi-class-image-classification, face-detection, vehicle-detection, instance-segmentation, semantic-segmentation, panoptic-segmentation, image-captioning, grasping, task-planning, tabular-multi-class-classification, tabular-multi-label-classification, tabular-single-column-regression, rdf-to-text, multiple-choice-qa, multiple-choice-coreference-resolution, document-retrieval, utterance-retrieval, entity-linking-retrieval, fact-checking-retrieval, univariate-time-series-forecasting, multivariate-time-series-forecasting, visual-question-answering, document-question-answering
Dataset Card for Food-101
Dataset Summary
This dataset consists 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.
Supported Tasks and Leaderboards
- image-classification
Languages
English
Dataset Structure
Data Instances
A sample from the training set is provided below:
{
'image': '/root/.cache/huggingface/datasets/downloads/extracted/6e1e8c9052e9f3f7ecbcb4b90860668f81c1d36d86cc9606d49066f8da8bfb4f/food-101/images/churros/1004234.jpg',
'label': 23
}
Data Fields
The data instances have the following fields:
image: astringfilepath to an image.label: anintclassification label.
Data Splits
| name | train | validation |
|---|---|---|
| food101 | 75750 | 25250 |
Dataset Creation
Curation Rationale
[More Information Needed]
Source Data
Initial Data Collection and Normalization
[More Information Needed]
Who are the source language producers?
[More Information Needed]
Annotations
Annotation process
[More Information Needed]
Who are the annotators?
[More Information Needed]
Personal and Sensitive Information
[More Information Needed]
Considerations for Using the Data
Social Impact of Dataset
[More Information Needed]
Discussion of Biases
[More Information Needed]
Other Known Limitations
[More Information Needed]
Additional Information
Dataset Curators
[More Information Needed]
Licensing Information
[More Information Needed]
Citation Information
@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}
}
Contributions
Thanks to @nateraw for adding this dataset.
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