Food-101 Computer Vision Project
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downloadsThe Food-101 Dataset
From the authors:
We introduce a challenging data set 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.
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This dataset was accessed from the TensorFlow Datasets Library: https://www.tensorflow.org/datasets/catalog/food101
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The original dataset and paper are accewssible from this page: https://data.vision.ee.ethz.ch/cvl/datasets_extra/food-101/
Citation (Original Authors):
@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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Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
food-101_dataset,
title = { Food-101 Dataset },
type = { Open Source Dataset },
author = { Popular Benchmarks },
howpublished = { \url{ https://universe.roboflow.com/popular-benchmarks/food-101 } },
url = { https://universe.roboflow.com/popular-benchmarks/food-101 },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2022 },
month = { dec },
note = { visited on 2024-12-30 },
}