Food 101 Dataset

Name: Food 101
Creator: Bossard, Lukas and Guillaumin, Matthieu and Van Gool, Luc
License: https://creativecommons.org/publicdomain/zero/1.0/

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Visualization of the Food 101 dataset in the Deep Lake UI

Food 101 Dataset dataset

What is Food 101 Dataset Dataset?

Food 101 dataset comprises of 101 food classifications, with 101,000 pictures. For each class, 250 physically assessed test pictures are given as well as 750 preparation pictures. The labels for the test images have been manually cleaned, while the training set contains some intentional noise.

Download Food 101 Dataset Dataset in Python

Instead of downloading the Food 101 Dataset dataset in Python, you can effortlessly load it in Python via our Deep Lake open-source with just one line of code.

Load Food 101 Dataset Dataset Training Subset in Python

				
					import deeplake
ds = deeplake.load('hub://activeloop/food-101-dataset-train')

Food 101 Dataset Dataset Structure

Food 101 Data Fields

images: tensor containing the various food image.
labels: tensor contains different categories of foods.
classes: tensor to various classes of food.

Food 101 Data Splits

The Food 101 dataset training set is composed of 71096 images.

How to use Food 101 Dataset Dataset with PyTorch and TensorFlow in Python

Train a model on Food 101 Dataset dataset with PyTorch in Python

Let’s use Deep Lake built-in PyTorch one-line dataloader to connect the data to the compute:

				
					dataloader = ds.pytorch(num_workers=0, batch_size=4, shuffle=False)

Train a model on Food 101 Dataset dataset with TensorFlow in Python

				
					dataloader = ds.tensorflow()

Additional Information about Food 101 Dataset Dataset

Food 101 Dataset Dataset Description

Homepage:https://data.vision.ee.ethz.ch/cvl/datasets_extra/food-101/
Repository: N/A
Paper: Introduced by Lukas Bossard et al. in Food-101 – Mining Discriminative Components with Random Forests
Point of Contact: N/A

Food 101 Dataset Dataset Curators

Bossard, Lukas and Guillaumin, Matthieu and Van Gool, Luc

Food 101 Dataset Dataset Licensing Information

Deep Lake users may have access to a variety of publicly available datasets. We do not host or distribute these datasets, vouch for their quality or fairness, or claim that you have a license to use the datasets. It is your responsibility to determine whether you have permission to use the datasets under their license.

If you’re a dataset owner and do not want your dataset to be included in this library, please get in touch through a GitHub issue. Thank you for your contribution to the ML community!

Food 101 Dataset Dataset 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}
}

Food 101 Dataset Dataset FAQs

What is the Food 101 Dataset dataset for Python?

The Food 101 dataset has 101 food classifications, with 101,000 pictures. The labels for the test images have been manually cleaned, while the training set images have intentional noise.

How to download the Food 101 Dataset dataset in Python?

You can load Food 101 dataset fast with one line of code using the open-source package Activeloop Deep Lake in Python. See detailed instructions on how to load Food 101 dataset training subset in Python.

How can I use Food 101 Dataset dataset in PyTorch or TensorFlow?

You can stream Food 101 dataset while training a model in PyTorch or TensorFlow with one line of code using the open-source package Activeloop Deep Lake in Python. See detailed instructions on how to train a model on Food 101 dataset with PyTorch in Python or train a model on Food 101 dataset with TensorFlow in Python.