2022年11月23日 · 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.

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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.

The Food-101 dataset consists of 101 food categories with 750 training and 250 test images per category, making a total of 101k images. The labels for the test images have been manually cleaned, while the training set contains some noise.

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 ...

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.

In the paper, Food-101 – Mining Discriminative Components with Random Forests, they introduce the Food-101 dataset. There are 101 different classes of food, with 1000 labeled images per class available for supervised training.

The Food-101 Data Set. The Food-101 is 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.

"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"