--- pretty_name: Snacks task_categories: - image-classification - object-detection - computer-vision license: cc-by-4.0 --- # Dataset Card for Snacks ## Dataset Summary This is a dataset of 20 different types of snack foods that accompanies the book [Machine Learning by Tutorials](https://www.raywenderlich.com/books/machine-learning-by-tutorials/v2.0). The images were taken from the [Google Open Images dataset](https://storage.googleapis.com/openimages/web/index.html), release 2017_11. ## Dataset Structure Number of images in the train/validation/test splits: ```nohighlight train 4838 val 955 test 952 total 6745 ``` Total images in each category: ```nohighlight apple 350 banana 350 cake 349 candy 349 carrot 349 cookie 349 doughnut 350 grape 350 hot dog 350 ice cream 350 juice 350 muffin 348 orange 349 pineapple 340 popcorn 260 pretzel 204 salad 350 strawberry 348 waffle 350 watermelon 350 ``` To save space in the download, the images were resized so that their smallest side is 256 pixels. All EXIF information was removed. ### Annotations Included in the **annotations** folder are three CSV files with bounding box annotations for the images in the dataset, although not all images have annotations and some images have multiple annotations. The columns in the CSV files are: - `image_id`: the filename of the image without the .jpg extension - `x_min, x_max, y_min, y_max`: normalized bounding box coordinates, i.e. in the range [0, 1] - `class_name`: the class that belongs to the bounding box - `folder`: the class that belongs to the image as a whole, which is also the name of the folder that contains the image ### Data Splits Train, Test, Validation ## Licensing Information Just like the images from Google Open Images, the snacks dataset is licensed under the terms of the Creative Commons license. The images are listed as having a [CC BY 2.0](https://creativecommons.org/licenses/by/2.0/) license. The annotations are licensed by Google Inc. under a [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) license. The **credits.csv** file contains the original URL, author information and license for each image.