{"url":"/dataset/freiburg-groceries","name":"Freiburg Groceries","full_name":"Freiburg Groceries","description_markdown":"**Freiburg Groceries** is a groceries classification dataset consisting of 5000 images of size 256x256, divided into 25 categories. It has imbalanced class sizes ranging from 97 to 370 images per class. Images were taken in various aspect ratios and padded to squares.\r\n\r\nSource: [XNAS: Neural Architecture Search with Expert Advice](https://arxiv.org/abs/1906.08031)\r\nImage Source: [http://aisdatasets.informatik.uni-freiburg.de/freiburg_groceries_dataset/](http://aisdatasets.informatik.uni-freiburg.de/freiburg_groceries_dataset/)","description_withheld":null,"homepage":"http://aisdatasets.informatik.uni-freiburg.de/freiburg_groceries_dataset/","introduced_date":"2016-01-01","introduced_date_note":null,"introduced_by":{"paper":"/paper/the-freiburg-groceries-dataset","title":"The Freiburg Groceries Dataset","first_author":"Philipp Jund","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Object Detection","url":"/task/object-detection","datasets_with_task":"/datasets/task/object-detection"},{"name":"Neural Architecture Search","url":"/task/architecture-search","datasets_with_task":"/datasets/task/architecture-search"},{"name":"Object Recognition","url":"/task/object-recognition","datasets_with_task":"/datasets/task/object-recognition"}],"languages":[],"variants":["Freiburg Groceries"],"data_loaders":[],"num_papers_in_archive":7,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}