{"url":"/dataset/animals-10","name":"Animals-10","full_name":null,"description_markdown":"It contains about 28K medium quality animal images belonging to 10 categories: dog, cat, horse, spyder, butterfly, chicken, sheep, cow, squirrel, and elephant.\r\n\r\nAll the images have been collected from \"google images\" and have been checked by humans. There is some erroneous data to simulate real conditions (eg. images taken by users of your app).\r\nThe main directory is divided into folders, one for each category. The image count for each category varies from 2K to 5 K units.","description_withheld":null,"homepage":"","introduced_date":"2022-04-03","introduced_date_note":null,"introduced_by":{"paper":"/paper/adjusting-for-bias-with-procedural-data","title":"Adjusting for Bias with Procedural Data","first_author":"Shesh Narayan Gupta","url":null},"license":{"name":"https://www.kaggle.com/datasets/alessiocorrado99/animals10","url":"https://www.kaggle.com/datasets/alessiocorrado99/animals10"},"modalities":[],"tasks":[{"name":"Image Classification","url":"/task/image-classification","datasets_with_task":"/datasets/task/image-classification"},{"name":"Representation Learning","url":"/task/representation-learning","datasets_with_task":"/datasets/task/representation-learning"},{"name":"Multi-Animal Tracking with identification","url":"/task/multi-animal-tracking-with-identification","datasets_with_task":"/datasets/task/multi-animal-tracking-with-identification"}],"languages":[],"variants":["Animals-10"],"data_loaders":[],"num_papers_in_archive":3,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/representation-learning-on-animals-10","task":"Representation Learning","dataset_variant":"Animals-10","rows":1,"metrics":["1:1 Accuracy"],"first_row_in_archive_order":{"model":"top_model_weights_with_3d_2","paper":"/paper/adjusting-for-bias-with-procedural-data","metrics":{"1:1 Accuracy":"0.745896"},"code_links":[{"title":"aiskunks/ai_research","url":"https://github.com/aiskunks/ai_research"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/adjusting-for-bias-with-procedural-data","title":"Adjusting for Bias with Procedural Data","date":"2022-04-03","rows_on_this_dataset":1,"code_links":1,"syntology":null}],"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."}