{"url":"/dataset/household-waste-dataset","name":"Household Waste Dataset","full_name":null,"description_markdown":"Collection of images of garbages grouped into 10 classes (metal, glass, biological, paper, battery, trash, cardboard, shoes, clothes, and plastic). The number of files in respective classes is as follows: \r\n\r\n- **Metal**: 1869\r\n- **Glass**: 4097\r\n- **Biological**: 985\r\n- **Paper**: 2727\r\n- **Battery**: 945\r\n- **Trash**: 834\r\n- **Cardboard**: 2341\r\n- **Shoes**: 1977\r\n- **Clothes**: 5325\r\n- **Plastic**: 2542\r\n\r\nVisualization of the distribution of classes.","description_withheld":null,"homepage":"","introduced_date":"2024-01-27","introduced_date_note":null,"introduced_by":{"paper":"/paper/managing-household-waste-through-transfer","title":"Managing Household Waste through Transfer Learning","first_author":"Suman Kunwar","url":null},"license":{"name":"MIT","url":"https://www.kaggle.com/datasets/sumn2u/garbage-classification-v2/"},"modalities":[],"tasks":[],"languages":[],"variants":["Household Waste Dataset"],"data_loaders":[{"repo":"https://github.com/ultralytics/ultralytics","url":"https://github.com/ultralytics/ultralytics","frameworks":["pytorch"]}],"num_papers_in_archive":1,"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."}