{"url":"/dataset/nhr-edit","name":"NHR-Edit","full_name":"NoHumansRequired Edit Dataset","description_markdown":"NHR-Edit is a training dataset for instruction-based image editing. Each sample consists of an input image, a natural language editing instruction, and the corresponding edited image. All samples are generated fully automatically using the NoHumanRequired pipeline, without any human annotation or filtering.\r\n\r\nThis dataset is designed to support training of general-purpose image editing models that can follow diverse, natural editing commands. Each sample also includes additional metadata such as editing type, style, and image resolution, making it suitable for training fine-grained, controllable image editing models.","description_withheld":null,"homepage":"https://riko0.github.io/No-Humans-Required/","introduced_date":"2025-07-18","introduced_date_note":null,"introduced_by":{"paper":"/paper/nohumansrequired-autonomous-high-quality","title":"NoHumansRequired: Autonomous High-Quality Image Editing Triplet Mining","first_author":"Maksim Kuprashevich","url":null},"license":{"name":"Apache 2.0","url":null},"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[{"name":"Text-based Image Editing","url":"/task/text-based-image-editing","datasets_with_task":"/datasets/task/text-based-image-editing"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["NHR-Edit"],"data_loaders":[],"num_papers_in_archive":0,"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."}