{
 "id": "deepghs/nsfw_detect",
 "owner": "deepghs",
 "name": "nsfw_detect",
 "downloads": 482,
 "likes": 89,
 "last_modified": "2025-11-17T18:26:47.000Z",
 "stated_licence": "mit",
 "stated_from": "tag",
 "licence_name": null,
 "licence_link": null,
 "file_licence": null,
 "licence_files": [],
 "sources": [],
 "gated": "auto",
 "tasks": [
  "image-classification"
 ],
 "citation": "@misc{nsfw_detect_dataset,\n  title        = {NSFW Detection Dataset},\n  author       = {deepghs},\n  howpublished = {\\url{https://huggingface.co/datasets/deepghs/nsfw_detect}},\n  year         = {2023},\n  note         = {Multi-class image classification dataset for NSFW content detection with five categories: drawing, hentai, neutral, porn, and sexy},\n  abstract     = {This dataset is specifically designed for training NSFW (Not Safe For Work) detection models in the context of artistic content and image classification. The collection follows the established categorization format from popular NSFW detection implementations, providing a comprehensive benchmark for content moderation systems. The dataset contains images organized into five distinct classes that represent different levels of appropriateness and content types commonly encountered in online platforms. The classification framework divides images into drawing, hentai, neutral, porn, and sexy categories, enabling models to distinguish between various types of potentially sensitive content with fine-grained precision.},\n  keywords     = {NSFW detection, image classification, content moderation, artistic content, multi-class categorization}\n}",
 "signal": "permissive",
 "reason": "The declared licence (mit) is classified as permissive.",
 "revision": "ac763cb1e1557225168be3b6b6b1ee864c17bc36",
 "stated_evidence": "https://huggingface.co/datasets/deepghs/nsfw_detect/blob/ac763cb1e1557225168be3b6b6b1ee864c17bc36/README.md",
 "file_evidence": "https://huggingface.co/datasets/deepghs/nsfw_detect/tree/ac763cb1e1557225168be3b6b6b1ee864c17bc36",
 "card_nc": false
}