datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
OpenFake
Dataset Card for OpenFake
OpenFake is a dataset and benchmark for detecting AI-generated images, with a focus on politically and socially salient content where misinformation risk is highest. It pairs real photographs with synthetic counterparts produced by a wide range of frontier proprietary generators, open-source diffusion models, and community fine-tunes. A separate in-the-wild test set is sourced from Reddit to evaluate detector performance on naturally circulated… See the full description on the dataset page: https://huggingface.co/datasets/ComplexDataLab/OpenFake.OpenSDI_trainThis repository contains the OpenSDI training dataset, presented in the paper OpenSDI: Spotting Diffusion-Generated Images in the Open World.
Code: https://github.com/iamwangyabin/OpenSDI
OpenSDI_test
OpenSDI: Spotting Diffusion-Generated Images in the Open World
This dataset is designed to address the OpenSDI challenge: spotting diffusion-generated images in realistic, open-world scenarios. It is described in the paper:
Project Page: https://iamwangyabin.github.io/OpenSDI/
OpenSDID Dataset Highlights:
User Diversity: Simulates a wide range of user intentions and creative styles using diverse text prompts generated by VLMs.
Model Innovation: Includes images from multiple… See the full description on the dataset page: https://huggingface.co/datasets/nebula/OpenSDI_test.Open-Pixel-1T
🌌 Open-Pixel-1T (Visual Atlas)
A Large-Scale, High-Entropy Synthetic Image Dataset for Foundational Pre-Training
📑 Dataset Summary
Open-Pixel-1T is a monumental open-source initiative designed to create a "Visual Atlas" of stochastic imagery. Unlike traditional datasets scraped from social media which contain inherent human bias, Open-Pixel-1T is constructed using high-entropy random seeds to generate unique, diverse visual signals.
This dataset… See the full description on the dataset page: https://huggingface.co/datasets/LAYEK-143/Open-Pixel-1T.openbrush
OpenBrush-75K
A curated dataset of 75,313 public domain artworks with rich, structured VLM-generated captions designed for training image generation models, fine-tuning vision-language models, and art analysis research.
Dataset Description
OpenBrush-75K contains high-quality reproductions of paintings from the Western art canon, spanning from the Renaissance to the early 20th century. Each image is paired with a detailed structured caption generated by a… See the full description on the dataset page: https://huggingface.co/datasets/jaddai/openbrush.closed-open-eyes
👀 Open and Closed Eyes Dataset
Welcome to the Open and Closed Eyes Dataset! This dataset is designed to help researchers and developers in computer vision and machine learning tasks, particularly in recognizing and distinguishing between open and closed eyes in various contexts. Below, you'll find a detailed description of the dataset structure, categories, and how to interpret the data. 🌟
📁 Dataset Structure
The dataset is stored in Parquet files, ensuring efficient… See the full description on the dataset page: https://huggingface.co/datasets/MichalMlodawski/closed-open-eyes.OpenGameArt-CC0
Dataset Card for OpenGameArt-CC0
Dataset Summary
This dataset contains game artwork assets collected from OpenGameArt.org that are specifically released under the Creative Commons 0 (CC0) license, making them effectively public domain works. The dataset includes various types of game assets such as 2D art, 3D art, concept art, music, sound effects, textures, and documents along with their associated metadata.
Languages
The dataset is primarily monolingual:… See the full description on the dataset page: https://huggingface.co/datasets/nyuuzyou/OpenGameArt-CC0.open-vision-banana-snvc-train-full
SNVC-50M v5_full — Multi-Task Vision Dataset
Description
This dataset is a curated subset of the SenseNova Vision Corpus 50M (SNVC-50M), containing 43,509 samples across 6 vision task families and 31 source datasets. Each sample follows a conversational format with interleaved <image> tokens, designed for training vision-language models (VLMs).
Coverage: 43,509 / 57,878 (75.2%) of the original sampling plan. 23 datasets at 100%, 8 partial, 12 unrecoverable… See the full description on the dataset page: https://huggingface.co/datasets/gatilin/open-vision-banana-snvc-train-full.pexels-photos-janpf
Images:
There are approximately 130K images, borrowed from pexels.com.
Thanks to those folks for curating a wonderful resource.
There are millions more images on pexels. These particular ones were selected by
the list of urls at https://github.com/janpf/self-supervised-multi-task-aesthetic-pretraining/blob/main/dataset/urls.txt .
The filenames are based on the md5 hash of each image.
Download From here or from pexels.com: You choose
For those people who like… See the full description on the dataset page: https://huggingface.co/datasets/opendiffusionai/pexels-photos-janpf.t2i_safety_dataset
T2ISafety: Benchmark for Assessing Fairness, Toxicity, and Privacy in Image Generation
This dataset, T2ISafety, is a comprehensive safety benchmark designed to evaluate Text-to-Image (T2I) models across three key domains: toxicity, fairness, and bias. It provides a detailed hierarchy of 12 tasks and 44 categories, built from meticulously collected 70K prompts. Based on this taxonomy and prompt set, T2ISafety includes 68K manually annotated images, serving as a robust resource for… See the full description on the dataset page: https://huggingface.co/datasets/OpenSafetyLab/t2i_safety_dataset.openclipart
Dataset Card for OpenClipart.org SVG Images
Dataset Summary
This dataset contains 178,604 public domain SVG vector clipart images collected from OpenClipart.org. OpenClipart.org is a community-driven platform where artists share vector clip art explicitly released into the public domain (CC0). The dataset includes the SVG content along with comprehensive metadata such as titles, descriptions, artist names, creation dates, tags, and image URLs. The SVG files in this… See the full description on the dataset page: https://huggingface.co/datasets/nyuuzyou/openclipart.amfitrite-open-waters-hab-sentinel2
Dataset Card for Amfitrite-Open-Waters-HAB-Sentinel2
This dataset contains multispectral Sentinel-2 satellite imagery tiles focused on open water and coastal marine environments, classified by the potential presence of Harmful Algal Blooms (HABs).
It is designed to train Machine or Deep Learning models (like CNNs) for large-scale environmental monitoring and ocean anomaly detection.
Dataset Details
Dataset Description
Amfitrite-Open-Waters-HAB-Sentinel2 is a… See the full description on the dataset page: https://huggingface.co/datasets/kostaspic/amfitrite-open-waters-hab-sentinel2.OpenAI-4o_t2i_human_preference
Rapidata OpenAI 4o Preference
This T2I dataset contains over 200'000 human responses from over ~45,000 individual annotators, collected in less than half a day using the Rapidata Python API, accessible to anyone and ideal for large scale evaluation.
Evaluating OpenAI 4o (version from 26.3.2025) across three categories: preference, coherence, and alignment.
Explore our latest model rankings on our website.
If you get value from this dataset and would like to see more in the… See the full description on the dataset page: https://huggingface.co/datasets/Rapidata/OpenAI-4o_t2i_human_preference.OpenGVLab_Lumina_t2i_human_preference
Rapidata Lumina Preference
This T2I dataset contains over 400k human responses from over 86k individual annotators, collected in just ~2 Days using the Rapidata Python API, accessible to anyone and ideal for large scale evaluation.
Evaluating Lumina across three categories: preference, coherence, and alignment.
Explore our latest model rankings on our website.
If you get value from this dataset and would like to see more in the future, please consider liking it.… See the full description on the dataset page: https://huggingface.co/datasets/Rapidata/OpenGVLab_Lumina_t2i_human_preference.OpenSDIDplus
OpenSDID+
OpenSDID+ is an extended release of the OpenSDI dataset. It complements the original SD1.5 training split with large-scale images from the remaining OpenSDI generators: SD2, SD3, SDXL, and FLUX.
The dataset follows the OpenSDI challenge introduced in "OpenSDI: Spotting Diffusion-Generated Images in the Open World". OpenSDI studies detection and localization of diffusion-generated images under realistic open-world settings, including diverse user intentions, evolving… See the full description on the dataset page: https://huggingface.co/datasets/nebula/OpenSDIDplus.imet-open-access
iMet Open Access
A multi-label image classification dataset of 259,559 artworks and objects from The Metropolitan Museum of Art,
built from the Met's official CC0 Open Access release (metmuseum/openaccess).
It follows the spirit of the Kaggle iMet Collection challenges (FGVC6 2019 / FGVC7 2020): long-tail, fine-grained attribute
recognition from museum photography, with subject tags, culture, medium (material / technique) and country labels.
This is not the Kaggle iMet data.… See the full description on the dataset page: https://huggingface.co/datasets/timm/imet-open-access.OpenTME
OpenTME: Open-Access Tumor Microenvironment Profiles from TCGA
OpenTME is an open-access project by Aignostics for academic researchers. It provides comprehensive spatial outputs for whole slide images (WSIs) of H&E-stained, formalin-fixed, paraffin-embedded slides from The Cancer Genome Atlas (TCGA). OpenTME is powered by Atlas H&E-TME – a computational pathology application developed by Aignostics.
Atlas H&E-TME
Atlas H&E-TME is a foundation model-based… See the full description on the dataset page: https://huggingface.co/datasets/Aignostics/OpenTME.openbrush-baroque
OpenBrush Baroque
Baroque works from OpenBrush-75K (~1600–1750) — chiaroscuro, religious painting, dramatic light.
Curated subset of jaddai/openbrush. Same CC0 license, same caption schema, same VLM (Qwen3-VL-30B-A3B). This subset exists so you don't have to download 75,313 images to get to the 4,240 you actually want.
Why this subset
The canonical Baroque visual language — Caravaggio, Rembrandt, Vermeer, Velázquez, Rubens. Useful for models learning dramatic… See the full description on the dataset page: https://huggingface.co/datasets/jaddai/openbrush-baroque.openbrush-impressionism
OpenBrush Impressionism
Every Impressionist work from OpenBrush-75K — the largest movement subset.
Curated subset of jaddai/openbrush. Same CC0 license, same caption schema, same VLM (Qwen3-VL-30B-A3B). This subset exists so you don't have to download 75,313 images to get to the 12,798 you actually want.
Why this subset
Broad-coverage subset for training on the Impressionist visual language: broken brushwork, light-on-color theory, plein-air staging, atmospheric… See the full description on the dataset page: https://huggingface.co/datasets/jaddai/openbrush-impressionism.openbrush-75k
OpenBrush-75K
A curated dataset of 75,313 public domain artworks with rich, structured VLM-generated captions designed for training image generation models, fine-tuning vision-language models, and art analysis research.
Dataset Description
OpenBrush-75K contains high-quality reproductions of paintings from the Western art canon, spanning from the Renaissance to the early 20th century. Each image is paired with a detailed structured caption generated by a vision-language… See the full description on the dataset page: https://huggingface.co/datasets/Trever896/openbrush-75k.cc12m-cleaned
CC12m-cleaned
This dataset builds on two others: The Conceptual Captions 12million dataset, which lead to the LLaVa captioned subset done by
CaptionEmporium
(The latter is the same set, but swaps out the (Conceptual Captions 12million) often-useless alt-text captioning for decent ones_
I have then used the llava captions as a base, and used the detailed descrptions to filter out
images with things like watermarks, artist signatures, etc.
I have also manually thrown out all… See the full description on the dataset page: https://huggingface.co/datasets/opendiffusionai/cc12m-cleaned.openbrush-landscapes
OpenBrush Landscapes
Every landscape painting from OpenBrush-75K — across all artists, movements, and centuries. Largest single-genre subset.
Curated subset of jaddai/openbrush. Same CC0 license, same caption schema, same VLM (Qwen3-VL-30B-A3B). This subset exists so you don't have to download 75,313 images to get to the 12,612 you actually want.
Why this subset
Every landscape across the parent dataset's full range — Romantic wildernesses, Impressionist… See the full description on the dataset page: https://huggingface.co/datasets/jaddai/openbrush-landscapes.SNAP25_ESM2_OpenFold3_Structural_Analysis
🧬 SNAP25 OpenFold3 Structural Analysis Dataset
Comprehensive structural predictions and therapeutic discovery data for 677 SNAP25 missense variants
🎯 Overview
This dataset provides the first comprehensive structural analysis of SNAP25 (Synaptosomal-Associated Protein 25 kDa) missense variants, generated to support therapeutic discovery for SNAP25-related developmental and epileptic encephalopathy (DEE-SNAP25).
SNAP25 is a critical component of the neuronal… See the full description on the dataset page: https://huggingface.co/datasets/SkyWhal3/SNAP25_ESM2_OpenFold3_Structural_Analysis.OpenJev-Vision-Research-v0.1
OpenJev Vision Research v0.1
12,832 image records, with public provenance, original synthetic scenes,
and programmatically derived decision questions.
This is an experimental research dataset for visual posterior learning and
compositional decisions, released with OpenJev.
It is not a reproduction of TypeSafe's proprietary Jev model or training method.
Three separate configurations
Config
Images
What the labels mean
License
synthetic
8,192
Exact… See the full description on the dataset page: https://huggingface.co/datasets/IamBusy/OpenJev-Vision-Research-v0.1.nationalmuseet-open-images
Nationalmuseet Open Images
This dataset is an independently harvested research dataset from Nationalmuseet Samlinger Online.
It contains metadata and optionally WebDataset image shards for Nationalmuseet asset records whose
rights.license is one of:
Public Domain
CC-BY
No known rights
Public Domain and CC-BY are the strict open-license subset. No known rights is kept as a
separate license bucket because Nationalmuseet says this label means that, to their best assessment,
the… See the full description on the dataset page: https://huggingface.co/datasets/V4ldeLund/nationalmuseet-open-images.closed-open-eyes
👀 Open and Closed Eyes Dataset
Welcome to the Open and Closed Eyes Dataset! This dataset is designed to help researchers and developers in computer vision and machine learning tasks, particularly in recognizing and distinguishing between open and closed eyes in various contexts. Below, you'll find a detailed description of the dataset structure, categories, and how to interpret the data. 🌟
📁 Dataset Structure
The dataset is stored in Parquet files, ensuring efficient… See the full description on the dataset page: https://huggingface.co/datasets/VasilyLoginov/closed-open-eyes.OpenGameArt-CC-BY-3.0
Dataset Card for OpenGameArt-CC-BY-3.0
Dataset Summary
This dataset contains game artwork assets collected from OpenGameArt.org that are specifically released under the Creative Commons Attribution 3.0 (CC-BY-3.0) license. The dataset includes various types of game assets such as 2D art, 3D art, concept art, music, sound effects, textures, and documents along with their associated metadata.
Languages
The dataset is primarily monolingual:
English (en): All… See the full description on the dataset page: https://huggingface.co/datasets/nyuuzyou/OpenGameArt-CC-BY-3.0.OpenGameArt-CC-BY-SA-3.0
Dataset Card for OpenGameArt-CC-BY-SA-3.0
Dataset Summary
This dataset contains game artwork assets collected from OpenGameArt.org that are specifically released under the Creative Commons Attribution-ShareAlike 3.0 Unported (CC-BY-SA-3.0) license. The dataset includes various types of game assets such as 2D art, 3D art, concept art, music, sound effects, textures, and documents along with their associated metadata.
Languages
The dataset is primarily… See the full description on the dataset page: https://huggingface.co/datasets/nyuuzyou/OpenGameArt-CC-BY-SA-3.0.OpenGameArt-OGA-BY-3.0
Dataset Card for OpenGameArt-OGA-BY-3.0
Dataset Summary
This dataset contains game artwork assets collected from OpenGameArt.org that are specifically released under the OpenGameArt Attribution (OGA-BY-3.0) license. The dataset includes various types of game assets such as 2D art, 3D art, concept art, music, sound effects, textures, and associated metadata.
Languages
The dataset is primarily monolingual:
English (en): All asset descriptions and metadata are in… See the full description on the dataset page: https://huggingface.co/datasets/nyuuzyou/OpenGameArt-OGA-BY-3.0.openbrush-impressionist-landscapes
OpenBrush Impressionist Landscapes
Cross-cut subset: Impressionist landscape paintings from OpenBrush-75K. The most-targeted style+genre combination for Impressionist landscape LoRA training.
Curated subset of jaddai/openbrush. Same CC0 license, same caption schema, same VLM (Qwen3-VL-30B-A3B). This subset exists so you don't have to download 75,313 images to get to the 4,308 you actually want.
Why this subset
The intersection of the largest movement… See the full description on the dataset page: https://huggingface.co/datasets/jaddai/openbrush-impressionist-landscapes.