datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
cifar10
Dataset Card for CIFAR-10
Dataset Summary
The CIFAR-10 dataset consists of 60000 32x32 colour images in 10 classes, with 6000 images per class. There are 50000 training images and 10000 test images.
The dataset is divided into five training batches and one test batch, each with 10000 images. The test batch contains exactly 1000 randomly-selected images from each class. The training batches contain the remaining images in random order, but some training batches may contain… See the full description on the dataset page: https://huggingface.co/datasets/uoft-cs/cifar10.CT-RATE
The CT-RATE Team organizes the VLM3D Challenge
VLM3D 2026 (2nd Edition) → Challenge Finals at MICCAI 2026
VLM3D 2025 (1st Edition) → Challenge Finals at MICCAI 2025 • Workshop at ICCV 2025
The CT-RATE Team is developing the MR-RATE Dataset
A large-scale brain MRI dataset with paired radiology reports for training 3D vision-language models.
GitHub |
Dataset |
Metadata Dashboard
Generalist Foundation Models from a Multimodal Dataset for 3D Computed Tomography… See the full description on the dataset page: https://huggingface.co/datasets/ibrahimhamamci/CT-RATE.typed_digital_signatures
Typed Digital Signatures Dataset
This comprehensive dataset contains synthetic digital signatures rendered across 30 different Google Fonts, specifically selected for their handwriting and signature-style characteristics. Each font contributes unique stylistic elements, making this dataset ideal for robust signature analysis and font recognition tasks.
Dataset Overview
Total Fonts: 30 different Google Fonts
Images per Font: 3,000 signatures
Total Dataset Size:… See the full description on the dataset page: https://huggingface.co/datasets/Benjy/typed_digital_signatures.imagenet-1k
Dataset Card for ImageNet
Dataset Summary
ILSVRC 2012, commonly known as 'ImageNet' is an image dataset organized according to the WordNet hierarchy. Each meaningful concept in WordNet, possibly described by multiple words or word phrases, is called a "synonym set" or "synset". There are more than 100,000 synsets in WordNet, majority of them are nouns (80,000+). ImageNet aims to provide on average 1000 images to illustrate each synset. Images of each concept are… See the full description on the dataset page: https://huggingface.co/datasets/ILSVRC/imagenet-1k.DASP
Dataset Card for DASP
Dataset Description
The DASP (Distributed Analysis of Sentinel-2 Pixels) dataset consists of cloud-free satellite images captured by Sentinel-2 satellites. Each image represents the most recent, non-partial, and cloudless capture from over 30 million Sentinel-2 images in every band. The dataset provides a near-complete cloudless view of Earth's surface, ideal for various geospatial applications. Images were converted from JPEG2000 to JPEG-XL to… See the full description on the dataset page: https://huggingface.co/datasets/RichardErkhov/DASP.mnist
Dataset Card for MNIST
Dataset Summary
The MNIST dataset consists of 70,000 28x28 black-and-white images of handwritten digits extracted from two NIST databases. There are 60,000 images in the training dataset and 10,000 images in the validation dataset, one class per digit so a total of 10 classes, with 7,000 images (6,000 train images and 1,000 test images) per class.
Half of the image were drawn by Census Bureau employees and the other half by high school students… See the full description on the dataset page: https://huggingface.co/datasets/ylecun/mnist.small
TempoFunk Small
7.8k samples of metadata and encoded latents & prompts of random videos.
Data format
Video frame latents
Numpy arrays
120 frames, 512x512 source size
Encoded shape (120, 4, 64, 64)
CLIP (openai) encoded prompts
Video description (as seen in metadata)
Encoded shape (77,768)
Video metadata as JSON (description, tags, categories, source URL, etc.)
MR-RATE-atlas
MR-RATE: A Vision-Language Foundation Model and Dataset for Magnetic Resonance Imaging
This is the MR-RATE-atlas repository, part of the MR-RATE dataset release. It contains atlas-registered MRI volumes in which all imaging sequences within each study have been spatially normalized to a standard atlas-space. For full dataset details, native-space MRI volumes, radiology reports, metadata, and data splits, please refer to… See the full description on the dataset page: https://huggingface.co/datasets/Forithmus/MR-RATE-atlas.hest
Model Card for HEST-1k
What is HEST-1k?
A collection of 1,276 spatial transcriptomic profiles, each linked and aligned to a Whole Slide Image (with pixel size < 1.15 µm/px) and metadata.
HEST-1k was assembled from 180 public and internal cohorts encompassing:
26 organs
2 species (Homo Sapiens and Mus Musculus)
398 cancer samples from 25 cancer types.
HEST-1k processing enabled the identification of >1.5 million expression/morphology pairs and >76 million nuclei… See the full description on the dataset page: https://huggingface.co/datasets/MahmoodLab/hest.cifar100
Dataset Card for CIFAR-100
Dataset Summary
The CIFAR-100 dataset consists of 60000 32x32 colour images in 100 classes, with 600 images
per class. There are 500 training images and 100 testing images per class. There are 50000 training images and 10000 test images. The 100 classes are grouped into 20 superclasses.
There are two labels per image - fine label (actual class) and coarse label (superclass).
Supported Tasks and Leaderboards
image-classification: The… See the full description on the dataset page: https://huggingface.co/datasets/uoft-cs/cifar100.food101
Dataset Card for Food-101
Dataset Summary
This dataset consists of 101 food categories, with 101'000 images. For each class, 250 manually reviewed test images are provided as well as 750 training images. On purpose, the training images were not cleaned, and thus still contain some amount of noise. This comes mostly in the form of intense colors and sometimes wrong labels. All images were rescaled to have a maximum side length of 512 pixels.
Supported Tasks and… See the full description on the dataset page: https://huggingface.co/datasets/ethz/food101.cholect50
CholecT50 Dataset (FiftyOne Format)
This is a FiftyOne dataset version of the CholecT50 dataset.
CholecT50 is a dataset of laparoscopic cholecystectomy surgeries, annotated with surgical action triplets. It is the first public dataset to provide action triplet annotations for surgical videos, enabling research in fine-grained surgical activity recognition.
Dataset Summary
CholecT50 consists of 50 videos of laparoscopic cholecystectomy surgeries. Each frame is annotated… See the full description on the dataset page: https://huggingface.co/datasets/Voxel51/cholect50.RSCD-1million
RSCD: Road Surface Condition Dataset
Dataset Description
The Road Surface Condition Dataset (RSCD) is a large-scale image dataset containing over 1 million images for road surface condition classification. This dataset is designed for training computer vision models to identify and classify various road surface types, moisture conditions, and damage severity levels.
Dataset Summary
Total Images: ~1,028,000 images
Image Format: JPG
Use Cases:
Road condition… See the full description on the dataset page: https://huggingface.co/datasets/rezzzq/RSCD-1million.PhysicalAI-SimReady-Warehouse-01
NVIDIA Physical AI SimReady Warehouse OpenUSD Dataset
Dataset Version: 1.1.0
Date: May 18, 2025
Author: NVIDIA, Corporation
License: CC-BY-4.0 (Creative Commons Attribution 4.0 International)
Contents
This dataset includes the following:
This README file
A CSV catalog that enumerates all of the OpenUSD assets that are part of this dataset including a sub-folder of images that showcase each 3D asset (physical_ai_simready_warehouse_01.csv). The CSV file is organized in… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/PhysicalAI-SimReady-Warehouse-01.tempofunk-sdance
TempoFunk S(mall)Dance
10k samples of metadata and encoded latents & prompts of videos themed around dance.
Data format
Video frame latents
Numpy arrays
120 frames, 512x512 source size
Encoded shape (120, 4, 64, 64)
CLIP (openai) encoded prompts
Video description (as seen in metadata)
Encoded shape (77,768)
Video metadata as JSON (description, tags, categories, source URLs, etc.)
MR-RATE
MR-RATE: A Vision-Language Foundation Model and Dataset for Magnetic Resonance Imaging
Welcome to the official page for MR-RATE, a pioneering vision-language model and 3D medical imaging dataset that pairs textual reports with brain and spine MRI volumes. Following the approach of CT-RATE, the first 3D medical imaging dataset to pair images with textual reports, MR-RATE offers brain and spine MRI volumes matched with… See the full description on the dataset page: https://huggingface.co/datasets/Forithmus/MR-RATE.GAMMA
GAMMA — Glaucoma grading from Multi-Modality imAges (Challenge dataset)
Image: Dataset Samples.
Short description
GAMMA is the first public multi-modality glaucoma grading dataset that pairs 2D color fundus photographs with 3D OCT volumes for each sample. It was released as part of the GAMMA challenge (OMIA8 / MICCAI 2021) to encourage algorithms that combine fundus and OCT information for automatic… See the full description on the dataset page: https://huggingface.co/datasets/ctmedtech/GAMMA.TreasureEnglish | 中文
News
Our work has been accepted by ICML 2026 as a poster. 🎉🎉
The paper has released on ArXiv.
The code has released on Github.
Treasure Dataset
Treasure is the dataset companion to Fleet (Fleet: Few Shots Lead Effective AI-generated Images Detection), designed for AI-generated image detection in an open-world setting where generators evolve and distribution shift is central. Unlike saturated results on closed datasets, Treasure/Fleet emphasizes… See the full description on the dataset page: https://huggingface.co/datasets/ThreeLiu/Treasure.Dataset
MM-OphBench: Multi-Center Multimodal Clinical Ophthalmic Benchmark Dataset
A Large-Scale, Standardized Multi-Center Benchmark Covering 7 Imaging Modalities & 4.3M+ Clinical Records
1. Executive Summary & Repository Overview
The MM-OphBench repository hosts a petabyte-scale, clinically harmonized ophthalmic image archive compiled from leading ophthalmic hospitals and benchmark cohorts. It spans 4,307,415 high-resolution diagnostic images and multimodal… See the full description on the dataset page: https://huggingface.co/datasets/Kaphathy/Dataset.text-to-image-promptsIf you have questions about this dataset , feel free to ask them on the fusion-discord : https://discord.gg/8TVHPf6Edn
This collection contains sets from the fusion-t2i-ai-generator on perchance.
This datset is used in this notebook: https://huggingface.co/datasets/codeShare/text-to-image-prompts/tree/main/Google%20Colab%20Notebooks
To see the full sets, please use the url "https://perchance.org/" + url
, where the urls are listed below:
_generator
gen_e621
fusion-t2i-e621-tags-1… See the full description on the dataset page: https://huggingface.co/datasets/codeShare/text-to-image-prompts.PASTIS-HD
🌱 PASTIS-HD 🌿 Panoptic Agricultural Satellite TIme Series : optical time series, radar time series and very high resolution image
PASTIS is a benchmark dataset for panoptic and semantic segmentation of agricultural parcels from satellite time series.
It contains 2,433 patches within the French metropolitan territory with panoptic annotations (instance index + semantic label for each pixel).
Each patch is a Sentinel-2 multispectral image time series of variable lentgh.
This… See the full description on the dataset page: https://huggingface.co/datasets/IGNF/PASTIS-HD.tiny-imagenet
Dataset Card for tiny-imagenet
Dataset Summary
Tiny ImageNet contains 100000 images of 200 classes (500 for each class) downsized to 64×64 colored images. Each class has 500 training images, 50 validation images, and 50 test images.
Languages
The class labels in the dataset are in English.
Dataset Structure
Data Instances
{
'image': <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=64x64 at 0x1A800E8E190,
'label': 15
}… See the full description on the dataset page: https://huggingface.co/datasets/zh-plus/tiny-imagenet.OpenFake
Dataset Card for OpenFake
Known issues
Prompt–image misalignment in the synthetic split (reported November 2025, fix pending)
For five of the eighty generators, the prompt field attached to synthetic
images does not correspond to the prompt actually used to generate that image.
Affected generators:
flux-realism
sd-3.5
sdxl-realvis-v5
sd-1.5-dreamshaper
sd-1.5-epicdream
This affects approximately 19.77% of synthetic images. It was first reported in
discussion… See the full description on the dataset page: https://huggingface.co/datasets/ComplexDataLab/OpenFake.stanford_cars
Stanford Cars Dataset
Dataset Overview
Splits:
Training: 8144 images used for model training.
Test: 8041 images used for evaluation.
Contrast: 8041 images with high contrast for robustness testing.
Gaussian Noise: 8041 images corrupted by Gaussian noise for robustness testing.
Impulse Noise: 8041 images corrupted by impulse noise for robustness testing.
JPEG Compression: 8041 compressed images for robustness testing.
Motion Blur: 8041 images with motion blur for… See the full description on the dataset page: https://huggingface.co/datasets/tanganke/stanford_cars.TreeOfLife-200M
Dataset Card for TreeOfLife-200M
If you are looking for the original release TreeOfLife-200M dataset, as used in training BioCLIP 2 and presented the paper, please see Revision a8f38b4. The dataset, as presented here, was used to train BioCLIP 2.5 Huge; it completes the dataset cleaning process and resolves an issue where Observation.org occurrences were not included in the training data.
With 233 million images representing 933,798 taxa across the tree of life, TreeOfLife-200M… See the full description on the dataset page: https://huggingface.co/datasets/imageomics/TreeOfLife-200M.TreeOfLife-10M-WEBP
Dataset Card for TreeOfLife-10M-WEBP
Dataset Description
This is an optimized version of the TreeOfLife-10M dataset,
containing over 10 million images covering 454 thousand taxa in the tree of life.
This version has been processed to improve usability and reduce storage requirements while maintaining full compatibility with the original dataset structure.
Dataset Summary
This version modifies the original dataset as follows:
Corrupted files were… See the full description on the dataset page: https://huggingface.co/datasets/birder-project/TreeOfLife-10M-WEBP.fish-vista
Dataset Card for Fish-Visual Trait Analysis (Fish-Vista)
Note that the '</Use this dataset>' option will only load the CSV files. To download the entire dataset, including all processed images and segmentation annotations, refer to Instructions for downloading dataset and images.
See Example Code to Use the Segmentation Dataset
Figure 1. A schematic representation of the different tasks in Fish-Vista Dataset.
Instructions for downloading dataset… See the full description on the dataset page: https://huggingface.co/datasets/imageomics/fish-vista.game_character_skins
Game Character Skins Dataset
Summary
This comprehensive dataset contains game character skins and artwork from multiple popular mobile and PC games, providing a rich collection of character visual assets for computer vision research and game development applications. The dataset spans eight major game titles including Arknights, Azur Lane, Blue Archive, Fate/Grand Order, Genshin Impact, Girls' Frontline, Neural Cloud, Nikke, Path to Nowhere, and Honkai: Star Rail… See the full description on the dataset page: https://huggingface.co/datasets/deepghs/game_character_skins.svhn
Dataset Card for Street View House Numbers
Dataset Summary
SVHN is a real-world image dataset for developing machine learning and object recognition algorithms with minimal requirement on data preprocessing and formatting. It can be seen as similar in flavor to MNIST (e.g., the images are of small cropped digits), but incorporates an order of magnitude more labeled data (over 600,000 digit images) and comes from a significantly harder, unsolved, real world problem… See the full description on the dataset page: https://huggingface.co/datasets/ufldl-stanford/svhn.imagenet1k-256-wdsThis is imagenet1k in webdataset format. Images are stored as jpg files. Every image has been resized to a maximum side length of 256. That means that if an image in the original dataset was 1000 by 500, the new size will be 256 by 128. Images with a maximum side length of under 256 were not resized.
The total size of all dataset files is 57.8 GB, there are 1,281,167 rows in the training split and 50,000 rows in the validation split.