datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
fashion_mnist
Dataset Card for FashionMNIST
Dataset Summary
Fashion-MNIST is a dataset of Zalando's article images—consisting of a training set of 60,000 examples and a test set of 10,000 examples. Each example is a 28x28 grayscale image, associated with a label from 10 classes. We intend Fashion-MNIST to serve as a direct drop-in replacement for the original MNIST dataset for benchmarking machine learning algorithms. It shares the same image size and structure of training and testing… See the full description on the dataset page: https://huggingface.co/datasets/zalando-datasets/fashion_mnist.zendo-synthetic-data
Zendo Synthetic Visual Reasoning Dataset
Synthetic Zendo-style scenes with associated rules and per-scene tensor
representations. Each scene either follows ("positive", label=1) or violates
("negative", label=0) a rule that is given in natural language and as a Prolog
query.
Splits
split
scenes
train
56475
test
3344
rules total
3439
Layout
images/<split>/<batch>/<rule_id>/<scene_id>.png — rendered scene… See the full description on the dataset page: https://huggingface.co/datasets/sophia1ch/zendo-synthetic-data.MPII_Human_Pose_Dataset
Dataset Card for MPII Human Pose
MPII Human Pose dataset is a state of the art benchmark for evaluation of articulated human pose estimation.
The dataset includes around 25K images containing over 40K people with annotated body joints.
The images were systematically collected using an established taxonomy of every day human activities.
Overall the dataset covers 410 human activities and each image is provided with an activity label.
Each image was extracted from a YouTube… See the full description on the dataset page: https://huggingface.co/datasets/Voxel51/MPII_Human_Pose_Dataset.food-dataset
Food Dataset
An image classification dataset of food photos organized into 201 categories (folders), with 35,046 images total (~924 MB).
Each top-level folder is a category (e.g. adana kebab, sushi, waffles, tiramisu, ...) containing JPEG images of that food/dish. This follows the standard Hugging Face imagefolder layout, so it loads directly with:
from datasets import load_dataset
ds = load_dataset("webbrain-one/food-dataset")
Structure
<category… See the full description on the dataset page: https://huggingface.co/datasets/webbrain-one/food-dataset.real-infrared-maritime-vessel-dataset
Real Infrared Maritime Vessel Dataset
Real infrared imagery of maritime vessels.
The dataset is provided in three forms — full-frame detection images, per-object classification crops, and a hand-curated subset.
Classes (7): liner, bulk carrier, warship, sailboat, canoe, container ship, fishing boat.
Layout
real-infrared-maritime-vessel-dataset/
├── original/ Full-frame IR images + XML bounding-box labels (detection)
│ ├── images/{train,test}/*.jpg… See the full description on the dataset page: https://huggingface.co/datasets/hanchong/real-infrared-maritime-vessel-dataset.Describable-Textures-Dataset
Dataset Card for Describable Textures Dataset
This is a FiftyOne dataset with 5640 samples.
Installation
If you haven't already, install FiftyOne:
pip install -U fiftyone
Usage
import fiftyone as fo
import fiftyone.utils.huggingface as fouh
# Load the dataset
# Note: other available arguments include 'max_samples', etc
dataset = fouh.load_from_hub("Voxel51/Describable-Textures-Dataset")
# Launch the App
session = fo.launch_app(dataset)… See the full description on the dataset page: https://huggingface.co/datasets/Voxel51/Describable-Textures-Dataset.military-aircraft-detection-dataset
Military Aircraft Detection Dataset
Military aircraft detection dataset in COCO and YOLO format.
The dataset was initially developed exclusively for military aircraft detection, but was later expanded to include commercial airliners for a broader and more challenging detection task.
The dataset contains 103 military aircraft types and 11 commercial airliner types.
Military aircraft: A10, A400M, AG600, AH64, AKINCI, AV8B, An124, An22, An225, An72, B1, B2, B21, B52, Be200, C1… See the full description on the dataset page: https://huggingface.co/datasets/a2015003713/military-aircraft-detection-dataset.efficientnet-v2-l-adv-dataset
Perturb Adversarial Images
Verified adversarial examples for efficientnet_v2_l (torchvision/EfficientNet_V2_L_Weights.IMAGENET1K_V1), produced by the
Perturb network. Each row is one clean image together with all of its
verified adversarial versions: images that are imperceptibly different from the original
(L∞ ≤ 0.03 in [0,1] pixel scale) yet change the model's top-1 prediction.
This dataset grows continuously. New rows are appended as the network produces them and uploaded in… See the full description on the dataset page: https://huggingface.co/datasets/perturb-ai/efficientnet-v2-l-adv-dataset.cctv-datasets
CCTV Datasets for helmet detection + ANPR
Training and evaluation data used by vivekvar/helmet-v5 and vivekvar/helmet-v4.
Source: Andhra Pradesh RTGS CCTV feeds (public road cameras). All crops and frames are from motorcycle traffic scenes.
Folders
Folder
Contents
Purpose
merged_v3/
YOLO-format dataset (data.yaml + train/valid/test)
Bike + rider detection training
clean_merged_data/
Cleaned / deduped crop set
Base training data for v4
extra_khadatkar/… See the full description on the dataset page: https://huggingface.co/datasets/vivekvar/cctv-datasets.cub200_dataset
Dataset Card for CUB_200_2011
Dataset Summary
The Caltech-UCSD Birds 200-2011 dataset (CUB-200-2011) is an extended version of the original CUB-200 dataset, featuring photos of 200 bird species primarily from North America. This 2011 version significantly expands its predecessor by doubling the number of images per class and introducing new part location annotations, alongside collecting detailed natural language descriptions for each image through Amazon Mechanical Turk… See the full description on the dataset page: https://huggingface.co/datasets/cassiekang/cub200_dataset.TIGAS_dataset
TIGAS Dataset
A comprehensive dataset for training AI-generated image detection models
TIGAS Model • GitHub Repository
Dataset Description
The TIGAS Dataset is a large-scale collection of real and AI-generated images designed for training and evaluating AI-generated image detection models. It contains 142,902 images from diverse sources, including state-of-the-art generative models.
Key Features
Binary classification task: Real (label=0) vs… See the full description on the dataset page: https://huggingface.co/datasets/H1merka/TIGAS_dataset.Defactify_Image_Dataset
Defactify_Image_Dataset
This dataset is associated with the paper A Comprehensive Dataset for Human vs. AI Generated Image Detection.
📝 Dataset Description
Dataset Summary
The Defactify_Image_Dataset (A Comprehensive Dataset for Human vs. AI Generated Image Detection) is a high-quality collection of 96,000 images and associated metadata designed to benchmark models for detecting and identifying the source of artificially generated content. Built using the MS… See the full description on the dataset page: https://huggingface.co/datasets/Rajarshi-Roy-research/Defactify_Image_Dataset.ARTO-Gen-Dataset
ARTO-KG: A Synthetic Artwork Dataset for Knowledge-Enhanced Understanding
Dataset Description
ARTO-KG is a large-scale synthetic artwork dataset that bridges visual content and structured knowledge through ontology-guided automated generation. Each artwork is annotated with comprehensive RDF knowledge graphs aligned with the ARTO ontology.
Dataset Summary
Total Artworks: 10,108 high-resolution images (1024×1024)
Object Instances: 39,878 (average… See the full description on the dataset page: https://huggingface.co/datasets/youngcan1/ARTO-Gen-Dataset.dacl10k
Dataset Card for dacl10k
dacl10k stands for damage classification 10k images and is a multi-label semantic segmentation dataset for 19 classes (13 damages and 6 objects) present on bridges.
The dacl10k dataset includes images collected during concrete bridge inspections acquired from databases at authorities and engineering offices, thus, it represents real-world scenarios. Concrete bridges represent the most common building type, besides steel, steel composite, and wooden bridges.… See the full description on the dataset page: https://huggingface.co/datasets/Voxel51/dacl10k.MLLM-Generated-Image-Detection-Dataset
MLLM-Generated Image Dataset
This dataset contains real and AI-generated image samples organized for binary MLLM-generated image detection.
Paper | Code
Dataset Summary
We construct an MLLM-generated image detection benchmark from GPT Image2 and Nano Banana2. This benchmark covers texture-dominated, structure-dominated, and hybrid-dominated. It is designed to evaluate detector performance under the new challenges introduced by large-scale image generation models.… See the full description on the dataset page: https://huggingface.co/datasets/zr-zhang/MLLM-Generated-Image-Detection-Dataset.synthetic-dataset-1m-dalle3-high-quality-captions
Dataset Card for Dalle3 1 Million+ High Quality Captions
Alt name: Human Preference Synthetic Dataset
Example grids for landscapes, cats, creatures, and fantasy are also available.
Description:
This dataset comprises of AI-generated images sourced from various websites and individuals, primarily focusing on Dalle 3 content, along with contributions from other AI systems of sufficient quality like Stable Diffusion and Midjourney (MJ v5 and above). As users typically… See the full description on the dataset page: https://huggingface.co/datasets/ProGamerGov/synthetic-dataset-1m-dalle3-high-quality-captions.DDR-dataset
DDR - Diabetic Retinopathy Detection Dataset
Image: Dataset Samples.
The DDR (Diabetic Retinopathy Detection) dataset is a large-scale collection of retinal fundus images designed for training and evaluating algorithms in diabetic retinopathy (DR) grading and lesion-level segmentation. It provides both image-level DR labels and pixel-level annotations of pathological features, making it suitable for… See the full description on the dataset page: https://huggingface.co/datasets/ctmedtech/DDR-dataset.LADI-v2-dataset
Dataset Card for LADI-v2-dataset
Dataset Summary : v2
The LADI-v2 dataset is a set of aerial disaster images captured and labeled by the Civil Air Patrol (CAP). The images are geotagged (in their EXIF metadata). Each image has been labeled in triplicate by CAP volunteers trained in the FEMA damage assessment process for multi-label classification; where volunteers disagreed about the presence of a class, a majority vote was taken. The classes are:
bridges_any… See the full description on the dataset page: https://huggingface.co/datasets/MITLL/LADI-v2-dataset.multiple-sclerosis-dataset
Multiple Sclerosis Dataset, Brain MRI Object Detection & Segmentation Dataset
The dataset consists of .dcm files containing MRI scans of the brain of the person with a multiple sclerosis. The images are labeled by the doctors and accompanied by report in PDF-format.
The dataset includes 13 studies, made from the different angles which provide a comprehensive understanding of a multiple sclerosis as a condition.
MRI study angles in the dataset
💴 For… See the full description on the dataset page: https://huggingface.co/datasets/UniqueData/multiple-sclerosis-dataset.danbooru2025-metadata
🎨 Danbooru 2025 Metadata
Latest Post ID: 9,158,800
(as of Apr 16, 2025)
📁 About the DatasetThis dataset provides structured metadata for user-submitted images on Danbooru, a large-scale imageboard focused on anime-style artwork.
Scraping began on January 2, 2025, and the data are stored in Parquet format for efficient programmatic access.Compared to earlier versions, this snapshot includes:
More consistent tag history tracking
Better coverage of older or previously… See the full description on the dataset page: https://huggingface.co/datasets/trojblue/danbooru2025-metadata.Crop_Disease_Image_Dataset
Crop Disease Image Dataset (5 Crops, 19 Classes)
Dataset Summary
The Crop Disease Image Dataset is a curated, high-quality agricultural image dataset designed for computer vision, deep learning, and smart farming applications. It contains 22,169 RGB leaf images spanning 5 major crops across 19 distinct healthy and diseased classes.
This dataset was constructed by collecting, filtering, and standardizing images from multiple open-source agricultural repositories… See the full description on the dataset page: https://huggingface.co/datasets/ipartzix/Crop_Disease_Image_Dataset.scanned-images-dataset-for-ocr-and-vlm-finetuning
Dataset Card for scanned_images_dataset
This is a FiftyOne dataset containing 3,482 scanned document images across 10 diverse document categories. Designed for OCR training and Vision-Language Model (VLM) fine-tuning, this dataset features real-world scanned documents with varied layouts, scanning quality, and document types.
Installation
If you haven't already, install FiftyOne:
pip install -U fiftyone
Usage
import fiftyone as fo
from… See the full description on the dataset page: https://huggingface.co/datasets/Voxel51/scanned-images-dataset-for-ocr-and-vlm-finetuning.dataset-biasX
UTKFace Dataset
Dataset Description
The UTKFace dataset is a large-scale face dataset with long age span (range from 0 to 116 years old). The dataset consists of over 20,000 face images with annotations of age, gender, and ethnicity. The images cover large variation in pose, facial expression, illumination, occlusion, resolution, etc.
Dataset Summary
Size: ~20,000 images
Format: JPG images
Resolution: Various
Annotations: Age, Gender, Race/Ethnicity… See the full description on the dataset page: https://huggingface.co/datasets/jerwinpog0427/dataset-biasX.review-dataset
MSIR-Bench Review Dataset
This repository contains an anonymized review snapshot of MSIR-Bench, a benchmark for identity-preserving style image retrieval.
Dataset Description
Each source identity is represented by an anonymous five-digit ID. Images are organized by split and identity folder. File names follow either <id>_<Style>.png, <id>_original.png, or legacy original.jpg for original reference images.
The dataset is intended for evaluating whether a retrieval… See the full description on the dataset page: https://huggingface.co/datasets/anonymous-review-dataset-2026/review-dataset.data-csgo-weapon-classification
Dataset for project: csgo-weapon-classification
Dataset Description
This dataset has for project csgo-weapon-classification was collected with the help of a bulk google image downloader.
Languages
The BCP-47 code for the dataset's language is unk.
Dataset Structure
Data Instances
A sample from this dataset looks as follows:
[
{
"image": "<1768x718 RGB PIL image>",
"target": 0
},
{
"image": "<716x375 RGBA PIL image>"… See the full description on the dataset page: https://huggingface.co/datasets/Kaludi/data-csgo-weapon-classification.imagenet-1k-wds
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 quality-controlled and human-annotated.
💡… See the full description on the dataset page: https://huggingface.co/datasets/dark-xet/imagenet-1k-wds.patfig
PatFig Dataset
Introduction
The PatFig Dataset is a curated collection of over 18,000 patent images from more than 7,000 European patent applications, spanning the year 2020. It aims to provide a comprehensive resource for research and applications in image captioning, abstract reasoning, patent analysis, and automated documentprocessing.
The overarching goal of this dataset is to advance the research in visually situated language understanding towards more… See the full description on the dataset page: https://huggingface.co/datasets/danaaubakirova/patfig.DamageTriage-Bench
DamageTriage-Bench
DamageTriage-Bench is a footprint-conditioned benchmark for per-building damage
typing from single post-event aerial images. Its five classes distinguish roof
from structural damage and partial from total affected extent:
ID
Class
0
Undamaged
1
Partial Roof Damage
2
Total Roof Damage
3
Partial Structural Damage
4
Total Structural Collapse
Quick statistics
Item
Value
Tiles
7,472 (1024 × 1024 PNG)
Labeled… See the full description on the dataset page: https://huggingface.co/datasets/Ymx1025/DamageTriage-Bench.Larch_Tree_Damage
Dataset Card for Forest Damages - Larch Casebearer
This is a FiftyOne dataset with 1536 samples.
Installation
If you haven't already, install FiftyOne:
pip install -U fiftyone
Usage
import fiftyone as fo
from fiftyone.utils.huggingface import load_from_hub
# Load the dataset
# Note: other available arguments include 'max_samples', etc
dataset = load_from_hub("Voxel51/Larch_Tree_Damage")
# Launch the App
session = fo.launch_app(dataset)
Forest… See the full description on the dataset page: https://huggingface.co/datasets/Voxel51/Larch_Tree_Damage.Capillary-Dataset
Capillary dataset
Paper: Capillary Dataset: A dataset of nail-fold capillaries captured by microscopy for diabetes detection
Github: https://github.com/urgonguyen/Capillarydataset.git
The dataset are structured as follows:
Capillary dataset
├── Classification
├── data_1x1_224
├── data_concat_1x9_224
├── data_concat_2x2_224
├── data_concat_3x3_224
├── data_concat_4x1_224
└── data_concat_4x4_224
├── Morphology_detection… See the full description on the dataset page: https://huggingface.co/datasets/MelanieCo/Capillary-Dataset.