datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
SuperWikiImage-7M
Dataset Card for SuperWikiImage (SWI)
Waifu to catch your attention.
Dataset Details
Dataset Description
Off from the presses of SuperWikipedia-NEXT comes SuperWikiImage: A ~15TiB (~7 Million) collection of images from wikipedia.
Curated by: KaraKaraWitch
Funded by: Recursal.ai
Shared by: KaraKaraWitch
Language(s) (NLP): Many. Refer to the data below for a list of languages.
License: Mixed. Refer to lower section on licensing
Dataset Sources… See the full description on the dataset page: https://huggingface.co/datasets/recursal/SuperWikiImage-7M.Military-Aircraft-Recognition-datasetThis is a remote sensing image Military Aircraft Recognition dataset that include 3842 images, 20 types, and 22341 instances annotated with horizontal bounding boxes and oriented bounding boxes.
ms1mv3-recordio
MS-Celeb-1M (v3)
This dataset is introduced in the Lightweight Face Recognition Challenge at ICCV 2019. Paper.
There are 5,179,510 images and 93,431 ids. All images are aligned based on facial landmarks predicted by RetinaFace and resized to 112x112.
This was downloaded from https://github.com/deepinsight/insightface/tree/master/recognition/_datasets_ (MS1M-RetinaFace). The dataset is stored in MXNet RecordIO format.
Usage
import io
import numpy as np
from PIL import… See the full description on the dataset page: https://huggingface.co/datasets/gaunernst/ms1mv3-recordio.facial-expression-recognition-dataset
Emotion recognition Dataset
Dataset comprises 199,955 images featuring 28,565 individuals displaying a variety of facial expressions. It is designed for research in emotion recognition and facial expression analysis across diverse races, genders, and ages.
By utilizing this dataset, researchers and developers can enhance their understanding of facial recognition technology and improve the accuracy of emotion classification systems. - Get the data
This dataset includes images… See the full description on the dataset page: https://huggingface.co/datasets/UniDataPro/facial-expression-recognition-dataset.sudoku-image-recognition
Dataset Card for Sudoku Image Recognition
Images of Sudoku puzzles for puzzle recognition. This dataset was used to bootstrap the Sudoku OCR engine.
Dataset Details
Dataset Description
This dataset consists of 1400 labelled images of Sudoku puzzles. It is intended for training and evaluating a system that can automatically determine the state of each cell in the puzzle: whether it is solved or unsolved, and which digits it contains. The images are split into… See the full description on the dataset page: https://huggingface.co/datasets/Lexski/sudoku-image-recognition.Recraft-V2_t2i_human_preference
Rapidata Recraft-V2 Preference
This T2I dataset contains over 195k human responses from over 47k individual annotators, collected in just ~1 Day using the Rapidata Python API, accessible to anyone and ideal for large scale evaluation.
Evaluating Recraft-V2 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/Recraft-V2_t2i_human_preference.recycling-dataset
Dataset Card for recycling-dataset
Dataset Summary
This is a recycling dataset that can be used for image classification. It has 11 categories:
aluminium
batteries
cardboard
disposable plates
glass
hard plastic
paper
paper towel
polystyrene
soft plastics
takeaway cups
It was scrapped from DuckDuckGo using this tool: https://pypi.org/project/jmd-imagescraper/
Human_Action_Recognition
Dataset Summary
A dataset from kaggle. origin: https://dphi.tech/challenges/data-sprint-76-human-activity-recognition/233/data
Introduction
The dataset features 15 different classes of Human Activities.
The dataset contains about 12k+ labelled images including the validation images.
Each image has only one human activity category and are saved in separate folders of the labelled classes
PROBLEM STATEMENT
Human Action Recognition (HAR) aims to understand… See the full description on the dataset page: https://huggingface.co/datasets/Bingsu/Human_Action_Recognition.recaptchav2-29k
ReCAPTCHAv2-29k
ReCAPTCHAv2-29k is a dataset consisting of images derived from Google's ReCAPTCHA v2 system, which is widely used for online human verification.
It contains thousands of ReCAPTCHA images, each paired with corresponding labels indicating the presence of specific objects or features (e.g., bicycle, bus, car).
This dataset is intended for educational and research purposes and is particularly suited for tasks such as feature extraction and multi-label image… See the full description on the dataset page: https://huggingface.co/datasets/nobodyPerfecZ/recaptchav2-29k.recaptcha-57k-images-dataset
recaptcha-57k-images-dataset
Image dataset of reCAPTCHA tile images for image classification. This dataset
is used to train recaptcha-classification-57k
and powers vision-ai-recaptcha-solver.
Dataset summary
Task: image classification
Size: ~57k labeled images
Labels: 14 classes (13 target classes + other)
Labels
Target classes in this dataset:
bicycle
bridge
bus
car
chimney
crosswalk
fire hydrant
motorcycle
mountain
palm tree
stairs
tractor
traffic light… See the full description on the dataset page: https://huggingface.co/datasets/DannyLuna/recaptcha-57k-images-dataset.multi-label-food-recognition
Multi-Label Food Recognition Dataset
This is a multi-label food recognition dataset generated from single-class food images.
Each image contains 2-5 different food items composited together using natural composition methods.
Dataset Details
Total Images: 13,000
Training Images: 10,400 (80%)
Validation Images: 2,600 (20%)
Number of Classes: 90
Labels per Image: 2-5 labels
Image Format: RGB, 512x512 pixels
File Format: Parquet
Dataset Structure
Each sample… See the full description on the dataset page: https://huggingface.co/datasets/ibrahimdaud/multi-label-food-recognition.fashion-recommendation-images
High-Resolution Fashion Product Images
This dataset is a highly optimized, high-resolution subset of the popular Fashion Product Images Dataset originally hosted on Kaggle.
It contains thousands of unique e-commerce fashion products, combining high-resolution product images with multiple descriptive label attributes.
All low-resolution thumbnails and anomalies have been aggressively filtered out. Every image in this dataset has a minimum resolution of 640px on its shortest… See the full description on the dataset page: https://huggingface.co/datasets/GangHitman/fashion-recommendation-images.viewpoint-aware-pig-posture-recognition
Viewpoint-Aware Pig Posture Recognition Dataset
This dataset supports multi-camera, viewpoint-aware pig posture recognition in livestock barn environments. It contains real-world pig images, bounding box annotations, posture class labels, and per-instance camera viewpoint angles (azimuth and elevation) derived from PnP-based camera calibration.
Code: Anil-Bhujel/viewpoint-aware-pig-posture-recognition on GitHub
Dataset Summary
Images were captured from 2… See the full description on the dataset page: https://huggingface.co/datasets/anilbhujel/viewpoint-aware-pig-posture-recognition.Recap-DataComp-1B-FoodOrDrink
Recap-DataComp-1B: Food or Drink
A filtered subset of Recap-DataComp-1B containing 106,230,157 rows classified as food/drink content, enriched with structured food/drink extraction from FoodExtract-v2.
Overview
Count
Percentage
Total rows
106,230,157
100%
Food/drink (Stage 5 label)
96,618,895
91.0%
Not food/drink (Stage 5 label)
9,611,262
9.0%
FoodExtract (re_caption): food/drink
79,519,489
74.9%
FoodExtract (re_caption): not food/drink
26,710,156… See the full description on the dataset page: https://huggingface.co/datasets/mrdbourke/Recap-DataComp-1B-FoodOrDrink.face-recognition-image-dataset
Image Dataset of face images for compuer vision tasks
Dataset comprises 500,600+ images of individuals representing various races, genders, and ages, with each person having a single face image. It is designed for facial recognition and face detection research, supporting the development of advanced recognition systems.
By leveraging this dataset, researchers and developers can enhance deep learning models, improve face verification and face identification techniques, and refine… See the full description on the dataset page: https://huggingface.co/datasets/UniDataPro/face-recognition-image-dataset.Recraft-v3-24-7-25_t2i_human_preference
Rapidata Recraft v3 Preference
This T2I dataset contains over ~400'000 human responses from over ~50'000 individual annotators, collected in less than 7h using the Rapidata Python API, accessible to anyone and ideal for large scale evaluation.
Evaluating Recraft v3 (version from 24.7.2025) 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 future… See the full description on the dataset page: https://huggingface.co/datasets/Rapidata/Recraft-v3-24-7-25_t2i_human_preference.Korean_Receipts_Dataset
Korean Receipts Dataset
This dataset contains high-resolution images of Korean retail receipts from supermarkets, restaurants, and stores. The dataset has been anonymized to remove personal information and is intended for AI research in OCR, document understanding, and financial analytics.
Contact
For queries or collaborations related to this dataset, contact:
anoushka@kgen.io
abhishek.vadapalli@kgen.io
Supported Tasks
Task Categories:
Image… See the full description on the dataset page: https://huggingface.co/datasets/HumynLabs/Korean_Receipts_Dataset.nano-receipts
🧾 Nano Receipts Dataset
A diverse collection of 2428 hyper-realistic synthetic receipt images generated using state-of-the-art text-to-image AI models.
🚀 Quick Start
from datasets import load_dataset
# Load dataset (fast parquet format!)
dataset = load_dataset("34data/nano-receipts")
# Access images
image = dataset["train"][0]["image"] # PIL Image
filename = dataset["train"][0]["filename"]
📊 Dataset Details
Total Images: 2428 receipts
Format:… See the full description on the dataset page: https://huggingface.co/datasets/34data/nano-receipts.palm-recognition-dataset24,000 high-quality images from 2,000 diverse participants worldwide - smartphone palm recognition dataset for biometric authentication
Participants & Demographics
2,000 diverse participants from multiple countries
Balanced gender representation
6+ ethnic groups: Black, South Asian, Caucasian, Arab/Middle Eastern, Hispanic, East Asian
Age range: Under 20 to 50+ years
Both right-handed and left-handed individuals
Image Capture
Smartphone-based: 200+ different models… See the full description on the dataset page: https://huggingface.co/datasets/AxonData/palm-recognition-dataset.MAHE_deepfake_recognition_datasetThis dataset is for different educational experiments of deepfake images classification.
It consists of the small datasets with various original and deepfake scenes (faces, animation, urban scenes and others):
Columbia Uncompressed Image Splicing Dataset
Kaggle Deepfake Dataset Challenge
CommunityForensics-Small
Traffic_Sign_Recogntion_DatabaseTSRD (Traffic Sign Recognition Database) 是一个中国交通标志数据集，包含多种交通标志类别。数据集分为训练集和测试集：
训练集：包含约4170张图像
测试集：包含约1994张图像
类别数：约58个不同的交通标志类别
数据集格式为：
图像文件名;宽;高;x1;y1;x2;y2;类别;
包含全种类数据集 / 4方向指示牌数据集
gpt4o-receipt
GPT4o-Receipt: AI-Generated Receipt Dataset
This directory contains the AI-generated receipts from the
GPT4o-Receipt benchmark, introduced in:
GPT4o-Receipt: A Dataset and Human Study for AI-Generated Document ForensicsYan Zhang*, Simiao Ren*†, Ankit Raj, En Wei, Dennis Ng, Alex Shen, Jiayu Xue, Yuxin Zhang, Evelyn MarottaarXiv:2603.11442 · March 2026 · CC BY-NC-SA 4.0*Equal contribution. †Corresponding author: benren@scam.ai
What Is GPT4o-Receipt?
GPT4o-Receipt is… See the full description on the dataset page: https://huggingface.co/datasets/Scam-AI/gpt4o-receipt.raw-food-recognition
Merged Raw Food Recognition Dataset
Dataset Description
This dataset is a comprehensive compilation of three publicly available food recognition datasets, merged and curated for raw food recognition tasks. The dataset contains images of various raw food items including fruits, vegetables, dairy products, and beverages, intended for educational purposes and the development of image recognition models.
Purpose
This dataset is created for educational purposes only… See the full description on the dataset page: https://huggingface.co/datasets/ibrahimdaud/raw-food-recognition.povarenok_recipes_detail
povarenok_recipes_detail
Crawled detailed recipes from povarenok.ru website.
Structure
WIP
letter_recognition
Dataset Card for "letter_recognition"
Images in this dataset was generated using the script defined below. The original dataset in CSV format and more information of the original dataset is available at A-Z Handwritten Alphabets in .csv format.
import os
import pandas as pd
import matplotlib.pyplot as plt
CHARACTER_COUNT = 26
data = pd.read_csv('./A_Z Handwritten Data.csv')
mapping = {str(i): chr(i+65) for i in range(26)}
def generate_dataset(folder, end, start=0):
if not… See the full description on the dataset page: https://huggingface.co/datasets/pittawat/letter_recognition.facial-emotion-recognition-datasetThe dataset consists of images capturing people displaying 7 distinct emotions
(anger, contempt, disgust, fear, happiness, sadness and surprise).
Each image in the dataset represents one of these specific emotions,
enabling researchers and machine learning practitioners to study and develop
models for emotion recognition and analysis.
The images encompass a diverse range of individuals, including different
genders, ethnicities, and age groups*. The dataset aims to provide
a comprehensive representation of human emotions, allowing for a wide range of
use cases.Black_People_Face_Recognition
Black people Face Detection Dataset: 3M+ Identities
Large human faces dataset for face recognition models (10M+ images)
Share with us your feedback and recieve additional samples for free!😊
Full version of dataset is availible for commercial usage - leave a request on our website Axon Labs to purchase the dataset 💰
Dataset targeting 1:N and 1:1 NIST face recognition tests. Dataset contains 3M individuals, each with 3-5 images containing their faces
The dataset is “cleaned” and has… See the full description on the dataset page: https://huggingface.co/datasets/AxonData/Black_People_Face_Recognition.nano-receipts
🧾 Nano Receipts Dataset
A diverse collection of 2428 hyper-realistic synthetic receipt images generated using state-of-the-art text-to-image AI models.
🚀 Quick Start
from datasets import load_dataset
# Load dataset (fast parquet format!)
dataset = load_dataset("34data/nano-receipts")
# Access images
image = dataset["train"][0]["image"] # PIL Image
filename = dataset["train"][0]["filename"]
📊 Dataset Details
Total Images: 2428 receipts… See the full description on the dataset page: https://huggingface.co/datasets/samarth010/nano-receipts.Recruitment-Task-3
DeepWeeds - AI-MED AGH convenience mirror
This is a convenience mirror of the official DeepWeeds image archive and the
upstream annotations pinned to a specific commit. original/images.zip is
preserved unchanged; images are not extracted or duplicated here. models.zip
from the source authors is deliberately not mirrored.
Dataset facts
17,509 in-situ images from Queensland, Australia.
Nine classes: eight weed species plus Negative.
The authors publish five folds… See the full description on the dataset page: https://huggingface.co/datasets/AI-MED-AGH/Recruitment-Task-3.medical_records_parsing_validation_set
Medical Records Parsing Validation Set
Dataset Composition and Clinical Relevance
The Eka Medical Records Parsing Dataset empowers evaluation of AI systems designed to extract structured information from unstructured medical documents, enabling true digitisation of healthcare data while maintaining clinical accuracy.
The dataset comprise 288 carefully selected images of laboratory reports and prescriptions representing diverse formats and templates encountered in Indian… See the full description on the dataset page: https://huggingface.co/datasets/ekacare/medical_records_parsing_validation_set.