datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
intel-image-classification
Intel Image Classification
The Intel Image Classification dataset contains images of natural scenes categorized into six classes:
Buildings
Forest
Glacier
Mountain
Sea
Street
📆 Content
The dataset contains ~25,000 images of size 150x150 pixels.
Images are evenly distributed across 6 categories:
{'buildings' -> 0,
'forest' -> 1,
'glacier' -> 2,
'mountain' -> 3,
'sea' -> 4,
'street' -> 5 }
It is divided into three parts:
Training set: ~14… See the full description on the dataset page: https://huggingface.co/datasets/sfarrukhm/intel-image-classification.autotrain-data-galaxy_classification
AutoTrain Dataset for project: galaxy_classification
Dataset Description
This dataset has been automatically processed by AutoTrain for project galaxy_classification.
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": "<256x256 RGB PIL image>",
"target": 0
},
{
"image": "<256x256 RGB PIL image>",
"target": 0
}]… See the full description on the dataset page: https://huggingface.co/datasets/Xanadu00/autotrain-data-galaxy_classification.aidovecl-vehicle-detection-classification-localization
AIDOVECL: AI-generated Dataset of Outpainted Vehicles for Eye-level Classification and Localization
We introduce an annotated AI-generated dataset of eye-level vehicle images using outpainting, offering versatile generation of diverse vehicle classes in varied contexts with pretrained models.
Citation Notice
Please ensure that all publications and presentations using this data reference the following paper:
Kazemi, A., Fatima, Q. ul A., Kindratenko, V., & Tessum, C. W.… See the full description on the dataset page: https://huggingface.co/datasets/amir-kazemi/aidovecl-vehicle-detection-classification-localization.AfriMCQA-category-classification
Afri-MCQA cross-modal cultural category classification (MTEB)
Classify the cultural category of an entry from its photograph and the question
about it spoken by a native speaker, across 16 African languages.
Labels index this list:
geography, building, and landmarks
public figure and pop culture
cooking and food
objects, materials, clothing
tranditions, art, and history
brands, products, and companies
plants and animals
people, and everyday life
vehicles and transportation… See the full description on the dataset page: https://huggingface.co/datasets/vnahata/AfriMCQA-category-classification.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.food-category-classification-v2.0
Dataset for project: food-category-classification-v2.0
Dataset Description
This dataset for project food-category-classification-v2.0 was scraped with the help of a bulk google image downloader.
Dataset Structure
Dataset Fields
The dataset has the following fields (also called "features"):
{
"image": "Image(decode=True, id=None)",
"target": "ClassLabel(names=['Bread', 'Dairy', 'Dessert', 'Egg', 'Fried Food', 'Fruit', 'Meat', 'Noodles', 'Rice'… See the full description on the dataset page: https://huggingface.co/datasets/Kaludi/food-category-classification-v2.0.chest-xray-classification
Dataset Labels
['NORMAL', 'PNEUMONIA']
Number of Images
{'train': 4077, 'test': 582, 'valid': 1165}
How to Use
Install datasets:
pip install datasets
Load the dataset:
from datasets import load_dataset
ds = load_dataset("keremberke/chest-xray-classification", name="full")
example = ds['train'][0]
Roboflow Dataset Page
https://universe.roboflow.com/mohamed-traore-2ekkp/chest-x-rays-qjmia/dataset/2
Citation… See the full description on the dataset page: https://huggingface.co/datasets/keremberke/chest-xray-classification.fall-detection-posture-classification
AI-Driven Posture Analysis & Fall Detection Dataset (Elderly Care)
Overview
This dataset supports the dissertation project "AI-Driven Posture Analysis Fall Detection System for the Elderly", completed by Patrick O. Ogbuitepu for the degree of MSc Artificial Intelligence and its Applications (CE901 MSc Project and Dissertation), School of Computer Science and Electronic Engineering (CSEE), University of Essex (2024). Supervisor: Dr Adrian Clark.
The project uses… See the full description on the dataset page: https://huggingface.co/datasets/pat2echo/fall-detection-posture-classification.data-food-classification
Dataset for project: food-classification
Dataset Description
This dataset has been processed for project food-classification.
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": "<308x512 RGB PIL image>",
"target": 0
},
{
"image": "<512x512 RGB PIL image>",
"target": 0
}]
Dataset Fields
The dataset has the… See the full description on the dataset page: https://huggingface.co/datasets/Kaludi/data-food-classification.autotrain-data-image-classification
AutoTrain Dataset for project: image-classification
Dataset Description
This dataset has been automatically processed by AutoTrain for project image-classification.
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": "<79x80 RGBA PIL image>",
"target": 1
},
{
"image": "<547x108 RGBA PIL image>",
"target": 1
}]… See the full description on the dataset page: https://huggingface.co/datasets/fsuarez/autotrain-data-image-classification.smoking_classificationautotrain-data-weather-classification
AutoTrain Dataset for project: weather-classification
Dataset Description
This dataset has been automatically processed by AutoTrain for project weather-classification.
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": "<771x514 RGB PIL image>",
"target": 2
},
{
"image": "<269x254 RGB PIL image>",
"target": 8
}]… See the full description on the dataset page: https://huggingface.co/datasets/dazzle-nu/autotrain-data-weather-classification.medicinal-leaf-classification-dataset
🌿 Medicinal Leaf Classification Dataset
An image dataset of 3 medicinal plant leaves — Aloe Vera, Neem, and Tulsi — used to train and evaluate deep learning classifiers.
Dataset Summary
Property
Value
Total Images
~7,380 (train + val)
Classes
3
Image Format
JPEG / PNG
Task
Image Classification
Classes
Index
Class
Train+Val Images
Test Images
0
Aloe Vera
—
183
1
Neem
—
453
2
Tulsi
—
284
Splits… See the full description on the dataset page: https://huggingface.co/datasets/poojan-s/medicinal-leaf-classification-dataset.indoor-scene-classification
Dataset Labels
['meeting_room', 'cloister', 'stairscase', 'restaurant', 'hairsalon', 'children_room', 'dining_room', 'lobby', 'museum', 'laundromat', 'computerroom', 'grocerystore', 'hospitalroom', 'buffet', 'office', 'warehouse', 'garage', 'bookstore', 'florist', 'locker_room', 'inside_bus', 'subway', 'fastfood_restaurant', 'auditorium', 'studiomusic', 'airport_inside', 'pantry', 'restaurant_kitchen', 'casino', 'movietheater', 'kitchen', 'waitingroom', 'artstudio', 'toystore'… See the full description on the dataset page: https://huggingface.co/datasets/keremberke/indoor-scene-classification.data-food-category-classification
Dataset for project: food-category-classification
Dataset Description
This dataset is for project food-category-classification.
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": "<512x512 RGB PIL image>",
"target": 0
},
{
"image": "<512x512 RGB PIL image>",
"target": 0
}]
Dataset Fields
The dataset has… See the full description on the dataset page: https://huggingface.co/datasets/Kaludi/data-food-category-classification.fresh_rotten_fruit_classification
Fresh Rotten Fruit Classification
A dataset for quality classification of 8 types of fruit. The dataset contains raw and augmented versions.The raw dataset contains 3,200 images.Images per class:
Fresh: 1,600
Rotten: 1,600
The augmented dataset contains 12,335 images.Images per class:
Fresh: 6,194
Rotten: 6,141
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
Citation
@article{SULTANA2022108552,
title = {An… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/fresh_rotten_fruit_classification.Uddessho-Bangla-Multimodal-Intent-Classification
📊 Uddessho Dataset — Multimodal Author Intent Classification
Uddessho (meaning "Intent" in English) is a multimodal dataset created for author intent classification in the low-resource Bangla language.It contains 3,048 social media posts (text + images) labeled into six distinct intent types.
🏷️ Intent Categories & Label Mapping
Label ID
Class Name
0
Advocative
1
Controversial
2
Exhibitionist
3
Expressive
4
Informative
5
Promotive
📂… See the full description on the dataset page: https://huggingface.co/datasets/Mukaffi28/Uddessho-Bangla-Multimodal-Intent-Classification.TN5000-thyroid-nodule-classification
TN5000 Thyroid Nodule Classification Dataset
A preprocessed, CNN-ready version of the TN5000 thyroid ultrasound dataset, cropped to individual nodule regions of interest and standardized to 224×224 PNG images for binary classification (Benign vs. Malignant).
Source Dataset
This dataset is derived from:
TN5000: An Ultrasound Image Dataset for Thyroid Nodule Detection and ClassificationXiaoxian Yu et al., Scientific Data (Nature Publishing Group), 2025DOI:… See the full description on the dataset page: https://huggingface.co/datasets/Johnyquest7/TN5000-thyroid-nodule-classification.bruised_vegetable_classification
Bruised Vegetable Classification
A dataset for classification of Bruised Vegetable Classification. The dataset contains 4,464 images across 3 classes.
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
Citation
@article{samanta2025nature,
title={Nature's best vs. bruised: A veggie edibility evaluation database},
author={Samanta, Bidisha and Banerjee, Sriparna and Das, Ranadhir and Chaudhuri, Sheli Sinha and Djemal… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/bruised_vegetable_classification.Crop_Weed_classification
Crop & Weed Classification Dataset
© 2026 Rishi. All rights reserved.
This dataset is provided under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license.
Usage
You are free to share and adapt this dataset under the following terms:
Attribution: You must give appropriate credit to the author.
Non-Commercial: You may not use this material for commercial purposes.
Citation & Paper
A research paper utilizing this… See the full description on the dataset page: https://huggingface.co/datasets/Rishi210904/Crop_Weed_classification.spark-plug-classification
Spark Plug Condition Classification
Labeled images of spark plugs for training a multi-class visual classifier. Includes four categories:
normal
carbon_fouled
oil_fouled
mechanical_damage
Optimized for use in Edge Impulse with the Transfer Learning (MobileNetV2) block.
Input: Images (96x96)
Task: Multi-class classification
Use case: Visual diagnostics and condition monitoring
Model trained and demonstrated on Edge Impulse.
Looking for anomaly detection?See the… See the full description on the dataset page: https://huggingface.co/datasets/eoinedge/spark-plug-classification.NSFW-MultiDomain-Classification
NSFW_MultiDomain
The NSFW_MultiDomain dataset is a curated image classification dataset focused on multi-domain adult content recognition. It consists of 5 distinct categories aimed at facilitating the development of robust NSFW (Not Safe For Work) image classification models. This dataset enables training and benchmarking of models that can distinguish between subtle variations in explicit and non-explicit content across artistic, animated, and real-world imagery.… See the full description on the dataset page: https://huggingface.co/datasets/strangerguardhf/NSFW-MultiDomain-Classification.HSRP_classification_data
HSRP Classification Dataset
Description
Dataset created for the Smart-HSRP project to train an image
classification model for HSRP-related classification.
Ownership
This dataset was collected, prepared, and annotated for this project.
Classes
HSRP
0
NON-HSRP
1
Dataset Structure
train/
├──hsrp/
└──non-hsrp/
validation/
├──hsrp/
└──non-hsrp/
test/
├──hsrp/
└──non-hsrp/
Collection
All the… See the full description on the dataset page: https://huggingface.co/datasets/Smolry/HSRP_classification_data.corn_leaf_pest_classification
Corn Leaf Pest Classification
A dataset for image classification of Corn Leaf Pest Classification.The raw dataset contains 1,308 images.The augmented dataset contains 11,772 images.
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
Citation
@article{tchokogoue2025towards,
title={Towards precision agriculture: A dataset for early detection of corn leaf pests},
author={Tchokogou{\'e}, Thierry and Noumsi, Auguste… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/corn_leaf_pest_classification.helicopter-classification
DCSkyCam Helicopter Classification Dataset
This dataset contains cropped images of helicopters and non-helicopter objects captured by the DCSkyCam - a Raspberry Pi-based webcam in Washington, DC. The images were used to train binary and multi-class helicopter classification models using transfer learning from EfficientNet.
Dataset Description
The DCSkyCam system used a three-stage detection pipeline:
Object Detection (SSD MobileNet V3) identifies candidate… See the full description on the dataset page: https://huggingface.co/datasets/dcskycam/helicopter-classification.agarwood_leaf_disease_classification
Agarwood Leaf Disease Classification
A dataset for disease classification of agarwood leaves. The dataset contains 5,472 images across 14 classes: Anthracnose, Black spots, Brown clumps, Brown spots, Downy mildew, Flea Beetles, Healthy, Mealy bugs, Mosaic Viruses, Powdery mildew, Scale insect, Sooty mold, Spiders, Translucent lesion.Images per class:
Anthracnose: 232
Black spots: 674
Brown clumps: 118
Brown spots: 1,055
Downy mildew: 674
Flea Beetles: 115
Healthy: 415
Mealy… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/agarwood_leaf_disease_classification.papaya_leaf_disease_classification_bangladesh
Papaya Leaf Disease Classification Bangladesh
A dataset for disease classification of Papaya leaves. The dataset contains raw and augmented versions.The raw dataset contains 1,400 images.Images per class:
Healthy Leaf: 182
Leaf Curl: 284
Mealybug: 233
Mite Disease: 243
Mosaic: 214
Ring Spot: 244
The augmented dataset contains 6,618 images.Images per class:
Healthy Leaf: 879
Leaf Curl: 1,334
Mealybug: 1,096
Mite Disease: 1,149
Mosaic: 1,009
Ring Spot: 1,151
This dataset is… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/papaya_leaf_disease_classification_bangladesh.painting-style-classification
Dataset Labels
['Realism', 'Art_Nouveau_Modern', 'Analytical_Cubism', 'Cubism', 'Expressionism', 'Action_painting', 'Synthetic_Cubism', 'Symbolism', 'Ukiyo_e', 'Naive_Art_Primitivism', 'Post_Impressionism', 'Impressionism', 'Fauvism', 'Rococo', 'Minimalism', 'Mannerism_Late_Renaissance', 'Color_Field_Painting', 'High_Renaissance', 'Romanticism', 'Pop_Art', 'Contemporary_Realism', 'Baroque', 'New_Realism', 'Pointillism', 'Northern_Renaissance', 'Early_Renaissance'… See the full description on the dataset page: https://huggingface.co/datasets/keremberke/painting-style-classification.pokemon-classification
Dataset Labels
['Porygon', 'Goldeen', 'Hitmonlee', 'Hitmonchan', 'Gloom', 'Aerodactyl', 'Mankey', 'Seadra', 'Gengar', 'Venonat', 'Articuno', 'Seaking', 'Dugtrio', 'Machop', 'Jynx', 'Oddish', 'Dodrio', 'Dragonair', 'Weedle', 'Golduck', 'Flareon', 'Krabby', 'Parasect', 'Ninetales', 'Nidoqueen', 'Kabutops', 'Drowzee', 'Caterpie', 'Jigglypuff', 'Machamp', 'Clefairy', 'Kangaskhan', 'Dragonite', 'Weepinbell', 'Fearow', 'Bellsprout', 'Grimer', 'Nidorina', 'Staryu', 'Horsea'… See the full description on the dataset page: https://huggingface.co/datasets/keremberke/pokemon-classification.human-nonhuman-face-classification
Human vs Non-Human Face Dataset
A robust dataset for binary classification between real human faces and non-human face-like objects (statues, art, gaming, anime).
📊 Dataset Statistics
Split
Human
Non-Human
Total
Train
3,024
2,949
5,973
Validation
864
842
1,706
Test
433
422
855
Total
8,534
📁 Format
Labels: 0: human, 1: non_human.
🚀 Quick Start
from datasets import load_dataset
ds =… See the full description on the dataset page: https://huggingface.co/datasets/LakoreAI/human-nonhuman-face-classification.