datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
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.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.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.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.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.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.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.smoking_classificationTN5000-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.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.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.apple_leaf_disease_classification
Apple Leaf Disease Classification
A dataset for image classification of Apple Leaf Disease Classification. The dataset contains 7,505 images across 3 classes: Alternaria, Apple_Mosaic, Healthy.Images per class:
Alternaria: 2,523
Apple_Mosaic: 2,523
Healthy: 2,459
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
Citation
@article{yatoo2024indigenous,
title={An indigenous dataset for the detection and classification… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/apple_leaf_disease_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.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.fruit-classification
Fruit Classification Dataset
This dataset contains images of fruits classified into six categories:
fresh and rotten apples, bananas, and oranges.
Classes
fresh_apple
fresh_banana
fresh_orange
rotten_apple
rotten_banana
rotten_orange
Structure
Images stored in train/ and test/
Labels provided in train.csv
Usage
from datasets import load_dataset
dataset = load_dataset("menasi11/fruit-classification")
print(dataset)
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.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.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.plant_doc_classification
Plant Doc Classification
A dataset for disease classification of various plants. The dataset contains 2,569 images across 28 classes:Images per class:
Apple Scab Leaf: 93
Apple leaf: 91
Apple rust leaf: 88
Bell_pepper leaf: 61
Bell_pepper leaf spot: 71
Blueberry leaf: 114
Cherry leaf: 57
Corn Gray leaf spot: 68
Corn leaf blight: 191
Corn rust leaf: 116
Peach leaf: 111
Potato leaf early blight: 116
Potato leaf late blight: 105
Raspberry leaf: 119
Soyabean leaf: 65
Squash Powdery… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/plant_doc_classification.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.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.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.TOM2024_disease_classification
TOM2024 Disease Classification Classification
A dataset for disease classification of Tomato, Onion, and Maize. The dataset contains raw and augmented versions.The raw dataset contains 12,082 images.Images per class:
abiotic-disease-d: 77
alternaria-d: 837
alternaria-mite-d: 8
aphids-p: 4
bacterial-floundering-d: 252
blossom-end-rot-d: 118
bulb-blight-d: 30
caterpillar-p: 879
curvulariosis-d: 259
excess-nitrogen-d: 43
fusarium-d: 756
healthy-fruit: 552
healthy-leaf: 2,046… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/TOM2024_disease_classification.SIMPDV1_plant_classification
SIMPDV1 Plant Classification
A dataset for classification of medicinal plants in South India. The dataset contains 2,513 images across 20 classes: Abutilon Indicum, Aloe barbadensis miller, Calotropis gigantea, Canna indica, Cissus quadrangularis, Curcuma longa, Eclipta prostrate, Eichhornia Crassipes, Hibiscus Rosasinensis, Ixora coccinea, Justica adhatoda, Murraya koenigii, Ocimum tenuiflorum, Ouretlanata, Phyllanthus amarus, Ricinus communis, Senna Atriculata, Sesbania… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/SIMPDV1_plant_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.SapBark_64_variety_classification
Sapbark 64 Variety Classification
A dataset for variety classification of sapling bark of fruit trees. The dataset contains 5,815 images across 64 classes.
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
Citation
@article{alizadeh2025sapbark,
title={SapBark-64: A dataset of bark images for 64 fruit-tree sapling classes},
author={Alizadeh, Sayyad and Shamsi, Hamed},
journal={Data in Brief},
pages={112354}… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/SapBark_64_variety_classification.Animal_Image_Classification_DatasetDataset Summary:
The Animal Image Classification Dataset is a comprehensive collection of images tailored for the development and evaluation of machine learning models in the field of computer vision. It contains 3,000 JPG images, carefully segmented into three classes representing common pets and wildlife: cats, dogs, and snakes.
Dataset Contents:
cats/: A set of 1,000 JPG images of cats, showcasing a wide array of breeds, environments, and postures.
dogs/: A diverse compilation of 1,000 dog… See the full description on the dataset page: https://huggingface.co/datasets/AlvaroVasquezAI/Animal_Image_Classification_Dataset.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.Product_Image_Classification
Product Image Classification Dataset
Датасет изображений товаров, собранный с крупных узбекских маркетплейсов (asaxiy.uz, texnomart.uz, olcha.uz) для задачи автоматической классификации e-commerce продукции.
Описание датасета
Данный набор данных содержит фотографии товаров, разбитых по 5 основным категориям электроники. Данные прошли автоматическую очистку от поврежденных файлов и дедупликацию по MD5-хешу.
Категории (Classes):
headphones — Наушники… See the full description on the dataset page: https://huggingface.co/datasets/NurzatS/Product_Image_Classification.typhoon-intensity-classification
Typhoon - Image Classification Dataset
This dataset comes from PTIT AI Challenge and is organized for a multi-class image classification task focusing on tropical cyclone (typhoon) intensity estimation.
Dataset Structure
The directory structure is organized as follows:
train/
├── images/
│ ├── image1.jpg
│ └── ...
└── annotations.csv (only present in the train folder)
The public_test and private_test sets are used to evaluate and score the… See the full description on the dataset page: https://huggingface.co/datasets/star092304/typhoon-intensity-classification.