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.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.smoking_classificationbruised_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.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.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.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.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.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.crop_pest_disease_classification
Crop Pest Disease Classification
A dataset for classification of disease/damage from common crop pests. The dataset contains raw and augmented versions.The raw dataset contains 25,170 images.Images per class:
anthracnose: 1,729
bacterial blight: 2,614
brown spot: 1,481
fall armyworm: 285
grasshoper: 673
green mite: 1,015
gumosis: 392
healthy: 3,235
leaf beetle: 938
leaf blight: 2,292
leaf curl: 514
leaf miner: 1,378
leaf spot: 1,249
mosaic: 1,205
red rust: 1,682
septoria leaf… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/crop_pest_disease_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.citrus_fruit_variety_classification
Citrus Fruit Variety Classification
A dataset for variety classification of citrus fruits. The dataset contains raw and augmented versions.The raw dataset contains 1,379 images.Images per class:
murcott: 280
ponkan: 328
tangerine: 400
tankan: 371
The augmented dataset contains 7,584 images.Images per class:
murcott: 1,540
ponkan: 1,803
tangerine: 2,200
tankan: 2,041
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
The original… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/citrus_fruit_variety_classification.shoe-classification
Dataset Labels
['converse', 'adidas', 'nike']
Number of Images
{'train': 576, 'test': 83, 'valid': 166}
How to Use
Install datasets:
pip install datasets
Load the dataset:
from datasets import load_dataset
ds = load_dataset("keremberke/shoe-classification", name="full")
example = ds['train'][0]
Roboflow Dataset Page
https://universe.roboflow.com/popular-benchmarks/nike-adidas-and-converse-shoes-classification/dataset/4… See the full description on the dataset page: https://huggingface.co/datasets/keremberke/shoe-classification.uchen_ume_classification_dataset
Uchen–Ume Classification Benchmark
A binary image classification dataset for distinguishing two fundamental categories of Tibetan script: Uchen (དབུ་ཅན།, headed script with a horizontal top stroke) and Ume (དབུ་མེད།, headless script without a top stroke). All images are raw, unprocessed manuscript scans from the Buddhist Digital Resource Center (BDRC).
Model: openpecha/uchen-ume-classifier
Dataset summary
Split
Examples
Uchen
Ume
Train
9,110
~3,124
~5,986… See the full description on the dataset page: https://huggingface.co/datasets/openpecha/uchen_ume_classification_dataset.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.guava_disease_classification
Guava Disease Classification
A dataset for disease classification of guava fruits and leaves. The dataset contains raw and augmented versions.The raw dataset contains 3,049 images.Images per class:
Anthracnose: 500
Canker: 192
Dot: 219
Healthy: 1,590
Rust: 167
Scab: 119
Styler end root: 262
The augmented dataset contains 20,344 images.Images per class:
Anthracnose: 4,026
Canker: 1,344
Dot: 1,533
Healthy: 8,724
Rust: 1,169
Scab: 1,190
Styler end root: 2,358
This dataset is… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/guava_disease_classification.guava_damage_classification
Guava Damage Classification
A dataset for image classification of various types of guava damage. The dataset contains 3,959 rgb and thermal images across 7 classes: 15cm_drop, 30cm_drop, 45cm_drop, chilling_injured, diseased, healthy, mixed_drop.Images per class:
15cm_drop: 887
30cm_drop: 832
45cm_drop: 1,078
chilling_injured: 32
diseased: 395
healthy: 588
mixed_drop: 147
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/guava_damage_classification.pokemon-classification
Dataset Labels
['Golbat', 'Machoke', 'Omastar', 'Diglett', 'Lapras', 'Kabuto', 'Persian', 'Weepinbell', 'Golem', 'Dodrio', 'Raichu', 'Zapdos', 'Raticate', 'Magnemite', 'Ivysaur', 'Growlithe', 'Tangela', 'Drowzee', 'Rapidash', 'Venonat', 'Pidgeot', 'Nidorino', 'Porygon', 'Lickitung', 'Rattata', 'Machop', 'Charmeleon', 'Slowbro', 'Parasect', 'Eevee', 'Starmie', 'Staryu', 'Psyduck', 'Dragonair', 'Magikarp', 'Vileplume', 'Marowak', 'Pidgeotto', 'Shellder', 'Mewtwo', 'Farfetchd'… See the full description on the dataset page: https://huggingface.co/datasets/fcakyon/pokemon-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.AgriVision4_disease_classification
AgriVision4 Disease Classification
A dataset for disease classification of Bottle Gourd, Zucchini, Papaya, and Tomato. The dataset contains raw and augmented versions.The raw dataset contains 5,246 images.Images per class:
Alternaria_Leaf_Blight: 303
Angular_Leaf_Spot: 120
Anthracnose: 405
Bacterial_Blight: 183
Carica_Insect_Hole: 318
Curled_Yellow_Spot: 538
Downy_Mildew: 496
Dry_Leaf: 67
Early_Alternaria_Leaf_Blight: 179
Fungal_Damage_Leaf: 39
Healthy: 636
Healthy_leaf: 189… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/AgriVision4_disease_classification.CottonWeedID15_classification
Cottonweedid15 Classification
This dataset contains real-world RGB images of 15 common weed species found in cotton agricultural fields, captured under natural field conditions. The images depict weeds growing in typical cotton crop environments, providing a practical resource for developing and evaluating computer vision models for weed identification in precision agriculture applications. The dataset contains 5,187 images across 15 classes: Carpetweeds, Crabgrass, Eclipta… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/CottonWeedID15_classification.medicinal_plant_classification_bd
Medicinal Plant Classification Bd
This dataset contains real RGB images of medicinal plants native to Bangladesh, captured in a controlled laboratory environment. Images were collected using handheld smartphones during the summer months (July to August), providing a diverse and standardized representation of plant specimens under consistent lighting and background conditions. The dataset contains 5,000 images across 10 classes: Bohera, Devilbackbone, Haritoki, Lemongrass… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/medicinal_plant_classification_bd.edgeimpulse-test-image-classification
Edgeimpulse Test Image Classification
This dataset is an integration-test fixture for Edge Impulse's "Import from Hugging Face" flow.
Structure
Splits: train, validation, test
Main fields: image, label
Extra metadata columns (from metadata.csv):
source_split
source_file
source_stem
source_path
Important note
Label source mode: source-metadata.
chest-xray-classification
Dataset Labels
['PNEUMONIA', 'NORMAL']
Number of Images
{'test': 582, 'valid': 1165, 'train': 12230}
How to Use
Install datasets:
pip install datasets
Load the dataset:
from datasets import load_dataset
ds = load_dataset("trpakov/chest-xray-classification", name="full")
example = ds['train'][0]
Roboflow Dataset Page
https://universe.roboflow.com/mohamed-traore-2ekkp/chest-x-rays-qjmia/dataset/3
Citation
License… See the full description on the dataset page: https://huggingface.co/datasets/trpakov/chest-xray-classification.ICPTC_pistachio_tree_variety_classification
ICPTC Pistachio Tree Variety Classification
A dataset for variety classification of pistachio trees. The dataset contains 526 images across 4 classes: J, L, R, S.Images per class:
J: 117
L: 129
R: 109
S: 171
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
The original train/test/val split has been preserved in the split column.
Citation
@article{heidary2021icptc,
title={ICPTC: Iranian commercial pistachio tree… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/ICPTC_pistachio_tree_variety_classification.wheat_mosaic_classification_multispectral
Wheat Mosaic Classification Multispectral
This dataset provides real multispectral images of wheat plants in field environments across South Africa, collected during August and October 2023. Captured using a specially adapted Canon EOS 800D DSLR, the images focus on early detection of Wheat Stripe Mosaic Virus, depicting plants at various stages of disease progression. The dataset contains 424 images across 2 classes: diseased, early.Images per class:
diseased: 252
early: 172… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/wheat_mosaic_classification_multispectral.pokemon_card_image_for_authenticity_classification
Pokemon Card Image for Authenticity Classification
This dataset contains front/back images of Pokemon cards for authenticity experiments.
Dataset structure
Images/: all image files (.jpeg)
Images/metadata.jsonl: metadata used by Hugging Face imagefolder
labels.csv: flat label file with the same rows as metadata
Columns
image: image object loaded from file
id: image filename (unique id)
side: card side (0 = front, 1 = back)
labels: authenticity label (1 =… See the full description on the dataset page: https://huggingface.co/datasets/stevelohwc/pokemon_card_image_for_authenticity_classification.pokemon-classification-gen1-9
Dataset Card for Pokemon Classification Gen 1 - 9
This dataset is designed for classifying Pokémon based on their images. All images are 256px x 256px and have metadata detailing each Pokémon's generation, types, and key statistics such as HP, Attack, Defense, Special Attack, Special Defense, and Speed. Additionally, the dataset features labeled images of shiny versions of Pokémon, providing a comprehensive resource for image-based classification tasks.
Dataset Details… See the full description on the dataset page: https://huggingface.co/datasets/JJMack/pokemon-classification-gen1-9.Dhan-Shomadhan_rice_leaf_disease_classification
Dhan Shomadhan Rice Leaf Disease Classification
This dataset provides real-world RGB images of rice leaves affected by multiple disease symptoms, captured under natural agricultural conditions. It offers a practical resource for developing and evaluating computer vision models in agricultural disease detection and monitoring applications. The dataset contains 1,106 images across 8 classes: Brown Spot, Browon Spot, Leaf Scaled, Rice Blast, Rice Tungro, Rice Turgro, Shath Blight… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/Dhan-Shomadhan_rice_leaf_disease_classification.