datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
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.multimodal_meme_classification_singapore
Dataset Card for Offensive Memes in Singapore Context
Dataset Details
Dataset Description
This dataset is a collection of memes from various existing datasets, online forums, and freshly scrapped contents. It contains both global-context memes and Singapore-context memes, in different splits. It has textual description and a label stating if it is offensive under Singapore society's standards.
Curated by: Cao Yuxuan, Wu Jiayang, Alistair Cheong, Theodore Lee… See the full description on the dataset page: https://huggingface.co/datasets/aliencaocao/multimodal_meme_classification_singapore.happy-whale-dolphin-classificationhagrid-classification-512p-dataset
Dataset Card for "hagrid-classification-512p-dataset"
More Information needed
vqa_plant-disease-classification-merged-datasetbruised_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.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.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.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.pose-classificationcorn_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.bus_uc_classification-ultrasound-datasetplant_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.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.hagrid-classification-512p-no-gesture-150k
Dataset Card for "hagrid-classification-512p-no-gesture-150k"
This dataset contains 153,735 training images from HaGRID (HAnd Gesture Recognition Image Dataset) modified for image classification instead of object detection. The original dataset is 716GB. I created this sample for a tutorial so readers can use the dataset in the free tiers of Google Colab and Kaggle Notebooks.
Original Authors:
Alexander Kapitanov
Andrey Makhlyarchuk
Karina Kvanchiani… See the full description on the dataset page: https://huggingface.co/datasets/cj-mills/hagrid-classification-512p-no-gesture-150k.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.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.color-classification-opensourcebirds-525-species-image-classificationOriginal dataset is https://www.kaggle.com/datasets/gpiosenka/100-bird-species
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.dfl_classification
Dataset Card for "dfl_classification"
More Information needed
Pokemon-Captioning-Classification
2000+ download monthly. Really appreciate for all of you guys:
Buy me a coffee:
https://buymeacoffee.com/tridoan
Disclaimer: This model is provided "as-is" without any warranties. The authors are not responsible for any misuse or damages arising from its use.
BrinjalFruitX_disease_classification
BrinjalFruitX Disease Classification
A dataset for disease classification of brinjal fruit (eggplant). The dataset contains 1,823 images across 5 classes: Brinjal Fruit Creaking, Healty Brinjal, Phomopsis Bright, Shoot and Fruit Borer, Wet Rot.Images per class:
Brinjal Fruit Creaking: 200
Healty Brinjal: 514
Phomopsis Bright: 161
Shoot and Fruit Borer: 725
Wet Rot: 223
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/BrinjalFruitX_disease_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.maize_disease_classification
Maize Disease Classification
A dataset for disease classification of Maize leaves. The dataset contains 9,356 images across 3 classes: Healthy, MLN, MSV.Images per class:
Healthy: 3,073
MLN: 3,231
MSV: 3,052
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
Citation
@article{mduma2024updating,
title={Updating “machine learning imagery dataset for maize crop: A case of Tanzania” with expanded data to cover the new… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/maize_disease_classification.teaLeafBD_disease_classification
Tealeafbd Disease Classification Classification
A dataset for image classification of Tealeafbd Disease Classification. The dataset contains 5,278 images across 7 classes: Brown Blight, Gray Blight, Green mirid bug, Healthy leaf, Helopeltis, Red spider, Tea algal leaf spot.
Images per class:
Brown Blight: 508
Gray Blight: 1,013
Green mirid bug: 1,282
Healthy leaf: 935
Helopeltis: 607
Red spider: 515
Tea algal leaf spot: 418
This dataset is indexed on… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/teaLeafBD_disease_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.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.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.