datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
crop-disease-balanced-5022diseasesncbi_diseaseThis paper presents the disease name and concept annotations of the NCBI disease corpus, a collection of 793 PubMed
abstracts fully annotated at the mention and concept level to serve as a research resource for the biomedical natural
language processing community. Each PubMed abstract was manually annotated by two annotators with disease mentions
and their corresponding concepts in Medical Subject Headings (MeSH®) or Online Mendelian Inheritance in Man (OMIM®).
Manual curation was performed using PubTator, which allowed the use of pre-annotations as a pre-step to manual annotations.
Fourteen annotators were randomly paired and differing annotations were discussed for reaching a consensus in two
annotation phases. In this setting, a high inter-annotator agreement was observed. Finally, all results were checked
against annotations of the rest of the corpus to assure corpus-wide consistency.
For more details, see: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3951655/
The original dataset can be downloaded from: https://www.ncbi.nlm.nih.gov/CBBresearch/Dogan/DISEASE/NCBI_corpus.zip
This dataset has been converted to CoNLL format for NER using the following tool: https://github.com/spyysalo/standoff2conll
Note: there is a duplicate document (PMID 8528200) in the original data, and the duplicate is recreated in the converted data.Agri-LLaVA_Agricultural_Pests_And_Diseases_Feature_Alignment_Dataset
Agri-LLaVA
Agri-LLaVA is a large multimodal instruction dataset for agriculture, pairing crop/leaf images with multi-turn diagnostic conversations about plant diseases, pests, and nutrient deficiencies. It is compiled from 16 public source datasets (see the license table below).
This dataset has been converted to Parquet format with image bytes embedded directly, standardized to the HF image_text_to_text format with a single conversational messages schema.
This dataset is… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/Agri-LLaVA_Agricultural_Pests_And_Diseases_Feature_Alignment_Dataset.Crop_Disease_Image_Dataset
Crop Disease Image Dataset (5 Crops, 19 Classes)
Dataset Summary
The Crop Disease Image Dataset is a curated, high-quality agricultural image dataset designed for computer vision, deep learning, and smart farming applications. It contains 22,169 RGB leaf images spanning 5 major crops across 19 distinct healthy and diseased classes.
This dataset was constructed by collecting, filtering, and standardizing images from multiple open-source agricultural repositories… See the full description on the dataset page: https://huggingface.co/datasets/ipartzix/Crop_Disease_Image_Dataset.risk-factors-verifyplant-disease-trainopus-doctor-patient-conversations-all-human-diseases
Opus-4.8-High-Thinking generated Doctor-Patient Conversations for All Human Diseases
Covers every human disease listed on my previous work here: nisten/all-human-diseases
The dataset strictly used Opus 4.8 - High and was cleaned over 3 times via Opus 4.8, 4.7 and 4.6. Minor corrections were needed upon each pass mainly to bypass single word safety filters like i.e. monkeypox.
The main hallucination noticed during generation was that Opus would make up wrong PMID ( PubMed ID )… See the full description on the dataset page: https://huggingface.co/datasets/nisten/opus-doctor-patient-conversations-all-human-diseases.BeejX-Crop-Disease-Dataset
BeejX Crop Disease Dataset
Edge-AI Data Solution for Crop Disease Recognition (Offline & Mobile-First).
Dataset Overview
The BeejX Crop Disease Dataset is an extensive, multi-crop image classification dataset curated for training lightweight Edge-AI models. The dataset is specifically structured and balanced to train models like MobileNetV2 (Quantized), enabling real-time, offline inference on low-end Android devices in rural agricultural areas.
This dataset… See the full description on the dataset page: https://huggingface.co/datasets/bf369/BeejX-Crop-Disease-Dataset.qasrisks-factorsPlant-Diseases-PlantVillage-Dataset
Dataset Card for Dataset Name
Train and Test (20%) splits for the PlantVillage-Dataset on the subject of plant disease
@article{Mohanty_Hughes_Salathé_2016,
title={Using deep learning for image-based plant disease detection},
volume={7},
DOI={10.3389/fpls.2016.01419},
journal={Frontiers in Plant Science},
author={Mohanty, Sharada P. and Hughes, David P. and Salathé, Marcel},
year={2016},
month={Sep}}
Dataset Details
Dataset Description
Curated by: [More… See the full description on the dataset page: https://huggingface.co/datasets/BrandonFors/Plant-Diseases-PlantVillage-Dataset.Crop_Disease_Images
Crop Disease Expert Annotations
1,026 expert annotations over 989 crop photographs, covering pests, diseases and nutrient deficiencies across 74 crop types. The images are included in this repository.
Every image is a photo taken by a smallholder farmer on their own plot and sent to Farmer.Chat, an AI advisory service run by Digital Green. Agronomists then reviewed each photo on Digital Green's annotation platform. Nothing here is scraped, staged, or lab-photographed.… See the full description on the dataset page: https://huggingface.co/datasets/DigiGreen/Crop_Disease_Images.rice-disease-datasetThis is the dataset for my project of Plant Diagnosis Suite at here. You can check out to see a Disease Detector trained on this dataset
Vietnamese Rice Disease & Crop Recommendation Dataset
An agricultural AI dataset collected in Vietnam, containing 37,978 rice plant images across 21 classes (diseases, pests, nutrient deficiencies, healthy) — for image classification.
Dataset Summary
Component
Type
Samples
Classes
Task
Rice Disease Images
Image (JPG)
37,978… See the full description on the dataset page: https://huggingface.co/datasets/minhhungg/rice-disease-dataset.Clinical_Documents_on_Syndromes_Diseaseidrid-disease-grading
Indian Diabetic Retinopathy Image Dataset (IDRiD)
This dataset is the disease grading portion of the IDRiD.
The original source of the dataset is here: https://ieee-dataport.org/open-access/indian-diabetic-retinopathy-image-dataset-idrid
vqa_plant-disease-classification-merged-datasetliver-disease
Liver Disease
This dataset is part of the Roboflow 100 benchmark, a diverse collection of 100 object detection datasets spanning 7 imagery domains.
Dataset Statistics
Split
Images
Train
2,782
Validation
794
Test
400
Total
3,976
Classes (4)
ballooning
fibrosis
inflammation
steatosis
Usage
With LibreYOLO
from libreyolo import LIBREYOLO
# Load a model
model = LIBREYOLO(model_path="libreyoloXnano.pt")
# Train on this… See the full description on the dataset page: https://huggingface.co/datasets/LibreYOLO/liver-disease.cassava-leaf-disease-classificationParkinsons-Disease-MRI-Datasetplant_disease_detection_processedThis Dataset is created from processing the files from this GitHub repository : PlantDoc-Object-Detection-Dataset
Citation
BibTeX:
@inproceedings{10.1145/3371158.3371196,
author = {Singh, Davinder and Jain, Naman and Jain, Pranjali and Kayal, Pratik and Kumawat, Sudhakar and Batra, Nipun},
title = {PlantDoc: A Dataset for Visual Plant Disease Detection},
year = {2020},
isbn = {9781450377386},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url =… See the full description on the dataset page: https://huggingface.co/datasets/susnato/plant_disease_detection_processed.Oral_Diseasesmmlu-winogrande-afr
Bridging the Gap: Enhancing LLM Performance for Low-Resource African Languages with New Benchmarks, Fine-Tuning, and Cultural Adjustments
Authors:
Tuka Alhanai tuka@ghamut.com, Adam Kasumovic adam.kasumovic@ghamut.com, Mohammad Ghassemi ghassemi@ghamut.com, Aven Zitzelberger aven.zitzelberger@ghamut.com, Jessica Lundin jessica.lundin@gatesfoundation.org, Guillaume Chabot-Couture Guillaume.Chabot-Couture@gatesfoundation.org
This HuggingFace Dataset contains the human-translated… See the full description on the dataset page: https://huggingface.co/datasets/Institute-Disease-Modeling/mmlu-winogrande-afr.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.ncbi_diseaseThe NCBI disease corpus is fully annotated at the mention and concept level to serve as a research
resource for the biomedical natural language processing community.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.eye_diseasedisease-list
Dataset Card for Every Cure Disease List
Dataset Summary
The Every Cure Disease List
The Every Cure disease list is a flat list with disease terms derived from the Mondo disease ontology and
enriched with various features by the Every Cure team that are relevant to drug repurposing.
For more information see here.
Source Data
Attribution
rare-disease-diagnosis
Rare Disease Diagnosis v1
Materialized task data for the deeprare-curated-phenotype/v1 agent benchmark in
T0-RSI/ai4sci-tasks.
The files preserve the materializer's host directory layout. This is a frozen
scientific case selection served from the current repository main; later Hub
commits may update packaging or documentation.
public/development/: labeled fit/tune examples for the agent.
public/verifier/: phenotype-only evaluation inputs.
public/reference/: read-only… See the full description on the dataset page: https://huggingface.co/datasets/zifeng-ai/rare-disease-diagnosis.plant-disease-dataset