Datasets:
metadata
license: cc-by-sa-4.0
task_categories:
- image-classification
tags:
- agriculture
- plant-disease
- phytopathology
- leaf-disease
size_categories:
- 100K<n<1M
Agri-Foundation-145k: A Unified Agricultural Foundation Dataset
Dataset Summary
Agri-Foundation-145k is a large-scale, taxonomically harmonized dataset designed for pre-training agricultural foundation models. It aggregates, cleans, and normalizes data from eight major open-access repositories, resolving semantic ambiguities and removing over 50,000 duplicate images to create a robust benchmark for Domain Generalized Plant Disease Detection.
Key Features
- Size: 144,751 Images
- Classes: 215 Unified Biological Classes (Crop + Disease/Healthy)
- Sources: PlantVillage, PlantDoc, New Plant Diseases (Kaggle), Tomato Leaf (Mendeley), Cassava Leaf Disease, Wheat Leaf Disease, PlantSeg, PlantWild.
- Normalization: Mapped disparate labels (e.g., "Tomato_Blight" vs "Tomato_Early_Blight") into a single scientific taxonomy.
- Quality:
- Deduplicated: 51,323 duplicate images (cross-dataset contamination) removed via MD5 hashing.
- Merged: 128 redundant classes (e.g.,
_google,_bingscrapes) merged into 55 base biological entities, rescuing 54 classes from being underrepresented. - Verified: All images validated for file integrity.
Supported Tasks
- Pre-training: Ideal for self-supervised learning (MAE, DINO) or supervised pre-training of backbones (MobileNet, ResNet, ViT).
- Domain Adaptation: Contains both lab-controlled (PlantVillage) and "in-the-wild" (PlantDoc) images for the same classes, enabling Sim-to-Real research.
- Fine-grained Classification: Distinguishes between visually similar pathogens (e.g., Cercospora vs. Septoria).
Dataset Structure
The dataset follows the standard ImageFolder format:
data/
├── apple_black_rot/
│ ├── plantvillage_image_001.jpg
│ ├── new_plant_diseases_image_045.jpg
│ └── ...
├── tomato_early_blight/
│ └── ...
└── ...
A metadata.csv is provided containing:
filename: Image filename.label: The unified class label.source: The original dataset source (provenance).crop: The crop type.disease: The specific pathology.release_path: Path relative to the dataset root.
Construction Methodology
- Aggregation: Eight public datasets were ingested.
- Normalization: A "Fuzzy Alignment" algorithm mapped 200+ raw directory names to canonical biological entities.
- Deduplication: MD5 hashing identified and removed duplicate images caused by cross-pollination between source datasets (e.g., New Plant Diseases containing subsets of PlantVillage).
- Refinement: Classes with search-engine suffixes (e.g.,
_google,_baidu) were merged into their base classes to improve class balance. - Verification: All images were verified for file integrity.
Licensing
This dataset is a composite work.
- Original images retain the licenses of their respective source datasets (mostly CC-BY-SA 3.0 or CC-BY 4.0).
- This unified compilation and metadata are released under CC-BY-SA 4.0.
Citation
If you use this dataset, please cite:
@dataset{agri_foundation_145k,
author = {Your Name},
title = {Agri-Foundation-145k: A Unified Agricultural Foundation Dataset},
year = {2026},
publisher = {Hugging Face},
version = {1.0}
}