darcieg/bean-disease-uganda

---

dataset_name: bean-disease-uganda annotations_creators: - expert-generated language_creators: - found task_categories: - image-classification - computer-vision task_ids: - image-classification language: - en license: mit pretty_name: Bean Disease Uganda tags: - agriculture - plant-disease - imagefolder - beans - field-data - smartphone-images - open-access

Bean Disease Uganda Dataset

This dataset contains images of bean leaves categorized into three classes: angular_leaf_spot, bean_rust, and healthy. It is intended for training and evaluating image classification models for plant disease detection.

Source

The original images were collected by the Makerere AI Lab in collaboration with the National Crops Resources Research Institute (NaCRRI). Images were taken in the field using smartphones and annotated by agricultural experts during collection.

Structure

• train/, validation/, and test/ splits
• Each split contains subfolders for the three classes
• Images are in JPEG format, 500x500 pixels

Usage

from datasets import load_dataset

# Set drop_labels=False to retain the label column
dataset = load_dataset("darcieg/bean-disease-uganda", split="train", drop_labels=False)

image = dataset[0]["image"]
label = dataset[0]["label"]

Note: The drop_labels=False flag ensures that the label column is retained when loading the dataset. Without it, only the image column will be returned.

License

MIT License (inherited from the original ibean GitHub repository)

Acknowledgments

This dataset builds on the foundational work of the Makerere AI Lab and NaCRRI. It is intended to make the data more accessible and usable via the Hugging Face Hub.

Citation

If you use this dataset, please cite:

Makerere AI Lab. "Bean disease dataset." January 2020. https://github.com/AI-Lab-Makerere/ibean/