The viewer is disabled because this dataset repo requires arbitrary Python code execution. Please consider
removing the
loading script
and relying on
automated data support
(you can use
convert_to_parquet
from the datasets
library). If this is not possible, please
open a discussion
for direct help.
Dataset Card for Beans
Dataset Details
Dataset Description
The Beans dataset contains 1,296 images of bean plant leaves, categorized into three classes:
Healthy
Angular Leaf Spot (disease)
Bean Rust (disease)
The images were collected in Ugandan fields by the Makerere AI Lab in collaboration with the National Crops Resources Research Institute (NaCRRI). Each image was annotated during data collection by agricultural experts. The dataset is intended for plant disease classification and can be used to develop machine learning models for mobile-based agricultural diagnostics.
- License: MIT
Dataset Sources
Dataset Structure
Total images: 1,296
Classes: 3
Healthy leaves: 428 images
Angular Leaf Spot: 432 images
Bean Rust: 436 images
Image specs: JPEG format, RGB images
Example Usage
Below is a quick example of how to load this dataset via the Hugging Face Datasets library.
from datasets import load_dataset
# Load the dataset
dataset = load_dataset("randall-lab/beans", split="train", trust_remote_code=True)
# dataset = load_dataset("randall-lab/beans", split="test", trust_remote_code=True)
# dataset = load_dataset("randall-lab/beans", split="validation", trust_remote_code=True)
# Access a sample from the dataset
example = dataset[0]
image = example["image"]
label = example["label"]
image.show() # Display the image
print(f"Label: {label}")
Citation
BibTeX:
@misc{makerere2020beans, author = "{Makerere AI Lab}", title = "{Bean Disease Dataset}", year = "2020", month = "January", url = "https://github.com/AI-Lab-Makerere/ibean/" }
- Downloads last month
- 3