annotations_creators	language_creators	language	license	multilinguality	size_categories	source_datasets	task_categories	task_ids	pretty_name	dataset_info
expert-generated	expert-generated	en	mit	monolingual	1K<n<10K	original	image-classification	multi-class-image-classification	Beans	features splits download_size dataset_size name dtype image_file_path string name dtype image image name dtype labels class_label names 0 1 2 angular_leaf_spot bean_rust healthy name num_bytes num_examples train 382110 1034 name num_bytes num_examples validation 49711 133 name num_bytes num_examples test 46584 128 180024906 478405

Table of Contents

• Table of Contents
• Dataset Description
  • Dataset Summary
  • Supported Tasks and Leaderboards
  • Languages
• Dataset Structure
  • Data Instances
  • Data Fields
  • Data Splits
• Source Data
• Data Author

Dataset Description

• Repository: MLOps-essi-upc/MLOps-TeamBeans
• Paper: N/A
• Leaderboard: N/A
• Point of Contact: N/A

Dataset Summary

Beans leaf dataset with images of diseased and health leaves. Each image is 500 x 500 RGB. Dataset is balanced in terms of classes. There are 3 types of classes, 2 of them being diseased leafs and one being healthy:

• Angular Leaf Spot which is a bacterial disease caused by Pseudomonas syringae pv.lachrymans
• Bean Rust which is caused by Uromyces phaseoli typica.
• Healthy

Supported Tasks and Leaderboards

• image-classification: Based on a leaf image, the goal of this task is to predict the disease type (Angular Leaf Spot and Bean Rust), if any.

Languages

English

Dataset Structure

Data Instances

A sample from the training set is provided below:

{
    'image_file_path': '/root/.cache/huggingface/datasets/downloads/extracted/0aaa78294d4bf5114f58547e48d91b7826649919505379a167decb629aa92b0a/train/bean_rust/bean_rust_train.109.jpg',
    'image': <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=500x500 at 0x16BAA72A4A8>,
    'labels': 1
}

Data Fields

The data instances have the following fields:

• image_file_path: a string filepath to an image.
• image: A PIL.Image.Image object containing the image. Note that when accessing the image column: dataset[0]["image"] the image file is automatically decoded. Decoding of a large number of image files might take a significant amount of time. Thus it is important to first query the sample index before the "image" column, i.e. dataset[0]["image"] should always be preferred over dataset["image"][0].
• labels: an int classification label.

Class Label Mappings:

{
  "angular_leaf_spot": 0,
  "bean_rust": 1,
  "healthy": 2,
}

Data Splits

	train	validation	test
# of examples	1034	133	128

Source Data

The data has been sourced from repository at huggingface (https://huggingface.co/datasets/beans)

Data Author

@ONLINE {beansdata,
    author="Makerere AI Lab",
    title="Bean disease dataset",
    month="January",
    year="2020",
    url="https://github.com/AI-Lab-Makerere/ibean/"
}