Bangladesh Bean Leaf and Pod Disease Image Dataset for Multi-Class Classification

This dataset presents a comprehensive collection of bean leaf and bean pod images gathered from real agricultural fields located in Bogura (B Block), Mymensingh (Ishwarganj), and Netrokona, Bangladesh. The dataset includes both healthy samples and disease-affected specimens representing several important diseases that commonly impact bean production.

All images were captured under natural field conditions using smartphone cameras, preserving variations in lighting, background complexity, viewing angles, disease severity, and plant growth stages. Such diversity enhances the dataset's ability to reflect real-world agricultural environments and improves its suitability for developing robust artificial intelligence solutions.

The dataset is designed to support research in plant disease recognition, computer vision, machine learning, deep learning, precision agriculture, and intelligent crop monitoring systems. It can be utilized for tasks such as disease classification, object detection, image segmentation, transfer learning, and automated decision-support systems for sustainable agriculture.

By providing field-collected and carefully organized images of both bean leaves and bean pods, this dataset serves as a valuable resource for researchers, students, and agricultural technology developers working on automated plant disease diagnosis and smart farming applications.