Jute Leaf Disease Classification Dataset

Description

This dataset contains 900 images of jute leaves, organized into three folders: Cercospora Leaf Spot, Golden Mosaic disease, and Healthy Leaf. Each folder represents one class and can be directly used for image classification and machine learning tasks. The images were collected from real-world conditions and show clear visual differences between healthy and diseased leaves, such as spots, color changes, and mosaic patterns. This makes the dataset suitable for research in plant disease detection, computer vision, and deep learning. An official Verification and Approval Form (PDF) is included with the dataset. This document confirms the authenticity and accuracy of the data and approves its use for research and educational purposes. This dataset can be used for training, testing, and evaluating machine learning models for agricultural and plant health applications.

Steps to reproduce

Download the dataset from Mendeley Data using the provided DOI link. Extract the downloaded ZIP file to a local directory. Open the extracted folder and locate the three class directories: Cercospora Leaf Spot Golden Mosaic disease Healthy Leaf Verify that each folder contains image files in JPG or PNG format. (Optional) Review the included Verification and Approval Form (PDF) to confirm the authenticity and accuracy of the dataset. Use the folder-based labels directly to train, validate, or test image classification models using machine learning or deep learning frameworks such as TensorFlow or PyTorch.

Institutions

• Daffodil International University

  Dhaka District, Dhaka

Categories

Licence