Dhan-Shomadhan

The Rice Leaf Disease Dataset is a high-quality computer vision dataset designed for AI-driven plant disease detection, precision agriculture, and crop health monitoring. It contains 1,106 labeled images of rice leaves affected by five distinct diseases, making it an essential resource for deep learning, image classification, and disease prediction models in agritech research.

Dataset Overview

• Dataset Focus: Rice leaf disease classification and crop health monitoring
• Number of Images: 1,106 high-resolution images
• Diseases Covered:
  • Brown Spot
  • Leaf Scaled
  • Rice Blast
  • Rice Tungro
  • Stealth Blight
• Institution: Daffodil International University
• Optimized Image Size: The dataset is resized for efficient processing without compromising quality

Key Features

• Comprehensive Disease Coverage: Includes five major rice leaf diseases affecting crop yield
• AI & Deep Learning Ready: Suitable for image classification, object detection, and segmentation tasks
• Optimized for Agricultural Research: Supports precision farming, disease prediction, and pest control models
• High-Quality Annotations: Well-labeled images for accurate training and validation
• Scalability: Ideal for real-time disease detection and agritech solutions

This dataset is sourced from Kaggle.