A Comprehensive dataset on diseases affecting rose leaves: Identification, Symptoms, and Control Strategies
Description
A Comprehensive dataset on diseases affecting rose leaves: contains 3,113 high-resolution images and 15,500 augmented images (resized to 640x480) of rose leaves, categorized by disease type to assist in identification and control strategy research. The dataset is designed for training deep learning and machine learning models and studying plant pathology, pest management, and disease prevention in rose cultivation. The images were taken from October 30 - November 6, 2024 , approximately 8 days. Total Original Images: 3,113 images Total Augmented Images: 15,500 images Resolution: Resized to 640x480 pixels Categories: Four disease classes Class 1: Black Spot Class 2: Healthy Leaf Class 3: Dry Leaf Class 4: Leaf Holes Image Count per Class: At least 300 images per category in original data Purpose: Disease detection, research in plant pathology, and development of control strategies