Apple Disease Detection 800

This dataset contains 800 annotated apple leaf and fruit images for apple disease detection using deep learning and computer vision techniques. The dataset is organized into train, validation, and test sets in YOLOv8 format. It was prepared for object detection and classification tasks related to identifying diseased and healthy apples. The images were preprocessed using auto-orientation and resized to 640×640 resolution. This dataset can be used for training, validating, and evaluating machine learning models for agricultural disease detection systems and smart farming applications. Dataset Split: Train Images: 560 Validation Images: 120 Test Images: 120 Total Images: 800