Fruit Object Detection using YOLOv8 (Computer Vision)

Developed a computer vision model to detect and classify different types of fruits in images using YOLOv8 object detection.

The dataset was prepared and split into training and validation sets, and the model was trained using the Ultralytics YOLOv8 framework.

The system can accurately detect multiple fruits in a single image and draw bounding boxes around each detected object.

The trained model achieved strong performance with high precision, recall, and mAP scores, demonstrating effective object detection capabilities.