🍓 Strawberry Maturity Detection and Segmentation using YOLO and OpenCV

This project uses computer vision techniques to detect and segment mature and immature strawberries in images. The workflow includes creating a custom dataset, training a YOLO model, applying OpenCV filters for segmentation, and performing inference using a YOLO model exported to ONNX.

📸 Project Overview

The goal is to detect mature and immature strawberries using a trained YOLO model on a custom dataset. The project also involves applying OpenCV filters to segment and isolate strawberries from the background.

🚀 Project Workflow

• Image Annotation with VoTT to create a custom dataset.
• Training YOLO Model using Ultralytics.
• Exporting YOLO Model to ONNX for inference.
• Segmentation and Filtering with OpenCV to isolate strawberries from the background.
• Inference using ONNX Model to test detection.