The project focuses on developing an AI-based system for fruit detection and counting in agricultural settings. It utilizes the YOLOv8 object detection model, to accurately identify and count fruits in real-time. The system aims to enhance precision agriculture practices by providing farmers with efficient tools for yield estimation and management.
Bot:
Circuit Diagram:
Object Detection Architecture:
Train the model using training.ipynb or just use the model.tf from this repo.
Add the model path into App.py and voila you can see a GUI.
You can see the ppt inside the
dataset & training
You can see the demo of this here:
