This project implements an automated monitoring system for a bottle filling production line using computer vision techniques. It utilizes the YOLOv8 object detection model to identify and track bottles as they move through the production line, providing real-time analytics and performance metrics.
- Object Detection: Uses YOLOv8 to detect bottles in each frame of the video feed.
- Bottle Counting: Tracks the number of unfilled and filled bottles.
- Production Rate Calculation: Computes the number of bottles processed per second.
- Efficiency Monitoring: Calculates and displays the production line efficiency.
- Defect Detection: Simulates the detection of defective bottles (for demonstration purposes).
- Speed Control Suggestions: Provides recommendations for adjusting the production line speed based on the current processing rate.
- Visual Analytics: Displays real-time statistics and metrics on the video feed.
pip install -r requirements.txt