This project implements a real-time trash detection and classification system using the YOLO (You Only Look Once) model. The system is designed to identify five categories of trash: plastic, paper, glass, metal, and cardboard. Once an object is detected and classified, the system controls a set of servomotors via an Arduino to open the corresponding chutes, ensuring that each type of trash is directed to its specific container.
- Real-Time Detection: Uses the YOLO model to detect and classify different types of trash with high accuracy and speed.
- Visual Interface: Live visualization of detections with bounding boxes and labels showing the category and confidence of detection.
- Servo Control: Serial communication with an Arduino to control servomotors that open chutes based on the detected type of trash.
- Handling Multiple Detections: Implementation of a priority queue to ensure that detected objects are processed in the correct order.
- YOLO: Object detection model trained to recognize different types of trash.
- OpenCV: Library for image processing and visualization of detections.
- Python: For integrating the detection model, image processing, and hardware control.
- Arduino IDE: For programming the servo control.
The images of the dataset can be found in the following link (Roboflow Universe) https://universe.roboflow.com/j1nzo1/garbage-detection-project
