This Python script is based on YOLOv5, a real-time object detection model. It supports multiple input sources including images, videos, webcams and screens. The script performs object detection using the specified YOLOv5 model, removes redundant detections, and displays the results with the option to save images or videos. Additionally, it generates a voice message to inform about object detection using gTTS (Google Text-to-Speech) and playsound. Runtime parameters, such as model, confidence thresholds, and input source, can be configured via command line arguments. This code is ideal for real-time object detection applications and can be customized according to specific project needs.
- Python 3.x
- PyTorch
- OpenCV
- YOLOv5
- roboflow
- ultralytics
- torch
- Pillow
- tensorboard
[ [YOLOv5]]https://github.com/ultralytics/yolov5
[[[ roboflow ]] ]https://roboflow.com/
*The implementation phase is where the YOLOv5 object detection model becomes a pivotal part of your real-time application, seamlessly processing and analyzing live data streams to swiftly and accurately recognize and locate objects, contributing to the application's core functionality.
If you have any questions or feedback, please contact me at [yjegham@gmail.com]