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README.md

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 ## YOLOv5 Object Detection with Bird's Eye View and Tracking
 
-This project utilizes the YOLOv5 deep learning model to perform real-time object detection from images or video streams. In addition, it provides a Bird's Eye View (BEV) visualization, which offers a top-down perspective of the detected objects.
+This project utilizes the YOLOv5 deep learning model to perform real-time object detection for Advanced Driver Assistance Systems (ADAS). It provides a framework for detecting and tracking objects in the context of automotive safety and driver assistance applications. it provides a Bird's Eye View (BEV) visualization, which offers a top-down perspective of the detected objects.
 
 ![demo](demo.gif)
 
 ### Features
 
 - Real-time object detection using the YOLOv5 model.
+- Detection of various objects relevant to ADAS, such as vehicles, pedestrians, cyclists, and traffic signs.
 - Object tracking to maintain continuity and trajectory of detected objects.
 - Bird's Eye View (BEV) visualization of the detected objects in a simulated environment.
 - Customizable confidence threshold and class filtering.