RoadGuard: Real-Time Accident and Speed Detection System

This project is a real-time accident and speed detection system using computer vision and deep learning. The system detects accidents in video footage and sends an email alert with an attached image of the detected accident.

Youtube Video Link

Table of Contents

• Installation
• Usage
• Features
• Configuration
• Contributing
• License

Installation

1. Clone the repository:

   git clone /~https://github.com/Ammar-Ali234/Car-Accident-Detection.git
   cd Car_Accident

2. Install the required packages (paste the following into your terminal):

   pip install ultralytics google-smtp

Usage

1. Place your video file in the project directory and update the cap = cv2.VideoCapture(r"your_video.mp4") line in the code with your video file path.

2. Update the sender_email, receiver_email, and password variables with your email credentials.

3. Run the script:

   python final.py

Features

• Real-time accident detection using YOLO model.
• Sends email alerts with an attached image of the detected accident.
• Configurable cooldown period to prevent multiple email alerts for the same accident.

Configuration

• Model: The YOLO model is used for object detection. Update the model path if necessary.

  model = YOLO(r"best (1).pt")

• Classes: The classes for detection are read from a text file.

  df = open(r"coco1.txt", "r")
  classes = df.read().split("\n")

• Email Configuration: Update the email credentials and settings.

  sender_email = "your_email@gmail.com"
  receiver_email = "receiver_email@gmail.com"
  password = "your_email_password"

Contributing

Contributions are welcome! Please open an issue or submit a pull request for any improvements or bug fixes.

If You need any help do contact me on linkedin (link is in my about section)

License

This project is licensed under the MIT License. See the LICENSE file for details.