Car Tracking with OpenCV

This simple Python script uses the OpenCV library to perform car tracking and stop sign detection in a video stream. It utilizes Haar cascades for both cars and stop sign detection.

Dependencies

• OpenCV: pip install opencv-python

Usage

1. Download the pre-trained Haar cascade XML files for vehicle and stop sign detection and place them in the "CarTracking" directory.

   • vehicle_haarcascades.xml
   • stop_sign_haarcascade.xml

2. Update the video file path in the script:

   vid = cv2.VideoCapture("video/file.mp4")

3. Run the script:

   python main.py

4. The script will display the video stream with rectangles around detected cars and stop signs.

Script Explanation

• The script initializes Haar cascade classifiers for car and stop sign detection.
• It reads frames from the specified video file and converts them to grayscale.
• Car and stop sign detection is performed using detectMultiScale method.
• Rectangles are drawn around detected cars and stop signs, and labels are added.
• The processed frames are displayed in a window named "Face Detector app."
• Press 'q' to exit the application.

Author

Abdulrahman Mendahawi

Feel free to modify and extend this script according to your requirements.