Car Detection and Counter Web-App

🚗 Overview:

• Real-time car counter detection using YOLO and SORT algorithms.
• Flask web application with WebSocket for dynamic updates.

⚙️ Technical Details:

• Language Used: Python.
• Frameworks: OpenCV, YOLO, SORT.
• Web Application: Flask for hosting the video feed with real-time updates.
• Tracking Algorithm: SORT for object tracking.
• Neural Network: YOLO for object detection.
• Image Processing: NumPy, cvzone.
• Data: Pre-trained on COCO dataset for vehicle detection.

🏁 How to Run:

1. Setup Environment:

   • Install required packages: pip install -r requirements.txt.
   • Ensure correct paths for video file, YOLO weights, and graphics.
   • Use python 10 version for better experience.

2. Run the App:

   • Execute python app.py in the terminal.

3. Access the Web Interface:

   • Open your browser and go to http://127.0.0.1:5000/.

4. Start/Stop Video Feed:

   • Click "Start Video" button to initiate the video feed.
   • Click again to stop.

5. View Vehicle Count:

   • Real-time vehicle count dynamically displayed on the web page.

📝 Notes:

• Adjust detection and tracking parameters in app.py for customization.
• SORT algorithm fine-tuned for accurate tracking.
• WebSocket enables dynamic updates without refreshing.

Happy car counting! 🚦👀