An AI-powered real-time video broadcasting system developed using Python, OpenCV, FastAPI, and PyVirtualCam. The project captures live webcam video, performs real-time frame processing using computer vision techniques, and streams the processed output as a virtual camera that can be used in applications like Zoom and Google Meet.
This project was developed to demonstrate the practical implementation of Computer Vision in real-time video processing and broadcasting systems.
The system captures live video from a webcam, processes each frame dynamically, applies background editing effects such as blur and enhancement, and then streams the modified output through a virtual camera interface.
The project mainly focuses on:
- Real-time webcam video capture
- Live frame-by-frame image processing
- Background blur and visual enhancement
- Virtual camera creation for streaming
- Integration with online meeting platforms
- Real-time broadcasting pipeline using Python
- Webcam captures live video input.
- OpenCV reads video frames continuously.
- Each frame is processed using Computer Vision techniques.
- Background effects such as blur are applied.
- FastAPI manages backend streaming operations.
- PyVirtualCam creates a virtual webcam output.
- The processed video stream is used in Zoom, Google Meet, or other broadcasting platforms.
- 🐍 Python
- 👁️ OpenCV
- ⚡ FastAPI
- 🎥 PyVirtualCam
- 🔢 NumPy
- 🌐 HTML / CSS / JavaScript
- Real-time webcam streaming
- Background blur effect
- Adjustable blur strength control
- Live video frame processing
- Virtual webcam support
- Lightweight and interactive UI
- Compatible with online meeting platforms
- Real-time broadcasting architecture
- Real-time frame processing
- Image filtering
- Background manipulation
- Video stream handling
- Frame-by-frame transformation
- Live video broadcasting
- Online meetings and conferences
- Virtual classrooms
- Content creation and streaming
- Video broadcasting systems
- AI-based webcam applications
- Real-time video enhancement systems
The system provides a user interface where users can:
- List available camera devices
- Start and stop streaming
- Select FPS settings
- Adjust blur intensity
- Apply background effects
- Stream processed video in real time
Click the preview below to watch the Real-Time Video Broadcasting System demonstration.
This project demonstrates how Computer Vision can be integrated with real-time video broadcasting systems to create interactive and intelligent webcam applications. By combining OpenCV, FastAPI, and PyVirtualCam, the system successfully performs live video processing and virtual camera streaming for modern communication platforms.