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Technical Report · Video & Audio Automation

Virtual Cam Python

Python/OpenCV utility that reads a video source, processes frames in real time, and publishes them to a virtual camera device via pyvirtualcam.

AUTHOR  Gaurav Verma CATEGORY  Video & Audio Automation SOURCE  https://github.com/gaurav-321/Virtual-Cam-Python DATE  Jan 2023 STATUS  published
View Source Python OpenCV Video PyVirtualCam RealTime

Abstract

A Python/OpenCV utility that reads a source video frame by frame, converts each frame to the format expected by pyvirtualcam, and publishes it as a virtual camera device in real time. The non-trivial part is the format and timing bridge between two different video APIs.

1. What This Is

Built in January 2023 to learn real-time video routing in Python. A configured source video is opened with OpenCV, each frame is transformed into the color and shape that pyvirtualcam expects, and the result is published as a virtual camera device that other applications can open as if it were a physical webcam. The loop is paced to the source frame rate rather than running as fast as the CPU allows.

2. How It Works

# Stage Input Tool Output
01 Open source Video file path OpenCV VideoCapture Frame stream
02 Init virtual cam Width, height, fps pyvirtualcam Virtual device handle
03 Frame transform BGR ndarray NumPy / OpenCV RGB ndarray, matching shape
04 Publish and pace Processed frame pyvirtualcam + timer Frame on virtual device
05 Clean exit EOF or user stop Keyboard handler Device released

3. Constraints

  • File-source only

    The reader is a video file; there is no live webcam input path. Swapping the source means rewriting the capture stage.

  • No processing pipeline

    Frames pass through with only a color and shape conversion. There is no filter or CV-operation stage between read and publish.

  • Platform-dependent backend

    pyvirtualcam wraps OS-specific virtual-camera drivers. The device name and availability are not portable across systems.

  • No mid-stream recovery

    If the source file ends or a frame read fails, the stream stops. There is no reconnect or loop-back logic.

4. Next

  1. a. Add a live webcam input path (OpenCV VideoCapture on a device index) alongside the file-based source.
  2. b. Insert a pluggable filter stage between read and publish so a single CV operation can be swapped in without touching the loop.
  3. c. Add a small argparse CLI for source path, output resolution, and target fps so the script is testable without editing constants.

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