Getting Started   |   Gears   |   Documentation   |   Installation   |   License

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🙏 We are incredibly thankful to all our sponsors for supporting the development of VidGear. If you'd like to support VidGear, please check out our GitHub Sponsors page ➶

 

Overview

VidGear provides an easy-to-use, highly extensible, thoroughly optimised Multi-Threaded + Asyncio API Framework on top of many state-of-the-art specialized libraries like OpenCV, FFmpeg, ZeroMQ, picamera2, starlette, yt_dlp, pyscreenshot, dxcam, aiortc and python-mss serving at its backend, and enable us to flexibly exploit their internal parameters and methods, while silently delivering robust error-handling and real-time performance 🔥.

If you're new to VidGear, head straight to the Getting Started ➶ section to install VidGear.

The following functional block diagram clearly depicts the generalized functioning of VidGear APIs:

 

Table of Contents

• TL;DR
• Getting Started
• Gears: What are these?
  • CamGear
  • FFGear
  • PiGear
  • VideoGear
  • ScreenGear
  • WriteGear
  • StreamGear
  • NetGear
  • WebGear
  • WebGear_RTC
  • NetGear_Async
• Contributions
• Donations and Sponsorships
• Citation

 

 

TL;DR

What is vidgear?

"VidGear is a cross-platform High-Performance Framework that provides an one-stop Video-Processing solution for building complex real-time media applications in python."

What does it do?

"VidGear can read, write, process, send & receive video files/frames/streams from/to various devices in real-time, and faster than underline libraries."

What is its purpose?

"Write Less and Accomplish More" — VidGear's Motto

"Built with simplicity in mind, VidGear lets programmers and software developers to easily integrate and perform Complex Video-Processing Tasks in their existing or newer applications without going through hefty documentation and in just a few lines of code. Beneficial for both, if you're new to programming with Python language or already a pro at it."

 

 

Getting Started

If this is your first time using VidGear, head straight to the Installation ➶ to install VidGear.

Once you have VidGear installed, Checkout its Well-Documented Function-Specific Gears ➶

Also, if you're already familiar with OpenCV library, then see Switching from OpenCV Library ➶

Or, if you're just getting started with OpenCV-Python programming, then refer this FAQ ➶

Finally, if looking for containerizing VidGear with Docker, then refer this guide ➶

 

 

Gears: What are these?

VidGear is built with multiple APIs a.k.a Gears, each with some unique functionality.

Each API is designed exclusively to handle/control/process different data-specific & device-specific video streams, network streams, and media encoders/decoders. These APIs provides the user an easy-to-use, dynamic, extensible, and exposed Multi-Threaded + Asyncio optimized internal layer above state-of-the-art libraries to work with, while silently delivering robust error-handling.

These Gears can be classified as follows:

A. Video-Capture Gears:

This is the beginning of the README. Read the rest at the original. Read the full README ↗