# abhiTronix/vidgear

A High-performance cross-platform Video Processing Python framework powerpacked with unique trailblazing features :fire:

Repository: https://github.com/abhiTronix/vidgear
Canonical: https://ross.abutalabs.com/products/vidgear
Homepage: https://abhitronix.github.io/vidgear
Language: Python
License: Apache-2.0
License Family: permissive
Topics: opencv, multithreading, python, video-processing, ffmpeg, youtube, video-stabilization, video, framework, twitch, webrtc-video, streaming, real-time, screen-capture, hls, live-streaming, dash, video-streaming, yt-dlp, picamera2
Last push: 2026-05-18T07:11:58+00:00

## Health v2 (maintenance only)
Score: 76/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 83, release rhythm 52, longevity 100
- inputs: {"age_days": 2726, "days_push": 107, "days_rel": 108, "gap_med": 186, "n_releases_24m": 2}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 3721, forks 287 (observed 2026-08-28T04:08:15.478422+00:00)

## What it is
VidGear is a high-performance, cross-platform Python framework for video processing built around multi-threaded and asynchronous pipelines. It wraps OpenCV, FFmpeg, and related tools to provide easy video reading/writing, streaming, screen capture, stabilization, and networked video transfer.

## Use cases
- read and write video files faster than opencv in python
- stream live video over network with low latency
- capture the screen in python for recording or processing
- stabilize shaky video footage programmatically
- download and process youtube or twitch streams
- stream video from a raspberry pi camera
- build a real-time video processing pipeline in python
- send video frames between machines over zmq

## When to choose
- you need a unified pythonic API over OpenCV, FFmpeg, and streaming protocols
- you need high frame-rate, multi-threaded video I/O without writing threading code yourself
- you need features like video stabilization, screen capture, or WebRTC/HLS/DASH streaming out of the box
- you target multiple platforms including Raspberry Pi cameras

## When to avoid
- you only need basic one-off video file conversion, where plain ffmpeg commands suffice
- you need deep learning video analytics models, which VidGear does not provide itself
- you work outside Python or need a GUI video editor

## Facets
- artifact type: framework
- maturity: active
- function: video-processing, streaming, computer-vision, concurrency, image-processing
- domain: media, computer-vision, cross-platform
- platform: python, cross-platform, windows
- tags: opencv, ffmpeg, multithreaded, video-stabilization, screen-capture, live-streaming, hls, webrtc, yt-dlp, raspberry-pi, asyncio, video, linux, macos

## Member repositories
- abhiTronix/vidgear (main) score 76

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:15.478422+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T18:29:19.277230+00:00, confidence not recorded.
  - readme: https://github.com/abhiTronix/vidgear (fetched 2026-08-28T04:08:15.478422+00:00, sha 683f4a934fe1)
  - homepage: https://abhitronix.github.io/vidgear (fetched 2026-08-29T09:23:57.969410+00:00, sha bb135177fe50)
  - registry_pypi: https://pypi.org/pypi/vidgear/json (fetched 2026-08-29T09:23:57.978412+00:00, sha 4d8cb4dd76be)
- Data as of 2026-08-30T08:39:29.467469+00:00.