vidgear VS ffmpeg-normalize

Compare vidgear vs ffmpeg-normalize and see what are their differences.

ffmpeg-normalize

Audio Normalization for Python/ffmpeg (by slhck)
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vidgear ffmpeg-normalize
13 22
2,941 1,066
- -
0.0 8.3
14 days ago 2 months ago
Python Python
Apache License 2.0 MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

vidgear

Posts with mentions or reviews of vidgear. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-02-23.

ffmpeg-normalize

Posts with mentions or reviews of ffmpeg-normalize. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-11-05.

What are some alternatives?

When comparing vidgear and ffmpeg-normalize you can also consider the following projects:

moviepy - Video editing with Python

OpenCV - Open Source Computer Vision Library

scikit-video - Video processing routines for SciPy

SaveTube - Youtube-dl GUI Wrapper

opencv-steel-darts - Automatic scoring system for steel darts using OpenCV, a Raspberry Pi 3 Model B and two webcams.

opencv-raspberrypi - Precompiled OpenCV 4.8.0 binaries for Raspberry Pi 3 & 4

auto-editor - Auto-Editor: Effort free video editing!

twitch-stream-recorder - Record twitch streams live!

python-mss - An ultra fast cross-platform multiple screenshots module in pure Python using ctypes.

chatsen - Cross-platform Twitch Chat application with 3rd-party addon support!

pafy - Python library to download YouTube content and retrieve metadata

Single-Image-Dehazing-Python - python implementation of the paper: "Efficient Image Dehazing with Boundary Constraint and Contextual Regularization"