Local FFmpeg compressor for video, audio, and image files.
FFmpeg is powerful, but its command-line workflow is often too technical for everyday use. This project packages common compression tasks into a browser-based, preset-driven workflow for local use on Windows.
- Open the GitHub release page and download an asset.
- Use
FFMPEG.zipif you want the packaged version, orFFMPEG.exedirectly. - Extract the zip if needed.
- Choose a media type, select a preset, and start compression.
This project provides:
- a browser-based UI
- a Python backend
- FFmpeg/FFprobe subprocess execution
- preset-based compression workflows
- Install Python dependencies from
requirements.txt - Make sure
ffmpeg.exeandffprobe.exeare available - Start the app with
start.bat,start.ps1, orpython app.py
If you want to force the Python app even when the packaged EXE exists, run:
.\start.ps1 -ForcePythonstart.bat is a lightweight launcher that hands off to start.ps1 so Windows users can double-click it safely.
- Built-in presets live in
presets/ - User presets and runtime logs are treated as local data
temp/,dist/,build/, and generated logs are not tracked
The repository includes a GitHub Actions workflow that builds the Windows EXE and publishes it as a release asset when a release/** branch is pushed.
Current release branch:
release/exe-latest
Download from:
Published assets:
FFMPEG.exeFFMPEG.zip
How to use the release:
- Open the release page
- Download
FFMPEG.zipif you want the packaged file, orFFMPEG.exedirectly - Extract the zip if needed
- Run the EXE on Windows
To rebuild locally, run:
.\build_exe.ps1To publish a GitHub Release with gh, run:
.\publish_release.ps1`
## Acknowledgments
This project uses FFmpeg and related libraries and tools provided by their respective authors and maintainers. I would like to express my gratitude to everyone who created and maintains the libraries and packaging tools used here.
This application was developed with the assistance of AI. The source code, release workflow, and publication process were prepared and published with AI support, and this is disclosed here transparently to avoid misunderstanding about how it was created.