ytffmpeg 1.5.1

Scripts and tools to ease the processing of videos for Social Media platforms.

ffmpeg-youtube

Python project I use to convert my videos into stuff that can be posted on YouTube, TikTok, Instagram and other social media sites.

FFMPEG is a great video editor by itself, but it's difficult to manage that incredible description library it has.

With this project, I hope to make it easier for program-oriented folks like me to have a descriptive file that converts your videos for you instead of having to remember complex filter graphs. Simply describe what you want the video to do and this app will help you in executing those changes.

This is a very context-specific application that is catered to my needs. I never expected it to become popular, but if it does, here's to all who may contribute to this project or find it useful in their own video editing process endeavours.

Usage

When recording from phone or cam, it's difficult to manage all the media and content that comes in without paying for crazy software to get it done. With this open-source product, you can simply pip3 install ffmpeg2youtube and go!

This project honours configuration defined in a system-wide configuration file in /etc/ytffmpeg/config.yml, user-specific configuration defined in ~/.config/ytffmpeg/config.yml, with the configurations merged together in that order as defined. A top-level directive .ytffmpeg in jq notation would configure how ytffmpeg operates globally, but also respects that data structure on a per-project level as well.

To create a new project, let's use this:

ytffmpeg new

This will render a new project with the following directory structure:

.
├── build/
├── readme.md
├── resources/
└── ytffmpeg.yml

You can drop your MP4 files from your devices into the ./resources/ directory.

Next, we can run

ytffmpeg refresh

to refresh the YAML file that is the configuration driving the changes we will be performing here.

This may take a moment as ffmpeg converts your MP4 format videos into MKV format under high compression as lossless as possible. This will reduce the amount of disk that is consumed by the videos recorded and saved raw from devices. Subtitles will also be automatically generated from the video files using Whisper! The system automatically detects your GPU VRAM and selects the best Whisper model that fits (preferring large-v3 for high-end GPUs).

Concurrent Processing: If you run multiple ytffmpeg instances simultaneously, they will automatically queue for GPU access using a file-based lock to prevent OOM (Out Of Memory) errors. Each instance waits its turn instead of competing for GPU resources.

You can suppress auto-subtitle generation with the --no-subtitles argument.

Once your videos have been compressed and subtitles generated for them, you will have artifacts available in the ./build/ directory as well.

INFO: See doc/configuration.md for more information about ytffmpeg.yml configuration.

You can use this:

ytffmpeg gensubs [path-to-file.mkv]

This will generate subtitles in build/path-to-file.${LANG}.srt for any video file you give this command. This is not necessary if you used ytffmpeg refresh to generate subs from a video resource. I used this to get access to the sub-generation functionality this app provided with this command and so I exposed that function to this command here. You can elect to do more with it after that.

Once your videos have been compressed and your configuration updated, you will see the YAML has been updated with the new video. If you have a preferred name for it, you should rename the file prior to running ytffmpeg refresh.

Observe that subtitles will also be generated as a result of this update. To avoid this, you can use --no-subtitles when executing ytffmpeg refresh --no-auto-subtitles and it will go a bit faster.

You can update the YAML configuration to have it execute a number of filters and stream the videos together into a final cut that can be used for social media sites and such.

The top-level videos is an array which will contain the set of video descriptions you will use to describe how you want transformations done on those videos.

To learn more about the ytffmpeg.yml file, see docs/ytffmpeg.md

Once you have your transformations written out, you can use this:

ytffmpeg build build/myvideo.mp4

This will build your video. If you omit any arguments, it'll attempt to build all videos in your project and ensure they are ready to go!

This project takes some of the rough edges off of the filter_complex argument in ffmpeg.

This started off as a simple script to try and automate some of the rough edges of my process when recording content and publishing to the platforms.

Multi-Language Subtitle Support

ytffmpeg now supports automatic translation of subtitles to multiple languages using Argos Translate!

Quick Start

1. Configure languages in your ytffmpeg.yml:

   ytffmpeg:
     language: en           # Base language for Whisper transcription
     languages:             # Translate to these languages
       - en                 # English (from Whisper)
       - es                 # Spanish (translated)
       - fr                 # French (translated)
       - de                 # German (translated)
   

2. Run refresh to generate and translate subtitles:

   ytffmpeg refresh
   

   This will:

   • Generate English subtitles using Whisper
   • Automatically translate to Spanish, French, and German
   • Preserve timing information from the original subtitles
   • Create separate SRT files for each language in build/

3. Build your video with all subtitle tracks:

ytffmpeg build

The final video will contain all subtitle tracks, properly mapped and labeled.

How Translation Works

Context-Aware Translation: The entire transcript is translated as one document to preserve meaning, intent, and context. This produces much better results than translating line-by-line.

Timing Preservation: After translation, the system intelligently splits the translated text to match the original subtitle timing, distributing words proportionally across subtitle entries.

Automatic Package Management: Argos Translate language packages are downloaded and installed automatically on first use.

Example Output

After running ytffmpeg refresh with multi-language support:

build/
├── my-video.mkv              # Processed video
├── my-video.txt              # Full English transcript
├── my-video.en.srt           # English subtitles (Whisper)
├── my-video.es.srt           # Spanish translation
├── my-video.fr.srt           # French translation
├── my-video.de.srt           # German translation
└── my-video.mp4              # Final video with all subtitle tracks

Supported Languages

Any language pair supported by Argos Translate, including:

• Spanish (es), French (fr), German (de), Portuguese (pt)
• Italian (it), Russian (ru), Chinese (zh), Japanese (ja)
• Arabic (ar), Hindi (hi), Korean (ko)
• And many more!

For detailed documentation, see CHANGES.md.

@FutureFeature

Features I'd like to add to this include:

• ytffmpeg publish to publish to your configured social media platforms -- I want to support YouTube, TikTok, and Mastadon. -- Right now, only an SFTP endpoint is supported (uses Fabric).
• Stream specifier error clarification: It would be nice to know that a stream is disconnected right there in vscode or some editor of sorts. I hope a project like this can make that more easily accesible as a potential by simulating the results of the configuration in ffmpeg's filter_complex parameter.