A comprehensive toolkit designed for content creators, educators, digital marketers, and video editing enthusiasts. It harnesses the power of AI and video processing through a suite of Python scripts that simplify the post-production process. This free open-source project aims to transform the way users handle video content, turning hours of editing into a task of a few command lines.
This project contains three scripts:
transcribe_from_video_XXX.py: Transcribe a videoclean_video_from_transcription.py: Zap filler words ('uh', 'um') in videos using FFMPEGsummary_chapters_blog.py: Generate a summary, video chapters and a blog post
Roadmap of future features:
- Remove or speedup (shorten) periods of "silence"
- Enhance speech by voice separation models
- Generate a supercut for a quick video snippet
- Add Audiogram / Kareoke kind of subtitles on the video
- Translate the subtitles to any language
Transcribe the video: (either AWS Transcribe API or Faster-Whisper)
$ python transcribe_from_video_XXX.py <path-to-video>The output will be a file called <video-name>.json in the same directory as the video.
Zap the filler words:
$ python clean_video_from_transcription.py <path-to-video> <path-to-transcript>The output will be a file called <video-name>-clean.mp4 in the same directory as the video.
Generate the summary, chapters and blog post:
$ python summary_chapters_blog.py --generate_summary --generate_chapters --generate_blog <path-to-transcript>Make sure to configure your AWS CLI with your credentials and region.