LibreAI / Clipping / videocutterAI
// clipping · Crezy-haker/videocutterAI

videocutterAI

Web-based highlight finder that auto-generates clips from your uploads.

💎 Hidden gem★ 42 stars⑂ 10 forksMITupdated 2026-10
▦ visual — this project's README ships no embeddable screenshot,
so here's a placeholder. The guide below is complete regardless.
// project facts

Project facts

videocutterAI is an open-source clipping project by Crezy-haker (Crezy-haker/videocutterAI on GitHub). It has 42 GitHub stars and 10 forks, is released under the MIT license, and was last updated on GitHub on 3 October 2026.

GitHub stars
42
Forks
10
License
MIT
Last updated on GitHub
3 October 2026
Category
Clipping
Listing
Hidden gem — a shorter page for a lesser-known project
Official site
GitHub
// how it works

How it works

  1. Feed it a long video

    Point the tool at a recording, podcast, or stream VOD to mine for moments.

  2. AI finds the highlights

    Transcription and scene analysis surface the clips most likely to perform.

  3. Reframe for vertical

    Speaker tracking and captions reshape each clip for 9:16 feeds.

  4. Export and publish

    Render the finished shorts and post them where your audience lives.

// features

Why people love it

AI highlight detection

Finds the punchiest moments in hours of footage automatically.

Vertical reframing

Keeps the speaker centered when cropping landscape to 9:16.

Auto captions

Burns in subtitles so clips work with the sound off.

Moment scoring

Ranks candidate clips so you publish the strongest first.

Multi-platform export

Renders shorts sized for TikTok, Reels, and YouTube Shorts.

Local-first options

Many tools run fully on your machine — no uploads, no watermark.

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// run it

Run it yourself

  1. Step 1 — Clone the repo

    Download the source and move into the project folder.

    git clone https://github.com/Crezy-haker/videocutterAI.git
    cd videocutterAI
  2. Step 2 — Check the README

    Every project documents its own setup; start with install requirements.

    cat README.md | head -60
  3. Step 3 — Run it

    Follow the project’s launch command — Docker, pip, npm, or a binary release.

    # see README for the exact launch command
// use cases

What you can build

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// faq

Questions, answered

Is it free to use?

The code is open source and free. Local AI features cost nothing beyond your hardware; anything cloud-based needs your own API key.

What license is it under?

MIT licensed — you can use it commercially with attribution.

Do I need a powerful GPU?

A GPU makes transcription and generation much faster, but lighter pipelines can run on CPU with smaller models — check the README for requirements.

Where can I post the clips?

Exports are standard vertical MP4s, ready for TikTok, Instagram Reels, and YouTube Shorts.

How is this different from Opus Clip?

You own the pipeline: no per-clip credits, no watermark, and your footage never has to leave your machine.

// keep exploring

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// alternatives

Alternatives in Clipping

The most-starred other Clipping projects in the LibreAI catalogue — the realistic shortlist if videocutterAI is not the right fit.

Get videocutterAI

Free and open — grab the source, star the repo, and start creating.