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Clips
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Individual clip
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Inspiration
Opening a new folder of video footage usually means spending hours scrubbing through clips to find the good takes, check audio, and write down notes. I wanted to build a tool that automates this tedious first step so editors can start actually editing right away.
What it does
Scrub acts as your automatic assistant editor. You point it at a folder of raw footage, and it automatically watches and listens to every clip. It checks for focus, exposure, and audio clipping, groups similar takes together, and creates a searchable transcript. It then grades the clips and tells you exactly why they were flagged, all happening 100% locally on your machine.
How I built it
I built Scrub using Python for the backend and Flask for the local web interface. For video and audio analysis, I used OpenCV, NumPy, and SciPy to measure technical metrics like exposure and audio levels. For transcribing the dialogue and making the footage searchable, I integrated faster-whisper for fast, offline speech-to-text processing.
Challenges I ran into
- Processing large video and audio files locally without making the user wait forever.
- Finding the right mathematical thresholds to accurately decide if a clip is "good" or "bad" based on focus and exposure.
- Figuring out how to automatically cluster different takes of the exact same shot together.
- Making the installation completely seamless so users just have to double-click a script to get started.
Accomplishments that I'm proud of
- Building a tool that runs entirely offline, ensuring complete privacy for creators and their unreleased footage.
- The take grouping feature, which puts multiple attempts at the same line side-by-side with the best one already picked.
- Creating a transparent grading system- Scrub isn't a black box; it tells you the exact numbers behind why a clip was flagged.
What I've learned
I learned a lot about audio and video signal processing, specifically how to programmatically detect things like audio clipping, silence, and camera focus. I also learned how to package local AI models (like Whisper) to run efficiently on a user's machine without a complicated setup.
What's next for Scrub
- Adding support for a wider variety of professional camera formats and codecs.
- Improving the take clustering accuracy using more advanced visual and audio similarity checks.
- Building direct plugin integrations for editing software like Premiere Pro and DaVinci Resolve so users don't even have to leave their editor to use Scrub.
