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Claude-real-video - any LLM can watch a video

89 pointsby cortexosmainyesterday at 7:10 PM28 commentsview on HN

Comments

fzysingularityyesterday at 11:43 PM

Pretty terribly expensive way to watch a video with Claude.

Use Gemini or some local VLM to do this way more efficiently. We spent quite a bit of time on video understanding, and Claude will just burn tokens.

Check out this library: https://vlm-run.github.io/mm/

You can swap models and try out different encoding methods for videos (https://vlm-run.github.io/mm/encoders/#video)

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bonoboTPyesterday at 10:23 PM

"Where the video goes: stays on your machine" - No, the frames (that this tool extracts) obviously get sent to Anthropic if you use Claude.

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nickpetersontoday at 1:13 AM

I’m currently punishing Fable by making it watch the entire series of 7th Heaven.

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zitterbewegungyesterday at 10:54 PM

This looks cool but this should be renamed without having Claude in the name.

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Lerctoday at 12:40 AM

Are models any good at descerning motion from multiple frames?

For instance if I gave models multiple animations of a bouncing ball as individual frames. Would they be able to tell which bounce was the more realistic motion.

(Is this a potential new benchmark? maybe also variations of stair dismount)

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ElijahLynnyesterday at 9:37 PM

I was just thinking about this exact use case yesterday:

And it's for me measuring different charged speeds at different starting battery capacities and different temperatures and I was like well. What if I just had a video camera pointing at the voltage going in and out and then I could see the battery percentage increase and I can have a temperature gun pointed at the phone as well. And I couldn't know what temperature of the phone is as well and it could just figure it all out create charts..

This would make reviewing different charging equipment really easy as long as you really have to do is plug it in and tell other people to do the same thing and take a video of it and beat it to the system.

I might very well give this a try!

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gvkhnayesterday at 9:31 PM

Nice @OP i put together something similar as well. Incidentally I found for motion design specifically llm is not able to infer specific animations as well as it just being described very plainly and accurately what is happening and the timing.

One thing which sort of worked decently was actually take the frames and put them into a grid and have the agent look at the image of all of the frames together. It did surprisingly well but missed a lot of subtle details that it couldn’t see.

Also tried various kinds of vision embeddings, heat map of motion etc, and blur etc to show motion. But none really worked as well so I ended up just describing it until it got it. Haven’t quite found the right solution yet.

nickvectoday at 12:55 AM

Curious as to how many tokens are used per second of video.

octemberyesterday at 10:28 PM

Cool idea, but keyframes are not videos. Motion, object permanence, are not things Claude can infer from a set of images. Nice demo though!

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BeetleByesterday at 9:57 PM

I think this is much more useful than just LLM related applications. I'd suggest renaming it to not make it seem like it's LLM related.

fred123123yesterday at 9:44 PM

How do you handle things like scrolling quickly in a video?

nxtfariyesterday at 10:06 PM

this is really clever, props

cortexosmainyesterday at 7:10 PM

Hi HN! I built this because I was frustrated that no LLM actually "sees" a video — Claude won't accept video files, ChatGPT reads the transcript only, and Gemini samples at a fixed 1fps (missing fast cuts, over-sampling static slides).

claude-real-video takes a URL or local file and:

1. Extracts frames at every scene change (not fixed intervals) + a density floor 2. Deduplicates with a sliding-window pixel-diff algorithm (so A-B-A interview cutaways don't re-send the same shot) 3. Transcribes audio (prefers embedded subtitles, falls back to Whisper) 4. Optionally keeps the full soundtrack for audio-capable models 5. Writes a clean MANIFEST.txt you can drop into any LLM chat

A 10-min presentation goes from ~600 fixed-interval frames to 5-15 meaningful keyframes. 90%+ token savings with better comprehension.

The dedup approach (v0.2.0) uses real pixel difference on 16x16 RGB thumbnails against a sliding window of the last N kept frames — inspired by videostil's pixelmatch, but simpler and self-contained.

`--report` generates a self-contained HTML showing every keep/drop decision with diff percentages, so you can tune the threshold visually.

pip install claude-real-video && crv "https://youtube.com/watch?v=..." --report

MIT licensed, pure Python + ffmpeg. Happy to answer questions!

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