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Show HN: Gemini can now natively embed video, so I built sub-second video search

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Show HN: Gemini can now natively embed video, so I built sub-second video search

#1
Gemini Embedding 2 can project raw video directly into a 768-dimensional vector space alongside text. No transcription, no frame captioning, no intermediate text. A query like "green car cutting me off" is directly comparable to a 30-second video clip at the vector level.

I used this to build a CLI that indexes hours of footage into ChromaDB, then searches it with natural language and auto-trims the matching clip. Demo video on the GitHub README. Indexing costs ~$2.50/hr of footage. Still-frame detection skips idle chunks, so security camera / sentry mode footage is much cheaper.

Show HN: Gemini can now natively embed video, so I built sub-second video search
github.com

Re: Show HN: Gemini can now natively embed video, so I built sub-second video search

#6
post #5

why not skip the text conversion? is it usable at all?

gemini embedding 2 converts straight video to vectors. in this case, dashcam clips don't have audio to transcribe and even if they did, it would be useless in the search

Re: Show HN: Gemini can now natively embed video, so I built sub-second video search

#9

Nice use of native video embedding. How do you handle cases where Gemini's response confidence is low? Do you have a fallback or threshold?

as of now, no threshold but that is planned in the future.

for example, for now if i search "cybertruck" in my indexed dashcam footage, i don't have any cybertrucks in my footage, so it'll return a clip of the next best match which is a big truck, but not a cybertruck

Re: Show HN: Gemini can now natively embed video, so I built sub-second video search

#10
post #8

very cool, anybody have apparent use cases for this?

dashcam and home security footage are the 2 main ones i can think of.

a bit expensive right now so it's not as practical at scale. but once the embedding model comes out of public preview, and we hopefully get a local equivalent, this will be a lot more practical.

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