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I indexed 669 GB of my GoPro videos using my M1 Max computer and local ML models

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21–30 of 129 posts

Re: I indexed 669 GB of my GoPro videos using my M1 Max computer and local ML models

#22

I was surprised to learn that the M1 Max CPU is an ARM/SoC, comparable to an 11th gen Intel i9 Do I have it right? Would Windows ARM performance be similar for those cpu? ref: https://www.cpubenchmark.net/compare/4585vs4245/Apple-M1-Max...

“Comparable” is maybe true if we are talking about single core performance, but for memory bandwidth, the M1 Max is about 8 times faster. Wider bus, lower latency, not even close.

Re: I indexed 669 GB of my GoPro videos using my M1 Max computer and local ML models

#24

I was surprised to learn that the M1 Max CPU is an ARM/SoC, comparable to an 11th gen Intel i9 Do I have it right? Would Windows ARM performance be similar for those cpu? ref: https://www.cpubenchmark.net/compare/4585vs4245/Apple-M1-Max...

To your question, I can’t deny or confirm that because I didn’t tried it this project over a Windows machine yet or a machine with this config

Re: I indexed 669 GB of my GoPro videos using my M1 Max computer and local ML models

#25
post #23

DaVinci 21 has indexing built-in (AI IntelliSearch). Not to diminish the work you did, but this is now available to many users (probably only Studio users since it has AI in the name)

Yes, I didn’t look at it. But does it upload your videos to the cloud or process them locally? And does it allow to provide custom faces data to help labeling faces in your videos ?

I think Adobe premiere pro have it as well but cloud processed

Re: I indexed 669 GB of my GoPro videos using my M1 Max computer and local ML models

#27
post #15

it is possible to use apple gpu with containers. either with podman + runkit + recent mesa or with recent vllm-metal from docker https://www.docker.com/blog/docker-model-runner-vllm-metal-m...

I was looking for a solution for this issue of running docker containers over MPS and utilizing their GPU power. I think this project will be the solution for it, I’ll try it very soon and add support for it. Thank you, much appreciated

Re: I indexed 669 GB of my GoPro videos using my M1 Max computer and local ML models

#28
Funny this is almost EXACTLY what I did a few days ago on the same machine using very similar techniques and was on the front-page of HN as well:

https://news.ycombinator.com/item?id=48222733 https://blog.simbastack.com/indexed-a-year-of-video-locally/

I wasn't familiar with your project though, interesting stuff.

I'm trying to add more photography related features to Framedex but yeah there's so much we can do locally, exciting times.

Re: I indexed 669 GB of my GoPro videos using my M1 Max computer and local ML models

#30
post #17

Grab frames, lower res, classify, combine meta data. Write to sql

Not really. Grab frames, lower res, classify, combine metadata, transcribe the audio, convert those data (text, visual and audio) to embedding, save them over a vector DB and SQL DB. Which helped me to do semantic search, RAG, search using a screenshot of the video to find the exact the moment in the video plus search using an audio file as well. And other features unlocked with vector DB
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