
Face Recognition Using Pytorch - timesler
https://github.com/timesler/facenet-pytorch
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briggers
I see from the MTCNN code that this repo (like all others I've seen) is still
bouncing tensors between GPU and CPU while passing between the P/R/ONets.

So many ML repos make this mistake in pre/post-processing and end up
bottlenecked on CPU.

Anyone know of an MTCNN that's been ported to run more or less fully on GPU?
(Or even that does batching instead of an image-by-image approach?)

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timesler
I'm not aware of any implementation with these features, but they are both on
the roadmap for the linked repo. Both should also be achievable. Batch
processing, in particular, will be a straight-forward change and should result
in quite a speed-up. Although it will require the input images to have the
same dimensions.

~~~
briggers
Good stuff.

In my experience inputs to MTCNN tend to be full frames, so the uniform
dimension requirement is usually met.

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cnxhk
I usually use this one:
[https://github.com/deepinsight/insightface](https://github.com/deepinsight/insightface)

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timesler
That's a good repo. It uses mxnet right? The aim of the repo in the topic was
mainly to provide a clean implementation that could slot easily into an
existing pytorch workflow.

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lorepieri
Thanks for sharing. I'm working on face recognition with homomorphic
encryption, therefore without compromising the user privacy. The bold goal is
the first privacy preserving videocamera. If you find this interesting, I
would love to chat about it.

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timesler
That sounds like a pretty interesting challenge. Happy to chat more - you can
get in touch using the contact details on github.

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s_Hogg
Where in the page is the evidence of the speed claim made in the headline for
this submission?

Edit: title has now been changed

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ldulcic
Great repo, been using it for a while now! Thank You Tim!

~~~
timesler
Awesome, and thanks for your feedback in the early days. I've made the
tracking interface much nicer as a result.

