Comments (10)
Yes, I have seen that and it looks promising. Do you want to take a look at it ?
There is also a Gist with a sample:
https://gist.github.com/anonymous/5832a6fffb8309ac851a29874c3dbb7b
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Btw, note that face recognition seems to be better with the face_recognition
module integrated here. So the dlib.get_frontal_face_detector()
should be replaced where relevant
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I pushed a first draft on my repo, inside the align
folder, it is the GIST code reworked to separate program logic from processing logic.
It is not intended to work, but if you want to work on it, please start from there.
CC @Ganonmaster
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@Clor would love to but I can't nowadays. coming months I will be helping other issues and features though
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A better merge function is also provided
https://gist.github.com/anonymous/8f468972d6286f403318c94bc6dbe382
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The face alignment script seems to rely on PyTorch, which is not fully supported on GPU for Windows users at this time. This could be blocking if we want it to be accessible and fast for non-tech users.
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Yes and it is also heavy as hell....
I'm still investigating because if it used just for faces landmarks, face_recognition
does it pretty well also...
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Closing this issue because the referenced scripted has evolved and should not be integrated as is in the project.
I'll reopen an issue to handle the new script when I'll be more available on the project
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Hey guys @Clorr @Ganonmaster just accidentally found this :) I have recently addressed some accuracy issues and now the code should be on par (or very close) with the results reported in the paper.
Regarding support on windows, while official support will be added soon, there is already a conda package available that works fine on windows: https://anaconda.org/peterjc123/pytorch
With respect to the speed, the slowest bit is dlib face detector, however, one can replace it with almost any other face detection method.
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Hi @1adrianb , and welcome around!
Thanks for the info. Meanwhile we switched to face_detection
lib since we are just using 2D landmarks and that face_detection
was already used for face extraction.
If you think we can take advantage of any part of your work, feel free to suggest or even make a PR, we will take care of it with great pleasure!
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