Awesome
Introduction
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InsightFace inference example (production ready architecture)
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Face recognition demo with insightface (visualization missing, add later)
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InsightFace training pipeline
What does this do if I know nothing about face recognitions?
This is a server, wrapping up with a frozen model, accepting a photo of face, then output a vector of 512 dimension to describe it.
It means:
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You pbbly need another pipeline before this to detect a face bounding box first
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Then you can run this project to describe this face
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Later on, it's up to your purpose, if your purpose is face alignment/detection/distinguish, you need another classifier after this to do the job
An example of this is as following, borrowed from openface:
Demo Facial Recognition App
Yes Yes Yes, I know your are lazy. So I made a demo app for you with following architecture:
How to run it
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Install Depenencies:
pip install -r requirements.txt
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Download pre-trained frozen model and put it under
pretrained
folder -
Run example:
python apps/example.py
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You shall be able to see terminal output a 512 element array representing face feature embedded
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Run demo:
python apps/demo.py
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You sahll be able to see it output the architecture described above logs
References
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Official Implementation (mxnet): deepinsight/insightface
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Third Party Implementation (tensorflow): auroua/InsightFace_TF