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[Project] Port of the tensorflow facenet pretrained models to pytorch

Hi all, this project contains pytorch pretrained inception resnets ported from the davidsandberg/facenet github repo. Models are implemented and used according to the standard pytorch/torchvision methodology (inheritable model modules, torchvision style model zoo for downloaded/cached pretrained state dictionaries etc.). Currently, the project covers face detection using MTCNN and face recognition. MTCNN is implemented as a single stand-alone pytorch module that wraps the p-, r-, and o-net modules as well as the post-processing, making it easy to chain MTCNN and recognition resnets together in a face recognition pipeline.

The motivation for the project was the lack of a clean implementation in pytorch that provides the performance of the davidsandberg/facenet github repo. My aim was to build a project that could be easily used to add value existing pytorch projects without a great deal of effort.

Performance wise, I see similar or better inference speed on my local machine when compared to the original repo, but that one data point doesn’t say a hell of a lot. Any extra testing or feedback much appreciated.

submitted by /u/timesler
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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.