Project Description

I have all my photos on a private NAS running nextcloud.

This NAS has an ARM CPU and 1GB of RAM, which means I cannot run the face recognition plugin because it requires a GPU, 2 GB of RAM, and PDLib is not available for this arch (I know I could build it and package it ... but doesn't sound fun ;) )

However, I have a Coral TPU connected to a USB port (Thanks to my super friend Marc!):

https://coral.ai/products/accelerator

Where I could run Tensorflow Lite... you see where this is going, don't you?

Goal for this Hackweek

The goal is to run face recognition on the Coral TPU using tensorflow lite and then using the nextcloud API to tag the images.

Resources

Looking for hackers with the skills:

ml ai nextcloud

This project is part of:

Hack Week 20

Activity

  • over 3 years ago: stefannica liked this project.
  • over 3 years ago: vliaskovitis liked this project.
  • over 3 years ago: jordimassaguerpla left this project.
  • over 3 years ago: XGWang0 liked this project.
  • over 3 years ago: ories liked this project.
  • over 3 years ago: jordimassaguerpla started this project.
  • over 3 years ago: mbrugger liked this project.
  • over 3 years ago: jordimassaguerpla added keyword "ml" to this project.
  • over 3 years ago: jordimassaguerpla added keyword "ai" to this project.
  • over 3 years ago: jordimassaguerpla added keyword "nextcloud" to this project.
  • over 3 years ago: jordimassaguerpla originated this project.

  • Comments

    • zetisno
      16 days ago by zetisno | Reply

      Users can Emoji Kitchen select two different emojis and blend them together to create a new character or avatar. For example, combining a heart emoji with a smiley face might result in a heart-eyed smiley, or blending a cat with a crying face could create a crying cat emoji.

    • Miranda23
      2 days ago by Miranda23 | Reply

      TPUs can greatly accelerate machine learning tasks, Geometry Dash Lite especially for inference tasks like face recognition. Google’s Coral USB Accelerator or Edge TPU provides hardware-accelerated inference with TensorFlow Lite models.

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