
Show HN: Try running deep learning inference on Raspberry Pi - nineties
https://actcast.io
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Stammon
We don't need more proprietary machine learning devices in our homes. I'd
appreciate this so much more, if it was open source, so I can reshape it to
whatever use case I have.

There are plenty of viable business models, that give you your well earned
money and us the option to customize and understand our devices.

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zozbot123
> We don't need more proprietary machine learning devices in our homes. I'd
> appreciate this so much more, if it was open source

It doesn't seem to do anything special? You can probably run your favorite
machine learning framework on the Raspberry Pi, and it will work - albeit
using the ARM cores and NEON only. Now, machine learning and inference _using
the Raspberry Pi's GPU part_ (which is broadly documented, unlike most GPU
hardware) would be a gamechanger, if only for educational scenarios.

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coolspot
There is PlaidML[1] - a cross-platform deep learning framework that works,
among others, on Raspberry Pi's GPU.

[1] - [https://github.com/plaidml/plaidml](https://github.com/plaidml/plaidml)

Edit: they don't support RPI GPU yet -
[https://github.com/plaidml/plaidml/issues/141](https://github.com/plaidml/plaidml/issues/141)

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moconnor
You can run TensorFlow Lite on a Pi with no problems at all. You can even
train and run basic gesture recognition with full TensorFlow on a Pi.

Source: wrote a tutorial doing this for Arm ([https://github.com/ARM-
software/ML-examples/blob/master/mult...](https://github.com/ARM-software/ML-
examples/blob/master/multi-gesture-recognition/README.md))

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contingencies
There are gesture recognition sensors available that don't even need a general
purpose CPU, eg. Broadcom APDS-9960.
[https://cdn.sparkfun.com/datasheets/Sensors/Proximity/apds99...](https://cdn.sparkfun.com/datasheets/Sensors/Proximity/apds9960.pdf)

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ngcc_hk
Security major issue for edge computing. Also I guess as it is isolated you
assume it will be hacked and then handle the risk as well.

Non-open source? would it make it harder to deal with security and deal with
as we do not know it is hacked or not.

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nineties
Blog article about this release:
[https://blog.idein.jp/post/181016515935/alphareleaseen](https://blog.idein.jp/post/181016515935/alphareleaseen)

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metildaa
Why would I use this rather than Snips? Edge computing is great, but in a
closed source, hard to audit form it will be a tough sell to get 3rd party
developers onboard.

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kankroc
Since this is about computing at the edge, I was wondering if anyone had an
opinion on the intel neural compute stick 2?

I got one recently and I am not convinced, but I suppose someone on HN might
have legitimate use cases.

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tanujt
I think the NCS2 has potential.. it's still early though. One thing on their
roadmap is to support ARM, which I view as a must-have for low powered edge
applications. Right now it only works with OpenVINO and certain x86 systems.
So I view the real use cases coming when it can be used in settings with
limited power (and limited or variable network connectivity).

