
Deep belief image recognition on Raspberry Pi - liquidmetal
https://github.com/jetpacapp/DeepBeliefSDK
======
bigiain
Apart from a recent (26 day old) update to the javascript, this looks like it
got abandoned back when Google acquired Jetpac (who's website now seems
defunct). Anyone know what the status of this is? I guess there must've been
some more-recent-than_aug-2014 updates, since it mentions RaspberryPi2s...

~~~
nl
[http://petewarden.com/2015/05/10/image-recognition-on-the-
ra...](http://petewarden.com/2015/05/10/image-recognition-on-the-raspberry-
pi-2/)

[http://petewarden.com/2015/05/18/jetpacs-deep-learning-
frame...](http://petewarden.com/2015/05/18/jetpacs-deep-learning-framework-on-
the-beaglebone-black/)

[https://github.com/tensorflow/tensorflow/issues/445#event-48...](https://github.com/tensorflow/tensorflow/issues/445#event-486230566)

------
dharma1
you could also try this:

[https://github.com/teradeep/demo-apps/tree/master/generic-
em...](https://github.com/teradeep/demo-apps/tree/master/generic-embedded)

or this:

[http://mxnet.readthedocs.org/en/latest/tutorial/smart_device...](http://mxnet.readthedocs.org/en/latest/tutorial/smart_device.html)

Not really RPi related - but I think it's only a matter of time until we have
mobile GPU optimised BLAS libraries working with Mali, Adreno etc. At that
point machine learning will become more feasible on current mobile devices

------
buserror
Had had a good play with that lib earlier on debian, it's pretty cool! Very
lightweight (considering) and I tossed it a few pictures of stuff, and it's
quite impressive. I particularly liked my eBay shopping history. Didn't like
my landscape photos so much, but it's likely to be that it hasn't been trained
on any...

What would be fantastic is a way to recover some sort of rough coordinates of
what the classification have found.

~~~
dharma1
bounding box - [https://github.com/rbgirshick/py-faster-
rcnn](https://github.com/rbgirshick/py-faster-rcnn)

------
es0m
This lib is so small and self-contained that it was straightforward to port it
to Windows (Visual Studio):
[https://github.com/jetpacapp/DeepBeliefSDK/pull/62](https://github.com/jetpacapp/DeepBeliefSDK/pull/62)

I had trouble getting Caffe and Torch to run natively (i.e. MS toolchain),
anyone knows of a good Windows port for these that one can link to?

