Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

TensorFlow Image Recognition on a Raspberry Pi

svds.com

Post reply on HN
Print view View original

1–10 of 31 posts

Re: TensorFlow Image Recognition on a Raspberry Pi

#2

Post by alex_hirner »

Inference times for inception-v3 on a Raspberry Pi have been benchmarked recently [1]. They weigh in at around 2s. If you remove the python layer it gets down to 500ms. However, it's not yet clear if the python overhead is the only reason for that.

Nvidia's Tegra X1 should supposedly be capable of And finally, Sam who also facilitated building TF on the Pi is about to host a 6 weeks half theory, half practice course on TF and deep learning [3] (me thinks he deserves this plug).

[1] https://github.com/samjabrahams/tensorflow-on-raspberry-pi/t...

[2] https://youtu.be/_4tzlXPQWb8?t=53m35s

[3] https://www.thisismetis.com/deep-learning-with-tensorflow

Re: TensorFlow Image Recognition on a Raspberry Pi

#3

Post by sja »

Very cool! It's good to see an example showcasing the importance of keeping a Session alive when using TensorFlow with Python on the RPi. Glad that the tensorflow-on-raspberry-pi repo was useful; let me know if you (or anyone) runs into any hitches or have any suggestions for improvement.

Re: TensorFlow Image Recognition on a Raspberry Pi

#5

Post by mrubashkin »

sja wrote: post #3

Very cool! It's good to see an example showcasing the importance of keeping a Session alive when using TensorFlow with Python on the RPi. Glad that the tensorflow-on-raspberry-pi repo was useful; let me know if you (or anyone) runs into any hitches or have any suggestions for improvement.

Hey Sam this is Matt, thanks for your comment and your help a few months back! And for anyone else reading this, Sam is great at getting back to filed issues about installing tensorflow on a Pi: https://github.com/samjabrahams/tensorflow-on-raspberry-pi/i...

Re: TensorFlow Image Recognition on a Raspberry Pi

#6

Post by Florin_Andrei »

mrubashkin wrote: post #5
sja wrote: post #3

Very cool! It's good to see an example showcasing the importance of keeping a Session alive when using TensorFlow with Python on the RPi. Glad that the tensorflow-on-raspberry-pi repo was useful; let me know if you (or anyone) runs into any hitches or have any suggestions for improvement.

Hey Sam this is Matt, thanks for your comment and your help a few months back! And for anyone else reading this, Sam is great at getting back to filed issues about installing tensorflow on a Pi: https://github.com/samjabrahams/tensorflow-on-raspberry-pi/i...

Yeah, I'm using Sam's TF wheel on RPi3 and it works great.

> it was not feasible to analyze every image captured image from the PiCamera using TensorFlow, due to overheating of the Raspberry Pi when 100% of the CPU was being utilized

Just put a heatsink on the CPU. It's like $1.50 ... $1.95 on Adafruit. I glue a heatsink to every RPi3 unit I build.

https://www.adafruit.com/products/3082

https://www.adafruit.com/products/3083

> it was taking too long to load the 85 MB model into memory, therefore I needed to load the classifier graph to memory

Yeah, one of the first things you learn with TF on the RPi is to daemonize it, load everything you can initially, and then just process everything in a loop. That initialization is super-slow, but after that it's fast enough. YMMV

Re: TensorFlow Image Recognition on a Raspberry Pi

#7

Post by [deleted] »

sja wrote: post #3

Very cool! It's good to see an example showcasing the importance of keeping a Session alive when using TensorFlow with Python on the RPi. Glad that the tensorflow-on-raspberry-pi repo was useful; let me know if you (or anyone) runs into any hitches or have any suggestions for improvement.

[deleted]

Re: TensorFlow Image Recognition on a Raspberry Pi

#8

Post by iaw »

alex_hirner wrote: post #2

Inference times for inception-v3 on a Raspberry Pi have been benchmarked recently [1]. They weigh in at around 2s. If you remove the python layer it gets down to 500ms. However, it's not yet clear if the python overhead is the only reason for that. Nvidia's Tegra X1 should supposedly be capable of And finally, Sam who also facilitated building TF on the Pi is about to host a 6 weeks half theory, half practice course…

If we get down to <10ms does that mean that real-time video processing becomes feasible?
Post reply on HN