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Show HN: Offline Object Detection and Tracking on a Raspberry Pi

106 points by bko 9y ago

dividuum 9y ago
Is there a more self-contained way of running trained models on devices like the Pi? Almost all tutorials I've come across always require me to install a lot of Python dependencies. I'd love to have classifiers installed as a single binary somewhere. I guess https://pjreddie.com/darknet/yolo/ https://pjreddie.com/darknet/yolo/ is pretty close to that and I would imagine with a custom build wrapper around https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/makefile https://github.com/tensorflow/tensorflow/tree/master/tensorf..., the same could be achieved. Any hints?
- zok3102 9y ago
  Not exactly a single binary, but Flogo - https://github.com/TIBCOSoftware/flogo https://github.com/TIBCOSoftware/flogo uses one binary + one .so for TF inferencing. See https://tibcosoftware.github.io/flogo/development/flows/tensorflow/inferencing-tf/ https://tibcosoftware.github.io/flogo/development/flows/tens... for some basic documentation. We’re looking to grow this further with a model serving service so that its more controlled and better abstracted from processing logic - A/B, champion/challenger, etc. Core devs hang out on gitter in case you have qns or feedback.
- deleted 9y ago
  [deleted]
- sarthakjain 9y ago
  This has a way to do it without installing anything https://medium.com/nanonets/how-to-easily-detect-objects-with-deep-learning-on-raspberrypi-225f29635c74 https://medium.com/nanonets/how-to-easily-detect-objects-wit...
- Maybestring 9y ago
  You could use tensorflow.js, not self-contained, but it only depends on the browser. And... Is it easy to get openCL working on a Pi? WebGL might be slower, but it ought to just work.
IloveHN84 9y ago
Why python and not c++?
- icebraining 9y ago
  Why C++ and not Python?
deleted 9y ago
[deleted]
ythn 9y ago
Why not just install all the python 3 dependencies to a docker image and then run the docker container on the pi?
- bko 9y ago
  This was actually my original approach. I meant to mention that. And I got it to work but then I had to figure out how to control the hardware from the pi and I just gave up. To be fair, I didn't try too hard. I'm sure there is a way to communicate with peripherals through
  - brittohalloran 9y ago
    Did you look at Resin OS at all (resin.io)? No affiliation. Ship a container to your Pi that you can develop on your laptop and then have built for the ARM architecture on Resin's server. It looked very good last fall when I was toying around with Pi video but never pursued it.
  - joshvm 9y ago
    Another option would be to make a minimal install and then just clone the SD card. It's less neat than Docker, but if you're provisioning a new Pi then you still need to install Docker on it in the first place. Or use something like Ansible to do the setup automatically? Hardware control on the Pi is pretty simple, use the WiringPi library. I guess you'd need to run Docker in privileged mode, but it should work from within a container?
- icebraining 9y ago
  Since the Pi is ARM, you'd need to get pip to cross-compile any native extensions in the Python libraries (or use a pre-compiled wheel, if available).
MarkMMullin 9y ago
You want to proceed carefully with a Pi Zero - the chip is an ARMv6, so you'll end up building more things and you loose some optimization - you might not like the performance :-(

106 points by bko 9y ago

Is there a more self-contained way of running trained models on devices like the Pi? Almost all tutorials I've come across always require me to install a lot of Python dependencies. I'd love to have classifiers installed as a single binary somewhere. I guess https://pjreddie.com/darknet/yolo/ https://pjreddie.com/darknet/yolo/ is pretty close to that and I would imagine with a custom build wrapper around https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/makefile https://github.com/tensorflow/tensorflow/tree/master/tensorf..., the same could be achieved. Any hints?

zok3102 9y ago
Not exactly a single binary, but Flogo - https://github.com/TIBCOSoftware/flogo https://github.com/TIBCOSoftware/flogo uses one binary + one .so for TF inferencing. See https://tibcosoftware.github.io/flogo/development/flows/tensorflow/inferencing-tf/ https://tibcosoftware.github.io/flogo/development/flows/tens... for some basic documentation. We’re looking to grow this further with a model serving service so that its more controlled and better abstracted from processing logic - A/B, champion/challenger, etc. Core devs hang out on gitter in case you have qns or feedback.
deleted 9y ago
[deleted]
sarthakjain 9y ago
This has a way to do it without installing anything https://medium.com/nanonets/how-to-easily-detect-objects-with-deep-learning-on-raspberrypi-225f29635c74 https://medium.com/nanonets/how-to-easily-detect-objects-wit...
Maybestring 9y ago
You could use tensorflow.js, not self-contained, but it only depends on the browser. And... Is it easy to get openCL working on a Pi? WebGL might be slower, but it ought to just work.

IloveHN84 9y ago

Why python and not c++?

icebraining 9y ago
Why C++ and not Python?

deleted 9y ago

[deleted]

ythn 9y ago

Why not just install all the python 3 dependencies to a docker image and then run the docker container on the pi?

bko 9y ago
This was actually my original approach. I meant to mention that. And I got it to work but then I had to figure out how to control the hardware from the pi and I just gave up. To be fair, I didn't try too hard. I'm sure there is a way to communicate with peripherals through
- brittohalloran 9y ago
  Did you look at Resin OS at all (resin.io)? No affiliation. Ship a container to your Pi that you can develop on your laptop and then have built for the ARM architecture on Resin's server. It looked very good last fall when I was toying around with Pi video but never pursued it.
- joshvm 9y ago
  Another option would be to make a minimal install and then just clone the SD card. It's less neat than Docker, but if you're provisioning a new Pi then you still need to install Docker on it in the first place. Or use something like Ansible to do the setup automatically? Hardware control on the Pi is pretty simple, use the WiringPi library. I guess you'd need to run Docker in privileged mode, but it should work from within a container?
icebraining 9y ago
Since the Pi is ARM, you'd need to get pip to cross-compile any native extensions in the Python libraries (or use a pre-compiled wheel, if available).

MarkMMullin 9y ago

You want to proceed carefully with a Pi Zero - the chip is an ARMv6, so you'll end up building more things and you loose some optimization - you might not like the performance :-(