Re:Show HN: Offline Object Detection and Tracking on a Raspb...
by dividuum on Wednesday May 09, 2018 @10:30AM
(#17030098)
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/ is pretty close to that and I would imagine with a custom build wrapper around https://github.com/tensorflow/tensorflow/tree/master/tensorf..., the same could be achieved. Any hints?
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Re:Show HN: Offline Object Detection and Tracking on a Raspb...
by zok3102 on Wednesday May 09, 2018 @10:50AM
(#17030254)
Not exactly a single binary, but Flogo - https://github.com/TIBCOSoftware/flogo
uses one binary + one .so for TF inferencing. See 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.
Re:Show HN: Offline Object Detection and Tracking on a Raspb...
by sarthakjain on Wednesday May 09, 2018 @02:02PM
(#17032172)
This has a way to do it without installing anything https://medium.com/nanonets/how-to-easily-detect-objects-wit...
Re:Show HN: Offline Object Detection and Tracking on a Raspb...
by Maybestring on Wednesday May 09, 2018 @02:23PM
(#17032400)
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.