Skynet w/ Raspberry Pi: Conclusion

This is the FINAL entry in my 8 part series on adding some object detection to my Raspberry Pi.

Part 1: Introduction
Part 2: SD Card Setup
Part 3: Pi Install
Part 4: Software
Part 5: Raspberry Pi Camera
Part 6: Installing TensorFlow
Part 7: MobileNetV2
Part 8: Conclusion

Introduction

It seems odd to have an “introduction” in my conclusion post but I like to keep the format the same (I copy the previous post to create this one!). I will just talk about some high level issues and some other topics and then wrap this whole thing up.

Issues

I guess I will start with the issues that I had during this build.

SD Card

First, I don’t use SD cards very often so that caused some issues when the hardware bit caused my card to become read only. Had I known about this “feature” I would have been able to keep my 64GB card for future projects. It would have also allowed me to not get into the 32GB limit partition limitation.

ARM

Second, while I never thought about it I really should have known that the ARM processor would cause some issues. I guess my blind trust in PIP lead me to think it could do anything including ignoring the processor.

Thankfully, the python/TF community is awesome and someone did all the hard work for me and created a TF library that would run on the Pi.

Image Detection

My final issue was with the actual image detection. This was 100% on my and not the model. With my personal life getting crazier by the day thanks to a 3 year old I didn’t do all the research I would have liked. I really should have gone through the whitepaper and see what/how the model was trained. This would allow me to get a feel for what images I should expect to detect.

Future

Conferences

My immediate goal for this project was to use it to get into a few conferences. My first conference application was for KCDC and I have yet to hear back but I am assuming I won’t get in. My second was a repeat of last year with the Twin Cities Code Camp but their deadline was February 14th at midnight and I took that as the night of the 14th and not the morning so I was 8 hours late. I don’t know if I will try and get back out to Denver again this year or not.

I decided that if I don’t get into any conferences this year I will put that part of my life on hold. The travel was interesting but with a young family it wasn’t worth going so far away. Maybe in a few years I will try and pick it back up.

Custom Training

As far as the project goes, I would like to do some custom training and see if it could pick out members of my family or something along those lines. I do have FishButler in the Google Play Store that could use some fish detection.

Conclusion

Conclusion to by conclusion post! Turtles all the way down.

Code: https://github.com/ehennis/Blog/tree/master/ImageDetection

7 thoughts on “Skynet w/ Raspberry Pi: Conclusion”

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