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AIY Vision Kit - Embedded ML for STEM and Makers (GDG Boston Tensorflow)


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I introduced Google's AIY Vision Kit at the Google Developers Group Boston Taking the Temperature of Tensorflow meetup. Google’s “AI Yourself” Vision Kit, now available at Target Stores, is a low-cost ($90), developer friendly development kit designed to make machine learning tangible for makers and STEM students. It includes pre-trained models for detecting mood, pets, meals, with the ability to load your own custom model.

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AIY Vision Kit - Embedded ML for STEM and Makers (GDG Boston Tensorflow)

  2. 2. Product Consultant A blog for WebRTC developers @webrtcHacks WebRTC events & videos @webrtclive AboutMe @chadwallacehart
  3. 3. WhatistheAIY VisionKit? 5/1/2018 A tiny box that let’s you do “AI Yourself” from Google. This kit is focused on Computer Vision based on Tensorflow. No internet connection is required.
  4. 4. WhatistheAIY VisionKit? 5/1/2018 You need to assemble the kit yourself. It takes 30 to 60 minutes.
  5. 5. JoyDetection Demo 5/1/2018 The joy detection demo loads by default. It does face detection and estimates your “Joy” score if you are smiling or frowning. The default demo will illuminate the LED button according to the average score it sees across all faces.
  6. 6. How doyouget one? 5/1/2018 The new, 1.1 version is available for sale at Target stores.
  7. 7. The Kit AIY Voice Kit
  8. 8. What’sinthe box? 5/1/2018 The new, 1.1 contains everything needed for operation except a USB power supply.
  9. 9. RaspberryPiZeroWH 5/1/2018 It runs on a tiny Raspberry Pi Zero. GPIO headers are required and WiFi is handy, so the kit ships with the WH version of the Pi Zero.
  10. 10. PiCamera 5/1/2018 And it includes the latest Pi Camera.
  11. 11. VisionBonnet 5/1/2018 All of the kit’s magic is performed on the Vision Bonnet – an add on board.
  12. 12. IntelMovidius MA2450 Vision Processing Unit 5/1/2018 The most important piece of hardware is the intel Movidius VPU chip. This is a specialized chip designed for running machine learning graphs at low power. You can also buy this check as part of a USB dongle from Intel (Intel NCS) for use with Intel’s SDK. The AIY Kit team built their own SDK and optimized it to work with Tensorflow.
  13. 13. Othergoodies wewon’ttalk abouttoday  Button with multi-color LED  Privacy LED  Buzzer  Micro controller chip on Bonnet with extra GPIO pins, LEDs, and button 5/1/2018 The kit comes with lots of other interfaces and hardware options
  14. 14. Development AIY Voice Kit
  15. 15. Models Face / Joy detector Bounding box Joy score Dog / Cat / Human Detector Object class Confidence score Bounding box Dish Classifier Food object Confidence score Image Classifier / Google Image Classifier Image classifier (1000 classes?) Confidence score Nature Explorer Image classification of 4,080 different species 5/1/2018 cwh.consultingGoogle maintains several computer vision (CV) models that can be loaded on to the kit. Several of these were recently added and hopefully more will come soon.
  16. 16. Process 1. Develop the model 2. Train 3. Freeze graph & compile 4. Deploy 5/1/2018 cwh.consultingModels need to be trained outside of the kit. Then they can be compiled for the AIY Vision Kit and deployed there.
  17. 17. Custommodels  Tensorflow Model Compiler  Only works on x86 64 Ubuntu  Lots of limitations on the model – specific operators and configuration require Build your own Retrain an existing model 5/1/2018 ./bonnet_model_compiler.par -- frozen_graph_path=cat_detector_interference_graph_aiy/frozen_inference_graph.p b --output_graph_path=cat_detector.binaryproto --input_tensor_name="input" --output_tensor_names="concat,concat_1" --input_tensor_size=160 --debug There are caveats compiling to the AIY Vision Kit. I have not been able to get this to work (or seen someone else do this), but I think we are very close – see
  18. 18. Demos AIY Vision Kit 5/1/2018 Cat detection using the built in cat/dog/human detector: Face detection:
  19. 19. What does it all mean? 2 things… 5/1/2018
  20. 20. 5/1/2018 Cloud Edge 1. Applying Machine Learning at the edge – not just the cloud
  21. 21. Cloudvs.Edge Privacy Latency Power Costs considerations 5/1/2018 cwh.consultingThere are several reasons why you might not want to push your machine learning to the cloud
  22. 22. EdgeML Examples of Computer Vision on the Movidius 5/1/2018 Here are some real products that use the Movidius chip for running machine learning on-device
  23. 23. STEM 5/1/2018
  24. 24. STEM 5/1/2018 2. The kit is designed to expose high-schoolers to using AI technologies, not for PhD’s Google is trying to make ML tangible for a large audience.
  25. 25. AIYLinks    5/1/2018
  26. 26. Contact @chadwallacehart 5/1/2018