Raspberry Pi Android Things TensorFlow Machine Learning
Image Classifier Example Code DemoThis example source code are from https://github.com/androidthings . In the details of example code use external GPIO button.but we don't use it. So,we use computer keyboard instead.
This project is based on the TensorFlow Android Camera Demo TF_Classify app. The TensorFlow training was done using Google inception model and the trained data set is used to run inference and generate classification labels via TensorFlow Android Inference APIs.
Hardware
- Raspberry Pi 3 Board + 16GB SD card
- Pi camera module
- Computer keyboard
- Speaker or ear phone
- HDMI display or TFT LED display
Software
- Android Things Raspberry pi Image ( Develop Preview3 ) androidthings_rpi3_devpreview_3.zip
- Android Things TensorFlow image classifier sample-tensorflow-imageclassifier
- Android Studio 2.3
How to Run Code
First Flash Android Things image onto your Raspberry Pi SD card.Connect Raspberry Pi to your network using the TCP/IP (LAN) Cable and use adb tool.
use this command to connect Raspberry Pi
use this command to check connection and found android thing device.
Now you can run code on Android Studio.
If you have everything work correctly.
Press ENTER button on keyboard.The current image is captured from attached camera.
The captured image is shown on the screen.Also the result is spoken out on speaker.if any.
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can we implement the same for object detection api
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