In this example, you will see how TensorFlow Lite is used to detect human's presence.
For more information: https://www.amebaiot.com/en/amebad-arduino-audio-tensorflow-detection/
Using TensorFlow Lite to determine human's presence
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In this example, you will see how TensorFlow Lite is used to detect human's presence.
For more information: https://www.amebaiot.com/en/amebad-arduino-audio-tensorflow-detection/
Code Reference
More information on TensorFlow Lite for Microcontrollers can be found at: https://www.tensorflow.org/lite/microcontrollers
AMB21 / AMB22 Wiring Diagram:
Connect the camera and LEDs to the RTL8722 board following the diagram.
AMB23:
BW16:
BW16 type C:
Download the Ameba customized version of TensorFlow Lite for Microcontrollers library at https://github.com/ambiot/ambd_arduino/tree/master/Arduino_zip_libraries.
Follow the instructions at https://docs.arduino.cc/software/ide-v1/tutorials/installing-libraries to install it.
Ensure that the patch files found at https://github.com/ambiot/ambd_arduino/tree/master/Ameba_misc/ are also installed.
You will also need to install the Ameba_ArduCAM library, found together with the TensorFlow Lite library.
In the Arduino IDE library manager, install the JPEGDecoder library. This example has been tested with version 1.8.0 of the JPEGDecoder library.
Once the library has installed, you will need to configure it to disable some optional components that are not compatible with the RTL8722DM. Open the following file:
Arduino/libraries/JPEGDecoder/src/User_Config.h
Make sure that both #define LOAD_SD_LIBRARY and #define LOAD_SDFAT_LIBRARY are commented out, as shown in this excerpt from the file:
//#define LOAD_SD_LIBRARY // Default SD Card library
//#define LOAD_SDFAT_LIBRARY // Use SdFat library instead, so SD Card SPI can be bit bashed
Open the example, “Files” -> “Examples” -> “TensorFlowLite_Ameba” -> “person_detection”.
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