TensorFlow Lite - Person Detection
• AmebaD [ AMB23 / AMB21 / AMB22 / BW16 / AW-CU488 Thing Plus / AMB25 ] x 1
• Arducam Mini 2MP Plus OV2640 SPI Camera Module x 1
• LED x 3
AMB21 / AMB22 wiring diagram:
Connect the camera and LEDs to the RTL8722 board following the diagram.
AMB23 wiring diagram:
BW16 wiring diagram:
BW16 type C wiring diagram:
AW-CU488 Thing Plus wiring diagram:
AMB25 wiring diagram:
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:
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”.
User can define the LED pins by using any GPIO pins on the boards.
Upload the code and press the reset button on the Ameba board once the upload has completed.
Once it is running, you should see the blue LED flashing every seconds, indicating that it has finished processing an image. The red LED will light up if it determines that there is no person in the previous image captured, and the green LED will light up if it will determines that there is a person.
The inference results are also output to the Arduino IDE serial monitor, which appears as follows:
More information on TensorFlow Lite for Microcontrollers can be found at: https://www.tensorflow.org/lite/microcontrollers