Example programs for GR-MANGO

Dependencies:   opencv-lib mbed-http

This is a collection of sample programs that work on RZ/A2M boards. You can try Mbed OS for RZ/A2M with GR-MANGO board.


Sample program files are located under the sample_programs folder. You can try each sample program by changing the following macro in sample_select.h.


No.Program fileDescription
0sample_00_led_rtc_analogin.cppDigitalOut, InterruptIn, RTC, Timer and AnalogIn
1sample_01_flash_write.cppFlashAPI sample
2sample_02_ssif_loop_back.cppSSIF loop back sample
4sample_04_ssif_wav_playback.cppSSIF wav playback sample (use USB memory or SD card)
7sample_07_usb_func_serial.cppUSBSerial (CDC) sample
8sample_08_usb_func_mouse.cppUSBMouse sample
9sample_09_usb_func_keyboard.cppUSBKeyboard sample
10sample_10_usb_func_midi.cppUSBMIDI sample
11sample_11_usb_func_audio_1.cppUSBAudio sample
12sample_12_usb_func_audio_2.cppUSBAudio and SSIF sample
13sample_13_ether_http.cppEther HTTP sample
14sample_14_ether_https.cppEther HTTPS sample
16sample_16_usb_func_msd_1.cppUSBMSD and FlashAPI sample
17sample_17_usb_func_msd_2.cppUSBMSD and FlashAPI sample advanced version
18sample_18_mipi_drp_lcd.cppMIPI, DRP and LCD sample
19sample_19_mipi_drp_diplayapp.cppMIPI, DRP and USBSerial (CDC) sample (use "DisplayApp")
20sample_20_drp_dynamic_loading.cppDRP Dynamic Loading Sample
21sample_21_deep_standby_alarm.cppDeep standby and RTC alarm sample
22sample_22_hdmi_disp_ssif.cppHDMI output and SSIF wav playback Sample
23sample_23_mipi_hdmi.cppHDMI output and MIPI Sample
24sample_24_facedetection.cppHDMI output and face detection using OpenCV
25sample_25_hdmi_mouse.cppHDMI output and Mouse Sample


sample_24_facedetection.cpp only can be compiled with GNU Compiler Collection.

About sample_24_facedetection.cpp, this is a demonstration that can detect the face of a person without a mask. It will surround the face of a person without a mask with a red rectangle and sound alarm at the same time. To use OpenCV for face recognition, you need to prepare the followings:
・USB drive or SD card
・ Raspberry Pi Camera Module V2
・ HDMI monitor

Perform the following steps to complete face recognition sample.
1. Copy the lbpcascade_frontalface.xml to the root folder of USB drive or SD card and save it.
2. Copy the alarm.wav to the root folder of USB drive or SD card and save it.
3. Set "camera-type" value to "CAMERA_RASPBERRY_PI_832X480" in mbed_app.json

About custom boot loaders

This sample uses custom bootloader revision 5, and you can drag & drop the "xxxx_application.bin" file to write the program. Please see here for the detail.

How to write program

When using DAPLink, please use xxxx.bin as following.

  1. Connect the micro USB type B terminal to the PC using a USB cable.
  2. You can find the MBED directory.
  3. Drag & drop xxxx.bin to the MBED directory.
  4. When writing is completed, press the reset button.

When using custom bootloader, please use xxxx_application.bin as following.

  1. Connect the USB type C terminal to the PC using a USB cable.
  2. Hold down USB0 and press the reset button.
  3. You can find the GR-MANG directory.
  4. Drag & drop xxxx_application.bin to the GR-MANGO directory.

When writing is completed, press the reset button.


For the first time only, you need to write a custom bootloader using DAPLink.

Terminal setting

If you want to confirm the serial communication the terminal soft on your PC, please specify the below values. You can change the baud rate by platform.stio-baud-rate of mbed_app.json.

Baud rate115,200
Flow controlnone

unknown revision 'shortlog'