Example programs for GR-MANGO
Dependencies: opencv-lib mbed-http
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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.
Overview¶
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
.
insample_select.h
#define SAMPLE_PROGRAM_NO 0
No. | Program file | Description |
---|---|---|
0 | sample_00_led_rtc_analogin.cpp | DigitalOut, InterruptIn, RTC, Timer and AnalogIn |
1 | sample_01_flash_write.cpp | FlashAPI sample |
2 | sample_02_ssif_loop_back.cpp | SSIF loop back sample |
4 | sample_04_ssif_wav_playback.cpp | SSIF wav playback sample (use USB memory or SD card) |
7 | sample_07_usb_func_serial.cpp | USBSerial (CDC) sample |
8 | sample_08_usb_func_mouse.cpp | USBMouse sample |
9 | sample_09_usb_func_keyboard.cpp | USBKeyboard sample |
10 | sample_10_usb_func_midi.cpp | USBMIDI sample |
11 | sample_11_usb_func_audio_1.cpp | USBAudio sample |
12 | sample_12_usb_func_audio_2.cpp | USBAudio and SSIF sample |
13 | sample_13_ether_http.cpp | Ether HTTP sample |
14 | sample_14_ether_https.cpp | Ether HTTPS sample |
16 | sample_16_usb_func_msd_1.cpp | USBMSD and FlashAPI sample |
17 | sample_17_usb_func_msd_2.cpp | USBMSD and FlashAPI sample advanced version |
18 | sample_18_mipi_drp_lcd.cpp | MIPI, DRP and LCD sample |
19 | sample_19_mipi_drp_diplayapp.cpp | MIPI, DRP and USBSerial (CDC) sample (use "DisplayApp") |
20 | sample_20_drp_dynamic_loading.cpp | DRP Dynamic Loading Sample |
21 | sample_21_deep_standby_alarm.cpp | Deep standby and RTC alarm sample |
22 | sample_22_hdmi_disp_ssif.cpp | HDMI output and SSIF wav playback Sample |
23 | sample_23_mipi_hdmi.cpp | HDMI output and MIPI Sample |
24 | sample_24_facedetection.cpp | HDMI output and face detection using OpenCV |
25 | sample_25_hdmi_mouse.cpp | HDMI output and Mouse Sample |
Notice
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.
- Connect the
micro USB type B terminal
to the PC using a USB cable. - You can find the
MBED
directory. - Drag & drop
xxxx.bin
to theMBED
directory. - When writing is completed, press the reset button.
When using custom bootloader
, please use xxxx_application.bin
as following.
- Connect the
USB type C terminal
to the PC using a USB cable. - Hold down
USB0
and press the reset button. - You can find the
GR-MANG
directory. - Drag & drop xxxx_application.bin to the GR-MANGO directory.
When writing is completed, press the reset button.
Attention!¶
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 rate | 115,200 |
Data | 8bit |
Parity | none |
Stop | 1bit |
Flow control | none |