UnitV2 Jupyter Notebook

Preparation

• 1.Device startup and connection: Refer to the tutorial in UnitV2 Built-in Recognition Service to complete the installation of the device driver and access to the device web control page through the browser.

Jupyter Notebook

the settings button in the upper right corner->Switch to Jupyter Notebook, and refresh according to the page prompts.

Examples

LED

import time

def control_white_led(value):
    open('/sys/class/gpio/export', 'w').write('0') # Export the GPIO0
    open('/sys/class/gpio/gpio0/direction', 'w').write('out') # Set the direction of the GPIO
    open('/sys/class/gpio/gpio0/value', 'w').write(str(value)) # Set the value, '1' or '0'
    
def control_red_led(value):
    open('/sys/class/gpio/export', 'w').write('1') # Export the GPIO0
    open('/sys/class/gpio/gpio1/direction', 'w').write('out') # Set the direction of the GPIO
    open('/sys/class/gpio/gpio1/value', 'w').write(str(value)) # Set the value, '1' or '0'


for i in range(10):
    control_white_led(0)
    time.sleep(0.5)
    control_white_led(1)
    time.sleep(0.5)

Microphone

import subprocess
import audioop
import time

audio_cmd = ['arecord', '-D', 'plughw:0', '-f', 'S16_LE', '-c', '1', '-r', '48000', '-t', 'raw', '-q', '-']
audio_source = subprocess.Popen(audio_cmd, stdout=subprocess.PIPE)

while True:
    audio_source.stdout.flush()
    data = audio_source.stdout.read(512)
    rms = audioop.rms(data, 2)
    print(rms)
    time.sleep(0.1)

• Execute this command in the terminal to record audio and save it to a file

arecord -d 20 -r 48000 -c 2 -f S16_LE audio.wav

UART

import serial

# Open the serial port, and set the baudrate to 115200
uart_grove = serial.Serial('/dev/ttyS1', 115200, timeout=0.5)

# Send Something
uart_grove.write('hello'.encode('utf-8')) 
# encode is for converting the string to bytes, or you can directly send bytes
uart_grove.write(b'hello') 


# Receive something
x = uart_grove.read()          # read one byte
s = uart_grove.read(10)        # read up to ten bytes (timeout)
line = uart_grove.readline()   # read a '/n' terminated line

Camera

The built-in camera of the M5Stack UnitV2 is located at /dev/video0. You can try to capture a static image frame.

import cv2

camera = cv2.VideoCapture(0)
ret, frame = camera.read()

if ret:
    print('Capture Successful!')
else:
    print('Oops, we get some trouble!')

Use the matplotlib library to display it on the Jupyter notebook page.

from matplotlib import pyplot as plt

# Magic to tell matplotlib to display the image in jupyter notebook
%matplotlib inline 

# Let's show the image! 
plt.imshow(frame)

Convert from OpenCV's BGR to RGB to make the color of the image displayed by matplotlib normal.

# Convert from BGR to RGB
frame_rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)

plt.imshow(frame_rgb)

Try converting to grayscale.

# Convert from BGR to RGB
frame_gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

# We need to tell matplotlib it is a grey image. You can try to change to other cmap, refer here: https://matplotlib.org/stable/tutorials/colors/colormaps.html
plt.imshow(frame_gray, cmap='gray') 

Capture and save the image.

import cv2
camera = cv2.VideoCapture(0)
ret, frame = camera.read()

if ret:
    print('Capture Successful!')
    cv2.imwrite('test2.png', frame)
else:
    print('Oops, we get some trouble!')

SSH Login

ssh m5stack@10.254.239.1 

//user: m5stack
//pwd: 12345678

//user: root
//pwd: 7d219bec161177ba75689e71edc1835422b87be17bf92c3ff527b35052bf7d1f

User default directory structure

//To store files edited in Jupyter Notebook
/home/notebook

//To store recognition service file resources, and some model files
/home/m5stack 

Related OpenCV Tutorials

• OpenCV tutorials