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Using USB Camera

The camera is like OpenCV's eyes. With a camera, you can process video streams and images captured by the camera in real-time, implementing image processing and machine vision algorithms on them.

The WalnutPi system has built-in USB camera drivers. Most USB cameras on the market can be used. The following model is used for this tutorial: Click to buy->

usb_cam1

Simply plug it into one of the WalnutPi USB ports.

usb_cam2

Getting USB Camera Device Information​

First, use v4l2-ctl to view the current USB camera device information. This requires installing v4l. Most WalnutPi software can be installed via sudo apt install:

sudo apt install v4l-utils

After installation, run the following command to view the inserted USB camera information:

v4l2-ctl --list-devices

You can see that this camera has multiple video devices, usually the first one. Here it is: video1

usb_cam3

Using Camera via OpenCV​

OpenCV can obtain camera video streams through the VideoCapture() function. A camera video stream is essentially a series of images frame by frame. Therefore, by combining the previously learned reading, displaying, and saving images, you can capture and display camera images (since it is fast, it looks like a video). Reference code is as follows:

'''
Experiment Name: Using USB Camera
Experiment Platform: WalnutPi
'''

import cv2

cam = cv2.VideoCapture(1) # Open the camera, confirm the number

while (cam.isOpened()): # Confirm it is opened
    
    retval, img = cam.read() # Read images from the camera in real-time
    
    cv2.imshow("Video", img) # Display the read image in a window
    
    key = cv2.waitKey(1) # Window image refresh time is 1 millisecond to prevent blocking
    
    if key == 32: # If the spacebar is pressed, break
        break
    
cam.release() # Close the camera
cv2.destroyAllWindows() # Destroy the window displaying the camera video

Run the code on the WalnutPi, and you can see the video images captured by the camera displayed in real-time:

usb_cam3

The img obtained in the code is each frame image, which can be used for all the OpenCV image processing operations we have learned previously.