OpenCV image reading and display

1. Reading of images:

img = cv2.imread('yahboom.jpg', 0) The first parameter is the path of the image, and the second parameter is how to read the image.

cv2.IMREAD_UNCHANGED: Keep the original format unchanged, -1;

cv2.IMREAD_GRAYSCALE: Read the image in grayscale mode, which can be represented by 0;

cv2.IMREAD_COLOR:, read a color picture, which can be represented by 1; default value

cv2.IMREAD_UNCHANGED: Read in an image and include its alpha channel, which can be represented by 2.

2. Image display

cv.imshow('frame', frame): Open a window named frame and display frame data (image/video data)

Parameter meaning:

The first parameter represents the name of the window that is created and opened.

The second parameter represents the image to be displayed

2.1. Code and actual effect display

• Start Docker

After entering the Raspberry Pi 5 desktop, open a terminal and run the following command to start the container corresponding to Dofbot:

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./Docker_Ros.sh

Access Jupyter Lab within Docker:

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IP:9999 // Example: 192.168.1.11:9999

Code path:

/root/Dofbot/4.opencv/1.OpenCV_basic/01_read_pic.ipynb

Main code:

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import cv2
img = cv2.imread('yahboom.jpg', 1)
# cv2.imshow('image', img) #This line can only be executed on the py file on the command line, and a video window will pop up.
# cv2.waitKey (0)

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#bgr8 to jpeg format
import enum
import cv2
def bgr8_to_jpeg(value, quality=75):
return bytes(cv2.imencode('.jpg', value)[1])

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#The image component in jupyterLab displays the read image
import ipywidgets.widgets as widgets
image_widget = widgets.Image(format='jpg', width=800, height=800)
display(image_widget)
image_widget.value = bgr8_to_jpeg(img)

After running the code block, you can see the following interface, and the image has been read out.