Welcome to AI View Depth camera repository

Image cutting

Image cutting first reads the image, and then obtains the pixel area in the array. In the following code, select the shape area X: 300-500 Y: 500-700. Note that the image size is 800*800, so the selected area should not exceed this resolution.

• 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/2.Transform/02_cut_pic.ipynb

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import cv2
img = cv2.imread('yahboom.jpg', 1)
dst = img[500:700,300:500] #Select the rectangular area X: 300-500 Y: 500-700
#cv2.imshow('image',dst)

#cv2.waitKey(0)

The following will display two compressed image comparison displays in the jupyterLab control.

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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])

Compare the before and after images below:

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import ipywidgets.widgets as widgets
image_widget1 = widgets.Image(format='jpg', )
image_widget2 = widgets.Image(format='jpg', )
# display the container in this cell's output
display(image_widget1)
display(image_widget2)
img1 = cv2.imread('yahboom.jpg',1)

image_widget1.value = bgr8_to_jpeg(img1) #Original image
image_widget2.value = bgr8_to_jpeg(dst) #Cut image

After the program is finished running, you can see that some parts have been cut out.