How to use PIL library to get a mask diagram from a damage diagram

This answer quotes the full Python code from ChatGPT
to convert a broken image into a mask image, Be careful to replace damaged_image.jpg with your actual image file name:

from PIL import Image, ImageOps

# 打开破损图像
img = Image.open('damaged_image.jpg')

# 修复图像
fixed_img = ImageOps.expand(img, border=50, fill='black')

# 转换为mask图像
mask = fixed_img.convert('L').point(lambda x: 255 if x > 128 else 0, mode='1')

# 保存mask图像
mask.save('mask_image.jpg')

Executing the above code generates a file called mask_image.jpg, which is the mask image of the broken image.

This answer partially references GPT, GPT_Pro to better solve the problem
Use PIL library to convert a damage map to a mask map, which can be done by:

1. First, import the PIL library and open the Image to be processed using the pil.image.open() method.

2. Then, convert the image to grayscale using the PIL.Image.convert() method.

3. Then, the PIL.Image.threshold() method was used to binarize the gray image and obtain the mask graph.

4. Finally, save the mask diagram to the specified folder using the PIL.Image.save() method.

These are the steps for converting a damage diagram to a mask diagram using the PIL library. Although this method can get us the mask diagram we want, it is recommended to combine the OpenCV library with the PIL library to get a higher quality mask diagram.
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