[python][图像切割]给定手写数字图片完成数字切割

import torch
import torch.nn as nn
from torchvision import transforms
from PIL import Image, ImageOps
import numpy as np

img = Image.open("QQ.png")
img

def CutImage(img):
  img = img.convert("L")
  threshold = 128
  img = img.point(lambda x: 0 if x > threshold else 255)
  width, height = img.size
  images = []
  images2828 = []
  in_digit = False
  left = 0
  top = height
  bottom = 0
  for x in range(width):
      has_black = False
      for y in range(height):
          pixel = img.getpixel((x, y))
          if pixel == 0:
              has_black = True
              top = min(top, y)
              bottom = max(bottom, y)
      if has_black and not in_digit:
          in_digit = True
          left = x
      if not has_black and in_digit:
          in_digit = False
          right = x
          image = img.crop((left, top, right, bottom))
          image = ImageOps.invert(image)
          images.append(image)

  for obj in images:
    if 4 * obj.size[0] <= obj.size[1]:
      zero_matrix = np.zeros((obj.size[1], 4 * obj.size[0]))
      result_matrix = np.concatenate((zero_matrix, obj, zero_matrix), axis=1)
      resized_image = Image.fromarray(result_matrix).resize((28, 28), resample=Image.Resampling.NEAREST)
      images2828.append(resized_image)
      continue
    obj = np.pad(np.asarray(obj), pad_width=20, mode='constant', constant_values=0)
    resized_image = Image.fromarray(obj).resize((28, 28), resample=Image.Resampling.NEAREST)
    images2828.append(resized_image.convert('F'))

  return images2828

image_list = CutImage(img)

image_list

[<PIL.Image.Image image mode=F size=28x28>,
 <PIL.Image.Image image mode=F size=28x28>,
 <PIL.Image.Image image mode=F size=28x28>,
 <PIL.Image.Image image mode=F size=28x28>,
 <PIL.Image.Image image mode=F size=28x28>,
 <PIL.Image.Image image mode=F size=28x28>,
 <PIL.Image.Image image mode=F size=28x28>,
 <PIL.Image.Image image mode=F size=28x28>,
 <PIL.Image.Image image mode=F size=28x28>]

import matplotlib.pyplot as plt
plt.imshow(image_list[0], cmap='gray')
plt.show()

plt.imshow(image_list[1], cmap='gray')
plt.show()

plt.imshow(image_list[2], cmap='gray')
plt.show()