#在PIL中，从模式“RGB”转换为“L”模式(灰度模式)
Gray = 0.299R+0.587G+0.114B

[0.0， 9.8)这|a
[9.8, 19.6)|b
[19.6, 29.4)|c
...|...
[225.6, 235.4]|x
[235.4, 245.2]|y
[245.2, 255.0]|z

char_string = 'abcdefghijklmnopqrstuvwxyz'

def rgb2char(r, g, b):
  length = len(char_string)
  gray = int(0.2126 * r + 0.7152 * g + 0.0722 * b)

  # 每个字符对应的gray值区间宽度
  unit = (256.0 + 1) / length

  # gray值对应到char_string中的位置（索引值）
  idx = int(gray / unit)
  return char_string[idx]

from PIL import Image

#预处理（将图片尺寸压缩，并转为灰度图） 
def preprocess(img_path,delta=100):
  img = Image.open(img_path) 
  # 获取图片尺寸
  width, height = img.size
  # 获取图片最大边的长度 if width > height:
    max = width
  else:
    max = height

  # 伸缩倍数scale
  scale = max / delta
  width, height = int(width / scale), int(height / scale)
  img = img.resize((width, height)) 
  return img

def img2char(img_obj, savepath):
  txt = ''
  width, height = img_obj.size
  # 获取像素点的rgb元组值，如(254, 0, 0)，并将其转化为字符
  for i in range(height):
    line = ''
    for j in range(width):
      line += rgb2char(*img_obj.getpixel((j, i)))
    txt = txt + line + '\n'

  # 保存字符画
  with open(savepath, 'w+', encoding='utf-8') as f:
    f.write(txt)




img_obj = preprocess(img_path)
img2char(img_obj, savepath)