Python PIL模块核心功能实战：图像二值化、坐标匹配与屏幕截图

from PIL import Image
from PIL import ImageEnhance
 
img = Image.open(r'E:\img\f1.png')
img.show()
#图像二值化
img = img.convert('L')
# 图像放大
img = img.resize((img.width * int(3), img.height * int(4)), Image.ANTIALIAS)
# # 对比度增强
enh_con = ImageEnhance.Contrast(img)
contrast = 2
img_contrasted = enh_con.enhance(contrast)
# 亮度增强
enh_bri = ImageEnhance.Brightness(img_contrasted)
brightness = 2.5
image_brightened = enh_bri.enhance(brightness)
#色度增强
enh_col = ImageEnhance.Color(img)
color = 50
image_colored = enh_col.enhance(color)
# # 锐度增强
enh_sha = ImageEnhance.Sharpness(img)
sharpness = 2
image_sharped = enh_sha.enhance(sharpness)
image_sharped.save(r'E:\img\f22.png', dpi=(300, 300), quality=95)
# image_sharped.save(r'E:\img\f22.png')
 
# 图片汉字识别
img2 = Image.open(r'E:\img\f22.png')
code2 = pytesseract.image_to_string(img2, lang='chi_sim')
# print(code2)
# 图片裁剪
image_cro = Image.open(r'E:\img\f24.png')
image_cropped = image_cro.crop(res)
image_cropped.save(u'E:\img\\f25.png')　

基于阈值的图像二值化处理

img_main = Image.open(u'E:/login1.png')
img_main = img_main.convert('L')
threshold1 = 138
table1 = []
for i in range(256):
  if i < threshold1:
    table1.append(0)
  else:
    table1.append(1)
img_main = img_main.point(table1, "1")
img_main.save(u'E:/login3.png')

小图在大图中的坐标匹配算法

def get_screenxy_from_bmp(main_bmp, son_bmp):
  # 获取屏幕上匹配指定截图的坐标->(x,y,width,height)
 
  img_main = Image.open(main_bmp)
  img_main = img_main.convert('L')
  threshold1 = 138
  table1 = []
  for i in range(256):
    if i < threshold1:
      table1.append(0)
    else:
      table1.append(1)
  img_main = img_main.point(table1, "1")
 
  img_son = Image.open(son_bmp)
  img_son = img_son.convert('L')
  threshold2 = 138
  table2 = []
  for i in range(256):
    if i < threshold2:
      table2.append(0)
    else:
      table2.append(1)
  img_son = img_son.point(table2, "1")
 
  datas_a = list(img_main.getdata())
  datas_b = list(img_son.getdata())
  for i, item in enumerate(datas_a):
    if datas_b[0] == item and datas_a[i + 1] == datas_b[1]:
      yx = divmod(i, img_main.size[0])
      main_start_pos = yx[1] + yx[0] * img_main.size[0]
 
      match_test = True
      for n in range(img_son.size[1]):
        main_pos = main_start_pos + n * img_main.size[0]
        son_pos = n * img_son.size[0]
 
        if datas_b[son_pos:son_pos + img_son.size[0]] != datas_a[main_pos:main_pos + img_son.size[0]]:
          match_test = False
          break
      if match_test:
        return (yx[1], yx[0], img_son.size[0], img_son.size[1])
  return False

使用ImageGrab进行屏幕截图

im = ImageGrab.grab()
im.save('D:/as1.png')
 
#   # # # 参数说明
#   # # # 第一个参数 开始截图的x坐标
#   # # # 第二个参数 开始截图的y坐标
#   # # # 第三个参数 结束截图的x坐标
#   # # # 第四个参数 结束截图的y坐标
bbox = (897, 131, 930, 148)
im = ImageGrab.grab(bbox)
im.save('D:/as2.png')