Module using python-PIL

PIL Basic Features

from PIL import Image
from PIL import ImageEnhance

img = Image.open(r'E:\img\f1.png')
img.show()
#Binary image
img = img.convert('L')
# Image to enlarge
img = img.resize((img.width * int(3), img.height * int(4)), Image.ANTIALIAS)
# # Contrast Enhancement
enh_con = ImageEnhance.Contrast(img)
contrast = 2
img_contrasted = enh_con.enhance(contrast)
# Brightness enhancement
enh_bri = ImageEnhance.Brightness(img_contrasted)
brightness = 2.5
image_brightened = enh_bri.enhance(brightness)
# Chroma enhancement
enh_col = ImageEnhance.Color(img)
color = 50
image_colored = enh_col.enhance(color)
# # Sharpness enhancement
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')

# Image Character Recognition
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')　　

The picture in black and white treatment

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')

　　

Coordinate calculation large panel of FIG.

def get_screenxy_from_bmp(main_bmp, son_bmp):
    # Get theme matching the specified coordinates on the screen -> (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

　　

ImageGrab achieve Screenshots

(Im = ImageGrab.grab)
im.save('D:/as1.png')

# # # # Parameter Description
# # # # The first parameter of the x coordinate of the start screenshot
# # # # The second parameter y coordinate of the start screenshot
# # # # End of the third parameter x coordinate screenshots
# # # # End of the fourth parameter y coordinate screenshots
Bbox = (897, 131, 930, 148)
im = ImageGrab.grab (Bbox)
im.save('D:/as2.png')