我要评论pil基本功能介绍
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')
对图片进行黑白化处理
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')
计算小图在大图的坐标
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
imagegrab实现屏幕截图
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')
以上就是python pil模块的基本使用的详细内容，更多关于python pil模块的资料请关注移动技术网其它相关文章！
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