python PIL模块的基本使用
傻白甜++ 人气:0本文着重讲解了python PIL模块的基本使用,帮助大家更好的利用python处理图片,欢迎大家阅读
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')
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