Python生成验证码方案

vcode_gen.py

# coding: utf-8
"""

    Python 验证码生成封装
    生产环境使用NO POLT模式，单次耗时100ms左右。


    2020-12-04
"""
from captcha.image import ImageCaptcha
from PIL import Image
import base64
import random

number = ['0', '1', '2', '3', '4', '5', '6', '7', '8', '9']
alphabet = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j', 'k', 'l', 'm', 'n', 'o', 'p', 'q', 'r', 's', 't', 'u',
            'v', 'w', 'x', 'y', 'z']
ALPHABET = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N', 'O', 'P', 'Q', 'R', 'S', 'T', 'U',
            'V', 'W', 'X', 'Y', 'Z']
MISC = number + alphabet + ALPHABET


def random_captcha_text(char_set=None, captcha_size=4):
    if char_set is None:
        char_set = MISC
    captcha_text = []
    for i in range(captcha_size):
        c = random.choice(char_set)
        captcha_text.append(c)
    return captcha_text


def gen_captcha_text_and_image():
    """
    仅供训练调试使用
    :return:
    验证码答案，验证码np图形
    """
    image1 = ImageCaptcha()
    captcha_text = random_captcha_text()
    captcha_text = ''.join(captcha_text)
    captcha = image1.generate(captcha_text)
    captcha_image = Image.open(captcha)
    captcha_image_np = np.array(captcha_image)
    return captcha_text, captcha_image_np


def gen_captcha_embed_base64():
    """
    供网页使用
    :return:
    验证码答案，base64编码过得web内嵌png图片
    """
    image1 = ImageCaptcha()
    captcha_text = random_captcha_text()
    captcha_text = ''.join(captcha_text)
    captcha = image1.generate(captcha_text)
    data = captcha.getvalue()
    encode_data = base64.b64encode(data)
    data = encode_data.encode('utf-8')
    img_data = "data:image/png;base64,{data}".format(data=data)
    return captcha_text, img_data


if __name__ == '__main__':
    PLOT = 0
    if PLOT:
        import matplotlib.pyplot as plt
        import numpy as np
        # 正确的答案也显示在图片上，可作数据源用TensorFlow训练，获得破解模型。
        text, image = gen_captcha_text_and_image()
        f = plt.figure()
        ax = f.add_subplot(111)
        ax.text(0.1, 0.9, text, ha='center', va='center', transform=ax.transAxes)
        plt.imshow(image)
        plt.show()
    else:
        text, embed_data = gen_captcha_embed_base64()
        print(text)
        print(embed_data[:100])