学习进度笔记20

观看Tensorflow案例实战视频课程20 构造网络的输入数据和标签

import numpy as np
import tensorflow as tf
from captcha.image import ImageCaptcha
import numpy as np
import matplotlib.pyplot as plt
from PIL import Image
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']

#def random_captcha_text(char_set=number+alphabet+ALPHABET,captcha_size=4):
def random_captcha_text(char_set=number,captcha_size=4):
    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():
    image=ImageCaptcha()

    captcha_text=random_captcha_text()
    captcha_text=''.join(captcha_text)

    captcha=image.generate(captcha_text)
    #image.write(captcha_text,captcha_text+'.jpg')

    captcha_image=Image.open(captcha)
    captcha_image=np.array(captcha_image)
    return captcha_text,captcha_image

if __name__=='__main__':
    train=0
    if train==0:
        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']

        text,image=gen_captcha_text_and_image()
        print("验证码图像channel:",image.shape)#(60,160,3)
        #图像大小
        IMAGE_HEIGHT=60
        IMAGE_WIDTH=160
        MAX_CAPTCHA=len(text)
        print("验证码文本最长字符数",MAX_CAPTCHA)
        #文本转向量
        #char_set=number+alphabet+ALPHACET+['_']#如果验证码长度小于4，'_'用来补充
        char_set=number
        CHAR_SET_LEN=len(char_set)

        X=tf.placeholder(tf.float32,[None,IMAGE_HEIGHT*IMAGE_WIDTH])
        Y=tf.placeholder(tf.float32,[None,MAX_CAPTCHA*CHAR_SET_LEN])
        keep_prob=tf.placeholder(tf.float32)# dropout

        train_crack_captcha_cnn()