def wrap_gen_captcha_text_and_image():
while True:
text, image = gen_captcha_text_and_image_new()
if image.shape == image_shape:
return text, image
# -*- coding:utf-8 -*-
from gen_check_code import gen_captcha_text_and_image_new, gen_captcha_text_and_image
from gen_check_code import number
from test_check_code import get_test_captcha_text_and_image
import numpy as np
import tensorflow as tf
text, image = gen_captcha_text_and_image_new()
print("验证码图像channel:", image.shape) # (60, 160, 3)
# 图像大小
IMAGE_HEIGHT = image.shape[0]
IMAGE_WIDTH = image.shape[1]
image_shape = image.shape
MAX_CAPTCHA = len(text)
print("验证码文本最长字符数", MAX_CAPTCHA) # 验证码最长4字符; 我全部固定为4,可以不固定. 如果验证码长度小于4，用'_'补齐
# 把彩色图像转为灰度图像（色彩对识别验证码没有什么用）
# 度化是将三分量转化成一样数值的过程
def convert2gray(img):
if len(img.shape) > 2:
gray = np.mean(img, -1)
# 上面的转法较快，正规转法如下
# r, g, b = img[:,:,0], img[:,:,1], img[:,:,2]
# gray = 0.2989 * r + 0.5870 * g + 0.1140 * b
# int gray = (int) (0.3 * r + 0.59 * g + 0.11 * b);
return gray
else:
return img
