#! env python
# coding: utf-8
# 功能：对图像进行预处理，将文字部分单独提取出来
# 并存放到ocr目录下
# 文件名为原验证码文件的文件名
import TickerConfig
if TickerConfig.AUTO_CODE_TYPE == 2:
import hashlib
import os
import pathlib
import cv2
import numpy as np
import requests
import scipy.fftpack
PATH = 'imgs'
def download_image():
# 抓取验证码
# 存放到指定path下
# 文件名为图像的MD5
url = 'https://kyfw.12306.cn/otn/passcodeNew/getPassCodeNew?module=login&rand=sjrand'
r = requests.get(url)
fn = hashlib.md5(r.content).hexdigest()
with open(f'{PATH}/{fn}.jpg', 'wb') as fp:
fp.write(r.content)
def download_images():
pathlib.Path(PATH).mkdir(exist_ok=True)
for idx in range(40000):
download_image()
print(idx)
def get_text(img, offset=0):
# 得到图像中的文本部分
return img[3:22, 120 + offset:177 + offset]
def avhash(im):
im = cv2.resize(im, (8, 8), interpolation=cv2.INTER_CUBIC)
avg = im.mean()
im = im > avg
im = np.packbits(im)
return im
def phash(im):
im = cv2.resize(im, (32, 32), interpolation=cv2.INTER_CUBIC)
im = scipy.fftpack.dct(scipy.fftpack.dct(im, axis=0), axis=1)
im = im[:8, :8]
med = np.median(im)
im = im > med
im = np.packbits(im)
return im
def _get_imgs(img):
interval = 5
length = 67
for x in range(40, img.shape[0] - length, interval + length):
for y in range(interval, img.shape[1] - length, interval + length):
yield img[x:x + length, y:y + length]
def get_imgs(img):
imgs = []
for img in _get_imgs(img):
imgs.append(phash(img))
return imgs
def pretreat():
if not os.path.isdir(PATH):
download_images()
texts, imgs = [], []
for img in os.listdir(PATH):
img = os.path.join(PATH, img)
img = cv2.imread(img, cv2.IMREAD_GRAYSCALE)
texts.append(get_text(img))
imgs.append(get_imgs(img))
return texts, imgs
def load_data(path='data.npz'):
if not os.path.isfile(path):
texts, imgs = pretreat()
np.savez(path, texts=texts, images=imgs)
f = np.load(path)
return f['texts'], f['images']
if __name__ == '__main__':
texts, imgs = load_data()
print(texts.shape)
print(imgs.shape)
imgs = imgs.reshape(-1, 8)
print(np.unique(imgs, axis=0).shape)
