data.py

import cv2
import pickle as pkl
import numpy as np

def load_dict_picklefile(dictFile):
    fp=open(dictFile,'rb')
    worddicts=pkl.load(fp)
    fp.close()
    worddicts_r = [None] * len(worddicts)
    i=1
    for kk, vv in worddicts.items():
        if(i<len(worddicts)):
            worddicts_r[vv] = kk
        else:
            break
        i=i+1
    return worddicts_r

def preprocess_img(img):
    if len(img.shape)>2:
      img= cv2.cvtColor(img.astype('float32'), cv2.COLOR_BGR2GRAY)
    height=img.shape[0]
    width=img.shape[1]

    if(width<300):
      result = np.ones([img.shape[0], img.shape[1]*2])*255
      result[0:img.shape[0],img.shape[1]:img.shape[1]*2]=img
      img=result

    img=cv2.resize(img, dsize=(800,100), interpolation = cv2.INTER_AREA)
    img=(img-img.min())/(img.max()-img.min())
    xx_pad = np.zeros((100, 800), dtype='float32')
    xx_pad[:,:] =1

    xx_pad = xx_pad[None, :, :]
    img=img[None, :, :]
    return img, xx_pad