from scipy.misc import imsave
import os
import numpy as np
import pandas as pd
from keras.datasets import mnist

def convert_to_jpg(x,y,df_type='train'):
    if df_type=='train':
        path = os.path.abspath('./digit-recognizer/train')
        if not os.path.isdir(path):
            os.mkdir(path)

    elif df_type=='test':
        path = os.path.abspath('./digit-recognizer/test')
        if not os.path.isdir(path):
            os.mkdir(path)

    c=0
    for i in range(y.shape[0]):
        name = 'image' + str(i) + '_' +str(y[i]) + '.jpg'
        imsave(os.path.join(path,str(name)),x[i])
        c+=1
        if c%5000==0:
            print('{} images written'.format(c))


if __name__=='__main__':
    (x_train,y_train),(x_test,y_test) = mnist.load_data()
    ## the above command might take some time as it will download the data(68 mb approx.)
    convert_to_jpg(x_train,y_train,'train')
    convert_to_jpg(x_test,y_test,'test')