# This Python 3 environment comes with many helpful analytics libraries installed
# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python
# For example, here's several helpful packages to load in 

import numpy as np # linear algebra
import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)
import cv2

# Input data files are available in the "../input/" directory.
# For example, running this (by clicking run or pressing Shift+Enter) will list the files in the input directory

from subprocess import check_output
print(check_output(["ls", "../input"]).decode("utf8"))

if __name__ == '__main__' :
    # Read source image.
    im_src1 = cv2.imread('../input/train_sm/set4_1.jpeg')
    im_src2 = cv2.imread('../input/train_sm/set4_2.jpeg')



# Any results you write to the current directory are saved as output.