def main():
parser = argparse.ArgumentParser(description='Deblur image')
parser.add_argument('-d','--data', help='Input data image')
parser.add_argument('-o','--output', help='Output image')
#START: Stage 0 load the image
args = parser.parse_args()
input_name = args.data
img = cv2.imread(input_name)
fig = plt.figure()
ax1 = fig.add_subplot(2,2,1)
ax1.imshow(img)
#Stage 1 add padding
img,y,x = add_padding(img)
#Stage 2 openCV optimization
#Stage 3 Machine Learning Deblur
model = NeuralNet()
img = model.predict(img)
#Stage 4 More openCV
#End
ax2 = fig.add_subplot(2,2,2)
img = remove_padding(img,x,y)
ax2.imshow(img)
plt.show()
