upscale images using opencv + deeplearning

upscale.py

import cv2
from cv2 import dnn_superres

import argparse
parser = argparse.ArgumentParser()
parser.add_argument('--in_dir', help='where is the images?')
parser.add_argument('--out_dir', help='where should I save the images?')
parser.add_argument('--num', help='id');

if __name__ == "__main__":

    args = parser.parse_args()

    num = args.num.zfill(4);

    # image path
    image_path = f'{args.in_dir}/upscaled_{num}.png'

    # Create an SR object
    sr = dnn_superres.DnnSuperResImpl_create()
    
    # Read image
    image = cv2.imread(image_path);
    
    # Read the desired model
    path = "models/EDSR_x3.pb"
    sr.readModel(path)
    
    # Set the desired model and scale to get correct pre- and post-processing
    sr.setModel("edsr", 3)
    
    # Upscale the image
    result = sr.upsample(image)
    
    # Save the image
    cv2.imwrite(f'{args.out_dir}/upscaled_{num}.png', result)

    print(f'upscaled {num}')