datasets/demo_dataset.py

import numpy as np
import torch

def preprocess_demo_image(image):
    image = image.resize( (256, 256))
    image = np.asarray(image).transpose(2, 0, 1).astype(np.float32) # C,H,W -> H,W,C
    image = torch.FloatTensor(image.copy())
    image = (image - 127.5) / 127.5     # Normalize
    return image.unsqueeze(0)