import torch
import os

# Define the model architecture and other necessary functions/classes
# ... (This would include the 'Pix2PixModelAdjusted', 'Opt', and any other necessary classes)

# Initialize the model
opt = Opt()
model = Pix2PixModelAdjusted(opt)
model.netG.eval()  # Set to evaluation mode

# Load the trained weights
model_path = "./latest_net_G.pth"  # Adjust the path if necessary
model.netG.load_state_dict(torch.load(model_path))

# The model is now initialized and ready for inferencing