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 | |