import pandas as pd
import torch
from PIL import Image
from torchvision import transforms

# Load the model
model = torch.jit.load("SuSy.pt")

# Load patch
patch = Image.open("midjourney-images-example-patch0.png")

# Transform patch to tensor
patch = transforms.PILToTensor()(patch).unsqueeze(0) / 255.

# Predict patch
model.eval()
with torch.no_grad():
    preds = model(patch)

# Print results
classes = ['authentic', 'dalle-3-images', 'diffusiondb', 'midjourney-images', 'midjourney_tti', 'realisticSDXL']
result = pd.DataFrame(preds.numpy(), columns=classes)
print(result)