inference.py

import torch
from transformers import AutoModelForImageClassification, AutoFeatureExtractor
from PIL import Image

# Load model and feature extractor
model = AutoModelForImageClassification.from_pretrained("your-username/deepfake-recognition")
feature_extractor = AutoFeatureExtractor.from_pretrained("your-username/deepfake-recognition")

# Load an image
image = Image.open("sample_image.jpg")
inputs = feature_extractor(images=image, return_tensors="pt")

# Predict
outputs = model(**inputs)
predicted_class = torch.argmax(outputs.logits, dim=1).item()

print(f"Predicted Class: {'Deepfake' if predicted_class == 1 else 'Real'}")