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

model_path = 'karolprando/deepfake-detector-v1'

model = AutoModelForImageClassification.from_pretrained(model_path)
processor = AutoImageProcessor.from_pretrained(model_path)

img_path = r"C:\Users\Karol\OneDrive\Imagens\popeia.jpeg" # substitui aqui
image = Image.open(img_path)

inputs = processor(images=image, return_tensors="pt")
with torch.no_grad():
    outputs = model(**inputs)
    preds = torch.nn.functional.softmax(outputs.logits, dim=-1)
    predicted_label = preds.argmax(-1).item()

print("Predição:", model.config.id2label[predicted_label])