app.py

import gradio as gr
from transformers import pipeline
from PIL import Image

# Model publik (tidak perlu token)
model1 = pipeline("image-classification", model="umm-maybe/ai-image-detector")
model2 = pipeline("image-classification", model="google/vit-base-patch16-224")

def detect_ai(image):
    img = image.convert("RGB").resize((224, 224))

    res1 = model1(img)[0]
    res2 = model2(img)[0]

    label1, conf1 = res1['label'], res1['score']
    label2, conf2 = res2['label'], res2['score']

    # Voting sederhana: kalau model1 bilang FAKE, lebih dipercaya
    if "fake" in label1.lower() or "ai" in label1.lower():
        verdict = "🚨 Kemungkinan besar AI Generated"
    elif "real" in label1.lower():
        verdict = "✅ Kemungkinan besar Foto Asli"
    else:
        verdict = "⚠️ Tidak Pasti (cek manual)"

    return f"""{verdict}

Model AI-detector: {label1} ({conf1*100:.2f}%)
Model General (ViT): {label2} ({conf2*100:.2f}%)"""

demo = gr.Interface(
    fn=detect_ai,
    inputs=gr.Image(type="pil"),
    outputs="text",
    title="Deteksi Foto AI vs Asli (Gratis)",
    description="Menggunakan model publik gratis Hugging Face."
)

demo.launch()