app.py

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

# Muat model Hugging Face khusus deteksi AI
classifier = pipeline("image-classification", model="elacour/ai-image-detection")

def detect_image(image):
    # --- Cek metadata (EXIF) ---
    exif = {}
    try:
        raw_exif = image._getexif()
        if raw_exif:
            exif = {ExifTags.TAGS.get(k, k): v for k, v in raw_exif.items()}
    except:
        pass
    
    if not exif:
        exif_result = "⚠️ Tidak ada metadata kamera → kemungkinan besar AI atau editan"
    else:
        exif_result = "✅ Metadata kamera terdeteksi"

    # --- Prediksi model ---
    results = classifier(image)
    label = results[0]["label"]
    score = results[0]["score"] * 100

    if "fake" in label.lower() or "ai" in label.lower():
        verdict = "🚨 Kemungkinan besar Hasil AI"
    else:
        verdict = "📷 Kemungkinan besar Foto Asli"

    # --- Gabungan hasil ---
    final_result = f"{verdict}\n\nLabel Model: {label}\nConfidence: {score:.2f}%\n\nCek Metadata: {exif_result}"
    return final_result

# Buat UI Gradio
iface = gr.Interface(
    fn=detect_image,
    inputs=gr.Image(type="pil"),
    outputs="text",
    title="Hybrid AI Image Detector",
    description="Upload foto untuk mendeteksi apakah gambar hasil kamera asli atau hasil AI."
)

iface.launch()