app.py

import gradio as gr
from transformers import pipeline

# gunakan model deteksi AI vs Real
pipe = pipeline("image-classification", model="umm-maybe/AI-image-detector")

def detect_ai(image):
    results = pipe(image)
    results = sorted(results, key=lambda x: x['score'], reverse=True)
    label = results[0]['label']
    confidence = results[0]['score']

    if "ai" in label.lower() or "fake" in label.lower():
        status = "⚠️ Kemungkinan besar AI Generated"
    else:
        status = "✅ Kemungkinan besar Foto Asli"

    return f"{status}\n\nLabel: {label}\nConfidence: {confidence*100:.2f}%"

with gr.Blocks() as demo:
    gr.Markdown("## 🖼️ AI Image Detector")
    with gr.Row():
        with gr.Column():
            image_input = gr.Image(type="pil", label="Upload Gambar")
            btn = gr.Button("Deteksi")
        with gr.Column():
            output_text = gr.Textbox(label="Hasil Deteksi", lines=5)

    btn.click(detect_ai, inputs=image_input, outputs=output_text)

demo.launch()