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import gradio as gr
from transformers import pipeline
from PIL import Image
# Gunakan model deteksi publik
classifier = pipeline("image-classification", model="dima806/deepfake_vs_real_image_detection")
def detect(image):
# image dari Gradio
results = classifier(image)
# hasil tertinggi
best = max(results, key=lambda x: x['score'])
label = best['label']
confidence = best['score'] * 100
if "fake" in label.lower() or "generated" in label.lower() or "ai" in label.lower():
verdict = "⚠️ Kemungkinan besar Gambar AI / Fake"
else:
verdict = "✅ Kemungkinan besar Foto Asli"
return f"{verdict}\n\nLabel: {label}\nConfidence: {confidence:.2f}%"
app = gr.Interface(
fn=detect,
inputs=gr.Image(type="pil", label="Upload Foto"),
outputs=gr.Textbox(label="Hasil Deteksi"),
title="Detektor Foto vs AI",
description="Unggah foto realistik untuk mendeteksi apakah foto asli atau hasil AI."
)
if __name__ == "__main__":
app.launch()
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