Update app.py

app.py

@@ -1,20 +1,23 @@
 import gradio as gr
 from transformers import pipeline
 
-# Gunakan model publik valid
 classifier = pipeline("image-classification", model="dima806/deepfake_vs_real_image_detection")
 
 def detect_ai(image):
     results = classifier(image)
-    label = results[0]['label']
-    score = results[0]['score']
-    # logika menentukan hasil
-    if "real" in label.lower():
-        return f"✅ Foto Asli (confidence: {score:.2f})"
+
+    output_str = "Hasil Deteksi:\n"
+    for r in results:
+        output_str += f"- {r['label']}: {r['score']:.2f}\n"
+
+    best = max(results, key=lambda x: x['score'])
+    if "real" in best['label'].lower():
+        output_str = f"✅ Foto Asli (confidence: {best['score']:.2f})\n\n" + output_str
     else:
-        return f"🤖 Gambar AI / Fake (confidence: {score:.2f})"
+        output_str = f"🤖 Gambar AI / Fake (confidence: {best['score']:.2f})\n\n" + output_str
+
+    return output_str
 
-# Buat interface Gradio
 demo = gr.Interface(
     fn=detect_ai,
     inputs=gr.Image(type="pil", label="Upload Gambar"),