Update app.py

app.py

@@ -1,30 +1,35 @@
 import gradio as gr
 from transformers import pipeline
 
-classifier = pipeline("image-classification", model="dima806/deepfake_vs_real_image_detection")
+# load pipeline deteksi AI vs Real
+pipe = pipeline("image-classification", model="microsoft/resnet-50")  
+# ⚠️ ganti dengan model pendeteksi AI/real sesuai yang kamu pakai
+# contoh lain: "microsoft/ai-image-detector"
 
 def detect_ai(image):
-    results = classifier(image)
+    results = pipe(image)
+    # Ambil hasil prediksi teratas
+    results = sorted(results, key=lambda x: x['score'], reverse=True)
+    label = results[0]['label']
+    confidence = results[0]['score']
 
-    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
+    # Ubah jadi lebih informatif
+    if "AI" in label or "Fake" in label:
+        status = "Kemungkinan besar AI"
     else:
-        output_str = f"🤖 Gambar AI / Fake (confidence: {best['score']:.2f})\n\n" + output_str
+        status = "Kemungkinan besar Foto Asli"
+
+    return f"{status}\n\nLabel: {label}\nConfidence: {confidence*100:.2f}%"
 
-    return output_str
+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)
 
-demo = gr.Interface(
-    fn=detect_ai,
-    inputs=gr.Image(type="pil", label="Upload Gambar"),
-    outputs=gr.Textbox(label="Hasil Deteksi"),
-    title="AI vs Real Image Detector",
-    description="Upload gambar untuk mengecek apakah gambar asli atau buatan AI."
-)
+    btn.click(detect_ai, inputs=image_input, outputs=output_text)
 
-if __name__ == "__main__":
-    demo.launch()
+demo.launch()