Update app.py

app.py

@@ -1,21 +1,52 @@
 import gradio as gr
-from PIL import Image
 from transformers import pipeline
+from PIL import Image
+
+# Model utama untuk deteksi real vs AI
+detector = pipeline("image-classification", model="umm-maybe/AI-image-detector")
+
+# Model tambahan general classifier (backup)
+general = pipeline("image-classification", model="google/vit-base-patch16-224")
+
+def detect_image(img):
+    try:
+        # Prediksi dengan AI detector
+        result1 = detector(img)
+        label1 = result1[0]['label']
+        conf1 = round(result1[0]['score'] * 100, 2)
+
+        # Prediksi dengan model general (untuk cek ganda)
+        result2 = general(img)
+        label2 = result2[0]['label']
+        conf2 = round(result2[0]['score'] * 100, 2)
+
+        # Logika sederhana untuk memutuskan hasil
+        if "fake" in label1.lower() or "artificial" in label1.lower():
+            final = f"⚠️ Kemungkinan Besar AI Generated ({conf1}%)"
+        elif "real" in label1.lower():
+            final = f"✅ Kemungkinan Besar Foto Asli ({conf1}%)"
+        else:
+            final = f"⚠️ Tidak Pasti (cek manual)"
+
+        output = f"""
+### Hasil Deteksi:
+{final}
+
+**Model AI-detector:** {label1} ({conf1}%)
+**Model General (ViT):** {label2} ({conf2}%)
+"""
+        return output
+    except Exception as e:
+        return f"Terjadi error: {str(e)}"
+
+# UI Gradio
+iface = gr.Interface(
+    fn=detect_image,
+    inputs=gr.Image(type="pil"),
+    outputs="markdown",
+    title="AI vs Real Image Detector",
+    description="Upload foto untuk mendeteksi apakah gambar kemungkinan besar asli atau hasil AI."
+)
 
-# Muat model deteksi AI
-classifier = pipeline("image-classification", model="umm-maybe/AI-image-detector")
-
-def detect_image(image: Image.Image):
-    result = classifier(image)
-    ai_score = result[0]['score'] if result[0]['label'] == 'AI-generated' else 0
-    human_score = 1 - ai_score
-    if ai_score == 1:
-        return f"Gambar ini 100% dihasilkan oleh AI."
-    elif human_score == 1:
-        return f"Gambar ini 100% asli."
-    else:
-        return f"Gambar ini {ai_score*100:.2f}% dihasilkan oleh AI dan {human_score*100:.2f}% asli."
-
-# Antarmuka Gradio
-iface = gr.Interface(fn=detect_image, inputs=gr.Image(type="pil"), outputs="text")
-iface.launch()
+if __name__ == "__main__":
+    iface.launch()