Update app.py

app.py

@@ -28,12 +28,15 @@ color_map = {
 def predict_segmentation(image_pil):
     image_pil = image_pil.convert("RGB")
     image_np = np.array(image_pil)
-
     results = model.predict(image_pil, conf=0.25, iou=0.5)
     result = results[0]
 
-    if result.masks is None:
-        return image_pil
+    # Jika tidak ada deteksi sama sekali
+    if result.boxes is None or len(result.boxes) == 0 or result.masks is None:
+        image_np = np.array(image_pil)
+        overlay = image_np.copy()
+        cv2.putText(overlay, "No detection found", (30, 50), cv2.FONT_HERSHEY_SIMPLEX, 1.2, (0, 0, 255), 3)
+        return Image.fromarray(overlay)
 
     masks = result.masks.data.cpu().numpy()
     boxes = result.boxes.xyxy.cpu().numpy()
@@ -53,20 +56,18 @@ def predict_segmentation(image_pil):
         for c in range(3):
             overlay[:, :, c] = np.where(mask > 0, overlay[:, :, c] * 0.5 + color[c] * 0.5, overlay[:, :, c])
 
-        # Gambar bounding box
+        # Gambar bounding box dan label
         cv2.rectangle(overlay, (box[0], box[1]), (box[2], box[3]), color, 2)
-
-        # Label + score
         text = f"{label} {score:.2f}"
         cv2.putText(overlay, text, (box[0], box[1] - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.6, color, 2)
 
-    # Tambah legend
+    # Tambahkan legend
     legend_height = 60
     h, w, _ = overlay.shape
     combined = np.ones((h + legend_height, w, 3), dtype=np.uint8) * 255
     combined[:h] = overlay
 
-    # Gambar legenda
+    # Legend
     x = 10
     for cid, label in label_map.items():
         color = color_map[cid]
@@ -82,7 +83,7 @@ iface = gr.Interface(
     inputs=gr.Image(type="pil"),
     outputs=gr.Image(type="pil"),
     title="YOLOv8 Segmentasi Sonar",
-    description="Upload citra Side Scan Sonar. Akan ditampilkan: mask, bounding box, confidence score, dan legenda kelas."
+    description="Upload citra Side Scan Sonar. Jika terdeteksi objek, akan ditampilkan mask, box, dan confidence. Jika tidak, akan muncul pesan."
 )
 
 if __name__ == "__main__":