use resize frame

pyroengine/engine.py

@@ -256,13 +256,14 @@ def predict(self, frame: Image.Image, cam_id: Optional[str] = None) -> float:
         cam_key = cam_id or "-1"
         # Reduce image size to save bandwidth
         if isinstance(self.frame_size, tuple):
-            frame_resize = frame.resize(self.frame_size[::-1], getattr(Image, "BILINEAR"))
-        else:
-            frame_resize = frame
+            frame = frame.resize(self.frame_size[::-1], getattr(Image, "BILINEAR"))
 
         # Inference with ONNX
         preds = self.model(frame.convert("RGB"), self.occlusion_masks[cam_key])
-        conf = self._update_states(frame_resize, preds, cam_key)
+        conf = self._update_states(frame, preds, cam_key)
+
+        if self.save_captured_frames:
+            self._local_backup(frame, cam_id, is_alert=False)
 
         # Log analysis result
         device_str = f"Camera '{cam_id}' - " if isinstance(cam_id, str) else ""
@@ -285,9 +286,6 @@ def predict(self, frame: Image.Image, cam_id: Optional[str] = None) -> float:
             self._dump_cache()
             self.last_cache_dump = ts
 
-        if self.save_captured_frames:
-            self._local_backup(frame_resize, cam_id, is_alert=False)
-
         return float(conf)
 
     def _stage_alert(self, frame: Image.Image, cam_id: str, ts: int, localization: list) -> None: