feat: add fallback when cant initially detect but backend start session

core/tracking/integration.py

@@ -411,27 +411,12 @@ class TrackingPipelineIntegration:
             logger.info(f"Executing processing phase for session {session_id}, vehicle {vehicle.track_id}")
 
             # Capture high-quality snapshot for pipeline processing
-            frame = None
-            if self.subscription_info and self.subscription_info.stream_config.snapshot_url:
-                from ..streaming.readers import HTTPSnapshotReader
+            logger.info(f"[PROCESSING PHASE] Fetching 2K snapshot for session {session_id}")
+            frame = self._fetch_snapshot()
 
-                logger.info(f"[PROCESSING PHASE] Fetching 2K snapshot for session {session_id}")
-                snapshot_reader = HTTPSnapshotReader(
-                    camera_id=self.subscription_info.camera_id,
-                    snapshot_url=self.subscription_info.stream_config.snapshot_url,
-                    max_retries=3
-                )
-
-                frame = snapshot_reader.fetch_single_snapshot()
-
-                if frame is not None:
-                    logger.info(f"[PROCESSING PHASE] Successfully fetched {frame.shape[1]}x{frame.shape[0]} snapshot for pipeline")
-                else:
-                    logger.warning(f"[PROCESSING PHASE] Failed to capture snapshot, falling back to RTSP frame")
-                    # Fall back to RTSP frame if snapshot fails
-                    frame = processing_data['frame']
-            else:
-                logger.warning(f"[PROCESSING PHASE] No snapshot URL available, using RTSP frame")
+            if frame is None:
+                logger.warning(f"[PROCESSING PHASE] Failed to capture snapshot, falling back to RTSP frame")
+                # Fall back to RTSP frame if snapshot fails
                 frame = processing_data['frame']
 
             # Extract detected regions from detection phase result if available
@@ -527,6 +512,19 @@ class TrackingPipelineIntegration:
         else:
             logger.warning(f"No pending processing data found for display {display_id} when setting session {session_id}")
 
+            # FALLBACK: Execute pipeline for POS-initiated sessions
+            logger.info(f"[FALLBACK] Triggering fallback pipeline for session {session_id} on display {display_id}")
+
+            # Create subscription_id for fallback (needed for pipeline execution)
+            fallback_subscription_id = f"{display_id};fallback"
+
+            # Trigger the fallback pipeline asynchronously
+            asyncio.create_task(self._execute_fallback_pipeline(
+                display_id=display_id,
+                session_id=session_id,
+                subscription_id=fallback_subscription_id
+            ))
+
     def clear_session_id(self, session_id: str):
         """
         Clear session ID (post-fueling).
@@ -676,6 +674,104 @@ class TrackingPipelineIntegration:
         if stage == "car_wait_staff":
             logger.info(f"Started monitoring session {session_id} for car abandonment")
 
+    def _fetch_snapshot(self) -> Optional[np.ndarray]:
+        """
+        Fetch high-quality snapshot from camera's snapshot URL.
+        Reusable method for both processing phase and fallback pipeline.
+
+        Returns:
+            Snapshot frame or None if unavailable
+        """
+        if not (self.subscription_info and self.subscription_info.stream_config.snapshot_url):
+            logger.warning("[SNAPSHOT] No subscription info or snapshot URL available")
+            return None
+
+        try:
+            from ..streaming.readers import HTTPSnapshotReader
+
+            logger.info(f"[SNAPSHOT] Fetching snapshot for {self.subscription_info.camera_id}")
+            snapshot_reader = HTTPSnapshotReader(
+                camera_id=self.subscription_info.camera_id,
+                snapshot_url=self.subscription_info.stream_config.snapshot_url,
+                max_retries=3
+            )
+
+            frame = snapshot_reader.fetch_single_snapshot()
+
+            if frame is not None:
+                logger.info(f"[SNAPSHOT] Successfully fetched {frame.shape[1]}x{frame.shape[0]} snapshot")
+                return frame
+            else:
+                logger.warning("[SNAPSHOT] Failed to fetch snapshot")
+                return None
+
+        except Exception as e:
+            logger.error(f"[SNAPSHOT] Error fetching snapshot: {e}", exc_info=True)
+            return None
+
+    async def _execute_fallback_pipeline(self, display_id: str, session_id: str, subscription_id: str):
+        """
+        Execute fallback pipeline when sessionId is received without prior detection.
+        This handles POS-initiated sessions where backend starts transaction before car detection.
+
+        Args:
+            display_id: Display identifier
+            session_id: Session ID from backend
+            subscription_id: Subscription identifier for pipeline execution
+        """
+        try:
+            logger.info(f"[FALLBACK PIPELINE] Executing for session {session_id}, display {display_id}")
+
+            # Fetch fresh snapshot from camera
+            frame = self._fetch_snapshot()
+
+            if frame is None:
+                logger.error(f"[FALLBACK] Failed to fetch snapshot for session {session_id}, cannot execute pipeline")
+                return
+
+            logger.info(f"[FALLBACK] Using snapshot frame {frame.shape[1]}x{frame.shape[0]} for session {session_id}")
+
+            # Check if detection pipeline is available
+            if not self.detection_pipeline:
+                logger.error(f"[FALLBACK] Detection pipeline not available for session {session_id}")
+                return
+
+            # Execute detection phase to get detected regions
+            detection_result = await self.detection_pipeline.execute_detection_phase(
+                frame=frame,
+                display_id=display_id,
+                subscription_id=subscription_id
+            )
+
+            logger.info(f"[FALLBACK] Detection phase completed for session {session_id}: "
+                       f"status={detection_result.get('status', 'unknown')}, "
+                       f"regions={list(detection_result.get('detected_regions', {}).keys())}")
+
+            # If detection found regions, execute processing phase
+            detected_regions = detection_result.get('detected_regions', {})
+            if detected_regions:
+                processing_result = await self.detection_pipeline.execute_processing_phase(
+                    frame=frame,
+                    display_id=display_id,
+                    session_id=session_id,
+                    subscription_id=subscription_id,
+                    detected_regions=detected_regions
+                )
+
+                logger.info(f"[FALLBACK] Processing phase completed for session {session_id}: "
+                           f"status={processing_result.get('status', 'unknown')}, "
+                           f"branches={len(processing_result.get('branch_results', {}))}, "
+                           f"actions={len(processing_result.get('actions_executed', []))}")
+
+                # Update statistics
+                self.stats['pipelines_executed'] += 1
+
+            else:
+                logger.warning(f"[FALLBACK] No detections found in snapshot for session {session_id}")
+
+        except Exception as e:
+            logger.error(f"[FALLBACK] Error executing fallback pipeline for session {session_id}: {e}", exc_info=True)
+
     def _filter_small_frontals(self, tracking_results, frame):
         """
         Filter out frontal detections that are smaller than minimum bbox area percentage.