Implement state verification

frigate/data_processing/real_time/custom_classification.py

@@ -53,6 +53,7 @@ class CustomStateClassificationProcessor(RealTimeProcessorApi):
         self.tensor_output_details: dict[str, Any] | None = None
         self.labelmap: dict[int, str] = {}
         self.classifications_per_second = EventsPerSecond()
+        self.state_history: dict[str, dict[str, Any]] = {}
 
         if (
             self.metrics
@@ -94,6 +95,42 @@ class CustomStateClassificationProcessor(RealTimeProcessorApi):
         if self.inference_speed:
             self.inference_speed.update(duration)
 
+    def verify_state_change(self, camera: str, detected_state: str) -> str | None:
+        """
+        Verify state change requires 3 consecutive identical states before publishing.
+        Returns state to publish or None if verification not complete.
+        """
+        if camera not in self.state_history:
+            self.state_history[camera] = {
+                "current_state": None,
+                "pending_state": None,
+                "consecutive_count": 0,
+            }
+
+        verification = self.state_history[camera]
+
+        if detected_state == verification["current_state"]:
+            verification["pending_state"] = None
+            verification["consecutive_count"] = 0
+            return None
+
+        if detected_state == verification["pending_state"]:
+            verification["consecutive_count"] += 1
+
+            if verification["consecutive_count"] >= 3:
+                verification["current_state"] = detected_state
+                verification["pending_state"] = None
+                verification["consecutive_count"] = 0
+                return detected_state
+        else:
+            verification["pending_state"] = detected_state
+            verification["consecutive_count"] = 1
+            logger.debug(
+                f"New state '{detected_state}' detected for {camera}, need {3 - verification['consecutive_count']} more consecutive detections"
+            )
+
+        return None
+
     def process_frame(self, frame_data: dict[str, Any], frame: np.ndarray):
         if self.metrics and self.model_config.name in self.metrics.classification_cps:
             self.metrics.classification_cps[
@@ -131,6 +168,19 @@ class CustomStateClassificationProcessor(RealTimeProcessorApi):
                 self.last_run = now
                 should_run = True
 
+        # Shortcut: always run if we have a pending state verification to complete
+        if (
+            not should_run
+            and camera in self.state_history
+            and self.state_history[camera]["pending_state"] is not None
+            and now > self.last_run + 0.5
+        ):
+            self.last_run = now
+            should_run = True
+            logger.debug(
+                f"Running verification check for pending state: {self.state_history[camera]['pending_state']} ({self.state_history[camera]['consecutive_count']}/3)"
+            )
+
         if not should_run:
             return
 
@@ -188,10 +238,19 @@ class CustomStateClassificationProcessor(RealTimeProcessorApi):
             score,
         )
 
-        if score >= self.model_config.threshold:
+        if score < self.model_config.threshold:
+            logger.debug(
+                f"Score {score} below threshold {self.model_config.threshold}, skipping verification"
+            )
+            return
+
+        detected_state = self.labelmap[best_id]
+        verified_state = self.verify_state_change(camera, detected_state)
+
+        if verified_state is not None:
             self.requestor.send_data(
                 f"{camera}/classification/{self.model_config.name}",
-                self.labelmap[best_id],
+                verified_state,
             )
 
     def handle_request(self, topic, request_data):