Add lpr fps

frigate/data_processing/common/license_plate/mixin.py

@@ -24,6 +24,7 @@ from frigate.comms.event_metadata_updater import (
 from frigate.config.camera.camera import CameraTypeEnum
 from frigate.const import CLIPS_DIR
 from frigate.embeddings.onnx.lpr_embedding import LPR_EMBEDDING_SIZE
+from frigate.util.builtin import EventsPerSecond
 from frigate.util.image import area
 
 logger = logging.getLogger(__name__)
@@ -34,11 +35,12 @@ WRITE_DEBUG_IMAGES = False
 class LicensePlateProcessingMixin:
     def __init__(self, *args, **kwargs):
         super().__init__(*args, **kwargs)
-
+        self.plates_rec_second = EventsPerSecond()
+        self.plates_rec_second.start()
+        self.plates_det_second = EventsPerSecond()
+        self.plates_det_second.start()
         self.event_metadata_publisher = EventMetadataPublisher()
-
         self.ctc_decoder = CTCDecoder()
-
         self.batch_size = 6
 
         # Detection specific parameters
@@ -955,7 +957,9 @@ class LicensePlateProcessingMixin:
         """
         Update inference metrics.
         """
-        self.metrics.alpr_speed.value = (self.metrics.alpr_speed.value * 9 + duration) / 10
+        self.metrics.alpr_speed.value = (
+            self.metrics.alpr_speed.value * 9 + duration
+        ) / 10
 
     def _generate_plate_event(self, camera: str, plate: str, plate_score: float) -> str:
         """Generate a unique ID for a plate event based on camera and text."""
@@ -982,6 +986,8 @@ class LicensePlateProcessingMixin:
         self, obj_data: dict[str, any], frame: np.ndarray, dedicated_lpr: bool = False
     ):
         """Look for license plates in image."""
+        self.metrics.alpr_pps.value = self.plates_rec_second.eps()
+        self.metrics.yolov9_pps.value = self.plates_det_second.eps()
         camera = obj_data if dedicated_lpr else obj_data["camera"]
         current_time = int(datetime.datetime.now().timestamp())
 
@@ -1011,6 +1017,7 @@ class LicensePlateProcessingMixin:
             logger.debug(
                 f"{camera}: YOLOv9 LPD inference time: {(datetime.datetime.now().timestamp() - yolov9_start) * 1000:.2f} ms"
             )
+            self.plates_det_second.update()
             self.__update_yolov9_metrics(
                 datetime.datetime.now().timestamp() - yolov9_start
             )
@@ -1093,6 +1100,7 @@ class LicensePlateProcessingMixin:
                 logger.debug(
                     f"{camera}: YOLOv9 LPD inference time: {(datetime.datetime.now().timestamp() - yolov9_start) * 1000:.2f} ms"
                 )
+                self.plates_det_second.update()
                 self.__update_yolov9_metrics(
                     datetime.datetime.now().timestamp() - yolov9_start
                 )
@@ -1197,6 +1205,7 @@ class LicensePlateProcessingMixin:
         license_plates, confidences, areas = self._process_license_plate(
             camera, id, license_plate_frame
         )
+        self.plates_rec_second.update()
         self.__update_lpr_metrics(datetime.datetime.now().timestamp() - start)
 
         if license_plates:

frigate/data_processing/real_time/face.py

@@ -149,6 +149,7 @@ class FaceRealTimeProcessor(RealTimeProcessorApi):
         return face
 
     def __update_metrics(self, duration: float) -> None:
+        self.faces_per_second.update()
         self.metrics.face_rec_speed.value = (
             self.metrics.face_rec_speed.value * 9 + duration
         ) / 10
@@ -256,7 +257,6 @@ class FaceRealTimeProcessor(RealTimeProcessorApi):
                 max(0, face_box[0]) : min(frame.shape[1], face_box[2]),
             ]
 
-        self.faces_per_second.update()
         res = self.recognizer.classify(face_frame)
 
         if not res:

frigate/data_processing/types.py

@@ -11,7 +11,9 @@ class DataProcessorMetrics:
     face_rec_speed: Synchronized
     face_rec_fps: Synchronized
     alpr_speed: Synchronized
+    alpr_pps: Synchronized
     yolov9_lpr_speed: Synchronized
+    yolov9_lpr_pps: Synchronized
 
     def __init__(self):
         self.image_embeddings_speed = mp.Value("d", 0.01)
@@ -19,7 +21,9 @@ class DataProcessorMetrics:
         self.face_rec_speed = mp.Value("d", 0.01)
         self.face_rec_fps = mp.Value("d", 0.0)
         self.alpr_speed = mp.Value("d", 0.01)
+        self.alpr_pps = mp.Value("d", 0.0)
         self.yolov9_lpr_speed = mp.Value("d", 0.01)
+        self.yolov9_pps = mp.Value("d", 0.0)
 
 
 class DataProcessorModelRunner:

frigate/stats/util.py

@@ -305,19 +305,25 @@ def stats_snapshot(
             stats["embeddings"]["face_recognition_speed"] = round(
                 embeddings_metrics.face_rec_speed.value * 1000, 2
             )
-            stats["embeddings"]["face_recognition_fps"] = round(
+            stats["embeddings"]["face_recognition"] = round(
-                embeddings_metrics.face_rec_speed.value, 2
+                embeddings_metrics.face_rec_fps.value, 2
             )
 
         if config.lpr.enabled:
             stats["embeddings"]["plate_recognition_speed"] = round(
                 embeddings_metrics.alpr_speed.value * 1000, 2
             )
+            stats["embeddings"]["plate_recognition"] = round(
+                embeddings_metrics.alpr_pps.value, 2
+            )
 
             if "license_plate" not in config.objects.all_objects:
                 stats["embeddings"]["yolov9_plate_detection_speed"] = round(
                     embeddings_metrics.yolov9_lpr_speed.value * 1000, 2
                 )
+                stats["embeddings"]["yolov9_plate_detection"] = round(
+                    embeddings_metrics.yolov9_lpr_pps.value, 2
+                )
 
     get_processing_stats(config, stats, hwaccel_errors)