Refactor processors and add LPR postprocessing (#16722)

* recordings data pub/sub

* function to process recording stream frames

* model runner

* lpr model runner

* refactor to mixin class and use model runner

* separate out realtime and post processors

* move model and mixin folders

* basic postprocessor

* clean up

* docs

* postprocessing logic

* clean up

* return none if recordings are disabled

* run postprocessor handle_requests too

* tweak expansion

* add put endpoint

* postprocessor tweaks with endpoint

frigate/data_processing/common/license_plate/model.py

@@ -0,0 +1,31 @@
+from frigate.embeddings.onnx.lpr_embedding import (
+    LicensePlateDetector,
+    PaddleOCRClassification,
+    PaddleOCRDetection,
+    PaddleOCRRecognition,
+)
+
+from ...types import DataProcessorModelRunner
+
+
+class LicensePlateModelRunner(DataProcessorModelRunner):
+    def __init__(self, requestor, device: str = "CPU", model_size: str = "large"):
+        super().__init__(requestor, device, model_size)
+        self.detection_model = PaddleOCRDetection(
+            model_size=model_size, requestor=requestor, device=device
+        )
+        self.classification_model = PaddleOCRClassification(
+            model_size=model_size, requestor=requestor, device=device
+        )
+        self.recognition_model = PaddleOCRRecognition(
+            model_size=model_size, requestor=requestor, device=device
+        )
+        self.yolov9_detection_model = LicensePlateDetector(
+            model_size=model_size, requestor=requestor, device=device
+        )
+
+        # Load all models once
+        self.detection_model._load_model_and_utils()
+        self.classification_model._load_model_and_utils()
+        self.recognition_model._load_model_and_utils()
+        self.yolov9_detection_model._load_model_and_utils()