Use norfair uninitialized score history for tracked object and update false positive docs (#8299)

* Update docs

* Use norfair score history to start object history

* Formatting

frigate/object_processing.py

@@ -105,6 +105,10 @@ class TrackedObject:
     def __init__(
         self, camera, colormap, camera_config: CameraConfig, frame_cache, obj_data
     ):
+        # set the score history then remove as it is not part of object state
+        self.score_history = obj_data["score_history"]
+        del obj_data["score_history"]
+
         self.obj_data = obj_data
         self.camera = camera
         self.colormap = colormap
@@ -136,11 +140,8 @@ class TrackedObject:
         return self.computed_score < threshold
 
     def compute_score(self):
-        scores = self.score_history[:]
-        # pad with zeros if you dont have at least 3 scores
-        if len(scores) < 3:
-            scores += [0.0] * (3 - len(scores))
-        return median(scores)
+        """get median of scores for object."""
+        return median(self.score_history)
 
     def update(self, current_frame_time, obj_data):
         thumb_update = False
@@ -151,6 +152,7 @@ class TrackedObject:
             self.score_history.append(0.0)
         else:
             self.score_history.append(obj_data["score"])
+
         # only keep the last 10 scores
         if len(self.score_history) > 10:
             self.score_history = self.score_history[-10:]

frigate/track/norfair_tracker.py

@@ -97,6 +97,12 @@ class NorfairTracker(ObjectTracker):
         obj["start_time"] = obj["frame_time"]
         obj["motionless_count"] = 0
         obj["position_changes"] = 0
+        obj["score_history"] = [
+            p.data["score"]
+            for p in next(
+                (o for o in self.tracker.tracked_objects if o.global_id == track_id)
+            ).past_detections
+        ]
         self.tracked_objects[id] = obj
         self.disappeared[id] = 0
         self.positions[id] = {