From 7f4b27a556cbd604baf2c42a27acf588d39f866e Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Wed, 27 Dec 2023 21:09:25 +0000
Subject: [PATCH] =?UTF-8?q?fix(pre=5Fcommit):=20=F0=9F=8E=A8=20auto=20form?=
 =?UTF-8?q?at=20pre-commit=20hooks?=
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---
 supervision/__init__.py           |  2 +-
 supervision/detection/smoother.py | 29 +++++++++++++++--------------
 2 files changed, 16 insertions(+), 15 deletions(-)

diff --git a/supervision/__init__.py b/supervision/__init__.py
index 7e34c0f4..ef9327df 100644
--- a/supervision/__init__.py
+++ b/supervision/__init__.py
@@ -32,8 +32,8 @@ from supervision.dataset.core import (
 )
 from supervision.detection.annotate import BoxAnnotator
 from supervision.detection.core import Detections
-from supervision.detection.smoother import Smoother
 from supervision.detection.line_counter import LineZone, LineZoneAnnotator
+from supervision.detection.smoother import Smoother
 from supervision.detection.tools.inference_slicer import InferenceSlicer
 from supervision.detection.tools.polygon_zone import PolygonZone, PolygonZoneAnnotator
 from supervision.detection.utils import (
diff --git a/supervision/detection/smoother.py b/supervision/detection/smoother.py
index 5559903d..21c9101b 100644
--- a/supervision/detection/smoother.py
+++ b/supervision/detection/smoother.py
@@ -1,7 +1,10 @@
 from collections import defaultdict
+
 import numpy as np
+
 from supervision.detection.core import Detections
 
+
 class Smoother:
     """
     A class for smoothing out noise in predictions over time by using a Tracker
@@ -33,11 +36,11 @@ class Smoother:
 
         # Run a tracker to link predictions across frames
         detections = byte_tracker.update_with_detections(detections)
-        
+
         # Record the new frame and get the smoothed predictions
         smoother.add_frame(detections)
         smoothed_detections = smoother.get_smoothed_detections()
-        
+
         # Render
         image_smoothed = box_annotator.annotate(scene=image.copy(), detections=smoothed_detections)
 
@@ -63,10 +66,7 @@ class Smoother:
         tracking into your inference pipeline.
     """
 
-    def __init__(
-        self,
-        length: int = 5
-    ) -> None:
+    def __init__(self, length: int = 5) -> None:
         """
         Args:
             length (int): The current count of detected objects within the zone
@@ -103,21 +103,21 @@ class Smoother:
                 # initialize a new tracker_id
                 self.tracks[tracker_id] = []
                 self.track_starts[tracker_id] = self.current_frame
-            
+
             self.tracks[tracker_id].append(detections[detection_idx])
             self.track_ends[tracker_id] = self.current_frame
-        
+
         for track_id in self.tracks:
             track = self.tracks[track_id]
             if self.track_ends[track_id] < self.current_frame:
                 # continue tracking for a few frames after the object has left
                 # (to prevent flickering in case it comes back)
                 track.append(None)
-            
+
             if len(track) > self.length:
                 # remove the oldest detection from the track it's too long
                 track.pop(0)
-    
+
     def get_track(self, track_id):
         track = self.tracks[track_id]
         if track is None:
@@ -126,12 +126,12 @@ class Smoother:
         track = [d for d in track if d is not None]
         if len(track) == 0:
             return None
-        
+
         ret = track[0]
         # set to an average of all the detection boxes
         ret.xyxy = np.mean([d.xyxy for d in track], axis=0)
         ret.confidence = np.mean([d.confidence for d in track], axis=0)
-        
+
         return ret
 
     def get_smoothed_detections(self):
@@ -147,9 +147,10 @@ class Smoother:
             track = self.get_track(track_id)
             if track is not None:
                 tracked_detections.append(track)
-        
+
         return Detections.merge(tracked_detections)
 
+
 class NoneDict(defaultdict):
     """
     Helper class that returns None instead of raising a KeyError
@@ -163,4 +164,4 @@ class NoneDict(defaultdict):
         try:
             return super(NoneDict, self).__getitem__(key)
         except KeyError:
-            return None
\ No newline at end of file
+            return None