fix(pre_commit): 🎨 auto format pre-commit hooks

Author: pre-commit-ci[bot]

trackers/core/botsort/__init__.py

@@ -5,4 +5,4 @@
 # ------------------------------------------------------------------------
 from .tracker import BoTSORTTracker
 
-__all__ = ["BoTSORTTracker"]
+__all__ = ["BoTSORTTracker"]

trackers/core/botsort/cmc.py

@@ -6,12 +6,12 @@
 
 from __future__ import annotations
 
+import copy
 from dataclasses import dataclass
 from typing import Optional
 
-import copy
-import numpy as np
 import cv2
+import numpy as np
 
 
 @dataclass
@@ -48,7 +48,9 @@ def reset(self) -> None:
         self._prev_kps = None
         self._prev_desc = None
 
-    def estimate(self, frame_bgr: np.ndarray, dets_xyxy: Optional[np.ndarray] = None) -> np.ndarray:
+    def estimate(
+        self, frame_bgr: np.ndarray, dets_xyxy: Optional[np.ndarray] = None
+    ) -> np.ndarray:
         if frame_bgr is None:
             return np.eye(2, 3, dtype=np.float32)
 
@@ -105,7 +107,9 @@ def estimate(self, frame_bgr: np.ndarray, dets_xyxy: Optional[np.ndarray] = None
             self._prev_desc = copy.copy(desc)
             return H_aff
 
-        max_spatial = self.cfg.max_spatial_distance_frac * np.array([W, H], dtype=np.float32)
+        max_spatial = self.cfg.max_spatial_distance_frac * np.array(
+            [W, H], dtype=np.float32
+        )
 
         prev_pts = []
         curr_pts = []
@@ -173,7 +177,9 @@ def apply_to_tracks(tracks: list, H: np.ndarray) -> None:
         A8[0:4, 0:4] = A4
         A8[4:8, 4:8] = A4
 
-        trans4 = np.array([t[0, 0], t[1, 0], t[0, 0], t[1, 0]], dtype=np.float32).reshape(4, 1)
+        trans4 = np.array(
+            [t[0, 0], t[1, 0], t[0, 0], t[1, 0]], dtype=np.float32
+        ).reshape(4, 1)
 
         for trk in tracks:
             trk.state = (A8 @ trk.state).astype(np.float32)

trackers/core/botsort/kalman_box_tracker.py

@@ -6,6 +6,7 @@
 
 import numpy as np
 
+
 class BoTSORTKalmanBoxTracker:
     """
     The `BoTSORTKalmanBoxTracker` class represents the internals of a single

trackers/core/botsort/tracker.py

@@ -12,12 +12,13 @@
 from scipy.optimize import linear_sum_assignment
 
 from trackers.core.base import BaseTracker
+from trackers.core.botsort.cmc import CMC, CMCConfig
 from trackers.core.botsort.kalman_box_tracker import BoTSORTKalmanBoxTracker
 from trackers.utils.sort_utils import (
     get_alive_trackers,
     get_iou_matrix,
 )
-from trackers.core.botsort.cmc import CMC, CMCConfig
+
 
 class BoTSORTTracker(BaseTracker):
     def __init__(
@@ -28,8 +29,7 @@ def __init__(
         minimum_consecutive_frames: int = 2,
         minimum_iou_threshold: float = 0.1,
         high_conf_det_threshold: float = 0.6,
-        enable_cmc: bool = True
-
+        enable_cmc: bool = True,
     ) -> None:
         # Calculate maximum frames without update based on lost_track_buffer and
         # frame_rate. This scales the buffer based on the frame rate to ensure
@@ -94,7 +94,9 @@ def update(
 
         # CMC (ORB) apply to all predicted tracks before association
         if self.enable_cmc and self.cmc is not None and frame is not None:
-            mask_boxes = high_prob_detections.xyxy if len(high_prob_detections) > 0 else None
+            mask_boxes = (
+                high_prob_detections.xyxy if len(high_prob_detections) > 0 else None
+            )
             H = self.cmc.estimate(frame, mask_boxes)
             self.cmc.apply_to_tracks(self.tracks, H)