update

tracking/scripts/AB3DMOT_libs/kalman_filter.py

 # Author: Xinshuo Weng
 # email: xinshuo.weng@gmail.com
-import math
+
 import numpy as np
 from filterpy.kalman import KalmanFilter
-from sklearn.decomposition import PCA
-
 
 
 class KalmanBoxTracker(object):
@@ -85,7 +83,6 @@ class KalmanBoxTracker(object):
         """
         Updates the state vector with observed bbox.
         """
-
         self.time_since_update = 0
         self.history = []
         self.hits += 1
@@ -128,7 +125,6 @@ class KalmanBoxTracker(object):
         """
         Advances the state vector and returns the predicted bounding box estimate.
         """
-
         self.kf.predict()
         if self.kf.x[3] >= np.pi: self.kf.x[3] -= np.pi * 2
         if self.kf.x[3] < -np.pi: self.kf.x[3] += np.pi * 2

tracking/scripts/utils/demo_ww.py

@@ -54,18 +54,6 @@ def get_T():
   return Trans
 
 
-def get_loc_GT(lidar_loc):
-
-  Trans = get_T()
-  tmp_loc = np.ones([4])
-  tmp_loc[:3] = lidar_loc[:3]
-  world_loc = np.dot(Trans,tmp_loc)
-
-  out_BL = Inverse_v2(world_loc[:2])
-  
-  return out_BL
-
-
 def get_loc(boxes_3d, car_type):
   corners_3d = my_compute_box_3d(boxes_3d[:3],boxes_3d[6],boxes_3d[3:6])
 
@@ -99,5 +87,3 @@ def get_loc(boxes_3d, car_type):
   out_center_BL = Inverse_v2(world_center_loc[:2])
   
   return lidar_loc, out_BL, out_center_BL
-  
-  return lidar_loc,out_BL