--- a/trafficintelligence/moving.py	Thu Apr 20 11:46:42 2023 -0400
+++ b/trafficintelligence/moving.py	Wed Apr 26 18:33:46 2023 -0400
@@ -4,7 +4,7 @@
 import copy
 from math import sqrt, atan2, cos, sin
 
-from numpy import median, mean, array, arange, zeros, ones, hypot, NaN, std, floor, ceil, float32, argwhere, minimum
+from numpy import median, mean, array, arange, zeros, ones, hypot, NaN, std, floor, ceil, float32, argwhere, minimum,  issubdtype, integer as npinteger
 from matplotlib.pyplot import plot, text
 from scipy.stats import scoreatpercentile
 from scipy.spatial.distance import cdist
@@ -720,7 +720,7 @@
         return self.__len__() == 0
 
     def __getitem__(self, i):
-        if isinstance(i, int):
+        if isinstance(i, int) or issubdtype(i, npinteger):
             return Point(self.positions[0][i], self.positions[1][i])
         elif isinstance(i, slice):
             return Trajectory([self.positions[0][i],self.positions[1][i]])

--- a/trafficintelligence/storage.py	Thu Apr 20 11:46:42 2023 -0400
+++ b/trafficintelligence/storage.py	Wed Apr 26 18:33:46 2023 -0400
@@ -1313,7 +1313,7 @@
     
     header = ['frame', # 0, 1, ..., n
               'trackingid', # -1, 0 , 1, ..., k
-              'type',  # 'Car', 'Pedestrian', ...
+              'usertype',  # 'Car', 'Pedestrian', ...
               'truncation', # truncated pixel ratio [0..1]
               'occlusion', # 0=visible, 1=partly occluded, 2=fully occluded, 3=unknown
               'alpha', # object observation angle [-pi..pi]
@@ -1381,7 +1381,8 @@
             for i in range(4):
                 featureTrajectories[i].addPositionXY(xCoords[i], yCoords[i])                
             # check https://docs.opencv.org/3.4/d9/d0c/group__calib3d.html#ga1019495a2c8d1743ed5cc23fa0daff8c
-        newObj = moving.MovingObject(num = objNum, timeInterval = moving.TimeInterval(int(tmp.frame.min()), int(tmp.frame.max())), positions = t, userType = tmp.iloc[0].type, features = [moving.MovingObject(num = featureNum+i, timeInterval = moving.TimeInterval(int(tmp.frame.min()), int(tmp.frame.max())), positions = featureTrajectories[i]) for i in range(4)])
+        
+        newObj = moving.MovingObject(num = objNum, timeInterval = moving.TimeInterval(int(tmp.frame.min()), int(tmp.frame.max())), positions = t, velocities = t.differentiate(True), userType = tmp.iloc[0].usertype, features = [moving.MovingObject(num = featureNum+i, timeInterval = moving.TimeInterval(int(tmp.frame.min()), int(tmp.frame.max())), positions = featureTrajectories[i], velocities = featureTrajectories[i].differentiate(True)) for i in range(4)])
         objects.append(newObj)
         featureNum += 4
     return objects