--- a/trafficintelligence/storage.py	Thu Mar 16 17:03:18 2023 -0400
+++ b/trafficintelligence/storage.py	Wed Mar 22 15:40:33 2023 -0400
@@ -1351,18 +1351,20 @@
     data = data[data.trackingid > -1]
 
     objects = []
+    featureNum = 0
     for objNum in data.trackingid.unique():
         tmp = data[data.trackingid == objNum].sort_values('frame')
         t = moving.Trajectory()#([[float(numbers[6])],[float(numbers[7])]])
+        featureTrajectories = [moving.Trajectory() for i in range(4)]
         for i, r in tmp.iterrows():
             _, Tr_imu2w = oxts[r.frame]
-            transfer_matrix = {'P2': reshape(kittiCalibration['P2'], (3, 4)),
-                               'R_rect': kittiCalibration['R_rect'],
-                               'Tr_cam_to_velo': kittiCalibration['Tr_cam_velo'],
-                               # transfer_matrix['Tr_velo_to_cam'] = kittiCalibration['Tr_velo_to_cam']
-                               'Tr_velo_to_imu': kittiCalibration['Tr_velo_imu'],
-                               # transfer_matrix['Tr_imu_to_velo'] = kittiCalibration['Tr_imu_to_velo']
-                               'Tr_imu_to_world': Tr_imu2w}
+            # transfer_matrix = {'P2': reshape(kittiCalibration['P2'], (3, 4)),
+            #                    'R_rect': kittiCalibration['R_rect'],
+            #                    'Tr_cam_to_velo': kittiCalibration['Tr_cam_velo'],
+            #                    # transfer_matrix['Tr_velo_to_cam'] = kittiCalibration['Tr_velo_to_cam']
+            #                    'Tr_velo_to_imu': kittiCalibration['Tr_velo_imu'],
+            #                    # transfer_matrix['Tr_imu_to_velo'] = kittiCalibration['Tr_imu_to_velo']
+            #                    'Tr_imu_to_world': Tr_imu2w}
             # 3D object
             # compute rotational matrix around yaw axis
             R = roty(r.ry)
@@ -1380,24 +1382,27 @@
             # box3d_pts_3d_velo = calib.project_rect_to_velo(box3d_pts_3d)
             veloCorners = transpose(dot(invR0, corners3d)) # 8x3 avoid double transpose np.transpose(pts_3d_rect)))
             #             boxes3d_world_single, flag_imu, flag_world = calib_function.project_velo_to_world(bboxes_3d_velo=boxes3d_velo_single, Tr_matrix=transfer_matrix)
-            Tr_velo_to_imu = transfer_matrix['Tr_velo_to_imu']
-            Tr_imu_to_world = transfer_matrix['Tr_imu_to_world']
+            #Tr_velo_to_imu = transfer_matrix['Tr_velo_to_imu']
+            #Tr_imu_to_world = transfer_matrix['Tr_imu_to_world']
             homVeloCorners = ones((veloCorners.shape[0], veloCorners.shape[1]+1))
             homVeloCorners[:,:-1] = veloCorners # 8x4 with ones in last column
-            imuCorners = dot(Tr_velo_to_imu, homVeloCorners.T).T # 8x3
+            imuCorners = dot(kittiCalibration['Tr_velo_imu'], homVeloCorners.T).T # 8x3
 
             homImuCorners = ones((imuCorners.shape[0], imuCorners.shape[1]+1))
             homImuCorners[:,:-1] = imuCorners # 8x4 with ones in last column
-            worldCorners = dot(Tr_imu_to_world, homImuCorners.T).T # 8x3
+            worldCorners = dot(Tr_imu2w, homImuCorners.T).T # 8x3
             
             # take first 4 lines of corners, x,y,_ # x0, y0, _ = boxes3d[0]
             xCoords = worldCorners[:4,0]
             yCoords = worldCorners[:4,1]
             t.addPositionXY(xCoords.mean(), yCoords.mean())
+            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
-        objects.append(moving.MovingObject(num = objNum, timeInterval = moving.TimeInterval(tmp.frame.min(), tmp.frame.max()),
-                                           positions = t,
-                                           userType = tmp.iloc[0].type))
+        newObj = moving.MovingObject(num = objNum, timeInterval = moving.TimeInterval(tmp.frame.min(), tmp.frame.max()), positions = t, userType = tmp.iloc[0].type, features = [moving.MovingObject(num = featureNum+i, timeInterval = moving.TimeInterval(tmp.frame.min(), tmp.frame.max()), positions = featureTrajectories[i]) for i in range(4)])
+        #newObj.featureNumbers = [f.getNum() for f in newObj.getFeatures()]
+        objects.append(newObj)
+        featureNum += 4
     return objects
 
 def convertNgsimFile(inputfile, outputfile, append = False, nObjects = -1, sequenceNum = 0):