def run(self):
obj_xyzvels = self.get_obj_list()
for bd_id, xyzvel in obj_xyzvels.items():
cur_pos = xyzvel[['center_x', 'center_y']].iloc[0].values
cur_vel = xyzvel[['speed_x', 'speed_y']].iloc[0].values
pred_duration = 5
kf = KalmanFilter()
kf.motion_model(cur_pos, cur_vel, pred_duration)
return
def predict(self, obj_xyzvels):
#TODO: Write a function that given the data, predits the position of an object at given time period.
res = {}
for bd_id, xyzvel in obj_xyzvels.items():
cur_pos = xyzvel[['center_x', 'center_y']].iloc[0].values
cur_vel = xyzvel[['speed_x', 'speed_y']].iloc[0].values
cur_time = xyzvel[['frame_id']].iloc[0].values[0]
pred_duration = 5
kf = KalmanFilter()
pred_xys = kf.motion_model(cur_pos, cur_vel, pred_duration,
cur_time)
res[bd_id] = pred_xys
return res
