pyfast_adt.main.tracking.KF_custom_models
Classes
Module Contents
- class pyfast_adt.main.tracking.KF_custom_models.ukf_2D(dt=1, x_std_P=500, y_std_P=500, x_std_R=100, y_std_R=100, noise_std_Q=100, pos_x0=0, pos_y0=0)
- dt
- x_std_P
- y_std_P
- x_std_R
- y_std_R
- noise_std_Q
- pos_x0
- pos_y0
- points
- kf
- f_track(x, dt)
state transition function for nonlinear kf x is a vector as [x, dx, y, dy]
- h_track(z)
measurement function for nonlinear kf.
- predict()
- update(z)
- run(path)
this function run the model on a custom dataset provided by the path argument where a path of a txt file containing the X,Y coordinates of the tracked object
- class pyfast_adt.main.tracking.KF_custom_models.ukf_4D(dt=1, x_std_P=500, y_std_P=500, x_std_R=100, y_std_R=100, noise_std_Q=100, pos_x0=0, pos_y0=0, vel_x0=0.0, vel_y0=0.0, vel_std_P=10.0)
- dt
- x_std_P
- y_std_P
- vel_std_P
- x_std_R
- y_std_R
- noise_std_Q
- pos_x0
- pos_y0
- vel_x0
- vel_y0
- points
- kf
- f_track(x, dt)
state transition function for nonlinear kf x is a vector as [x, dx, y, dy]
- h_track(z)
measurement function for nonlinear kf.
- predict()
- update(z)
- run(path)
- class pyfast_adt.main.tracking.KF_custom_models.ukf_6D(dt=1, x_std_P=500, y_std_P=500, x_std_R=100, y_std_R=100, noise_std_Q=100, pos_x0=0, pos_y0=0, vel_x0=0.0, vel_y0=0.0, acc_x0=0, acc_y0=0, vel_std_P=10.0, acc_std_P=10.0)
- dt
- x_std_P
- y_std_P
- vel_std_P
- acc_std_P
- x_std_R
- y_std_R
- noise_std_Q
- pos_x0
- pos_y0
- vel_x0
- vel_y0
- acc_x0
- acc_y0
- points
- kf
- f_track(x, dt)
state transition function for nonlinear kf x is a vector as [x, dx, y, dy]
- h_track(z)
measurement function for nonlinear kf.
- predict()
- update(z)
- run(path)