from grid.model.navigation.visualservoing import VisualServoingcar = AirGenCar()# We will be capturing an image from the AirGen simulator # and run model inference on it.img = car.getImage("front_center","rgb").datamodel = VisualServoing(use_local =True)delta_yaw, velocity = model.run((100,100),{"width":640,"height":480,"fov":90,"camera_orientation_euler_pry":(0,0,0),},)print(f"delta_yaw: {delta_yaw}, velocity: {velocity}")
The VisualServoing class provides core functionality for this module.
This code is licensed under the Apache 2.0 License.
from grid.model.navigation.visualservoing import VisualServoingcar = AirGenCar()# We will be capturing an image from the AirGen simulator # and run model inference on it.img = car.getImage("front_center","rgb").datamodel = VisualServoing(use_local =True)delta_yaw, velocity = model.run((100,100),{"width":640,"height":480,"fov":90,"camera_orientation_euler_pry":(0,0,0),},)print(f"delta_yaw: {delta_yaw}, velocity: {velocity}")
from grid.model.navigation.visualservoing import VisualServoingcar = AirGenCar()# We will be capturing an image from the AirGen simulator # and run model inference on it.img = car.getImage("front_center","rgb").datamodel = VisualServoing(use_local =True)delta_yaw, velocity = model.run((100,100),{"width":640,"height":480,"fov":90,"camera_orientation_euler_pry":(0,0,0),},)print(f"delta_yaw: {delta_yaw}, velocity: {velocity}")
