def create_settings(n_vehicles, n_pedestrians, quality_level,
image_size, use_lidar, root_dir, lidar_params, z_BEV=25):
# Create a CarlaSettings object. This object is a wrapper around
# the CarlaSettings.ini file. Here we set the configuration we
# want for the new episode.
settings = CarlaSettings()
# Make sure that the server is running with '-benchmark' flag
settings.set(
SynchronousMode=True,
SendNonPlayerAgentsInfo=True,
NumberOfVehicles=n_vehicles,
NumberOfPedestrians=n_pedestrians,
# WeatherId=4,
WeatherId=1,
# WeatherId=random.choice([1, 3, 7, 8, 14]),
QualityLevel=quality_level)
settings.randomize_seeds()
log.info("Vehicle seed: {}".format(settings.SeedVehicles))
# TODO make lidar params pay attention to the H x W of BEV?
settings.lidar_params = lidar_params
# Now we want to add a couple of cameras to the player vehicle.
# We will collect the images produced by these cameras every
# frame.
# The default camera captures RGB images of the scene.
front_cam_rgb = Camera('CameraRGB')
front_cam_position = (0., 0., 1.5)
# angel_cam_position = (-5.5, 0.0, 2.8)
# angel_cam_position = (-5.5, 0.0, 3.8)
angel_cam_position = (-7.5, 0.0, 4.8)
# For visualization.
front_cam_rgb.FOV = 90
# Set image resolution in pixels.
front_cam_rgb.set_image_size(*image_size)
# Set its position relative to the car in meters.
# Default forward-facing
# camera0.set_position(0.30, 0, 1.30)
# front_cam_rgb.set_position(*front_cam_position)
front_cam_rgb.set_position(*angel_cam_position)
# front_cam_rgb.set_rotation(roll=0., pitch=-15., yaw=0.0)
front_cam_rgb.set_rotation(roll=0., pitch=-15., yaw=0.0)
settings.add_sensor(front_cam_rgb)
# Bird's eye view.
bev_cam_rgb = Camera('CameraRGBBEV')
# Note that at FOV=90, image width across ground plane is z*2 (if camera is parallel to ground)
# z_BEV = 50
bev_cam_rgb.set_position(x=0, y=0, z=z_BEV)
bev_cam_rgb.set_rotation(pitch=-90, roll=0, yaw=-90)
bev_cam_rgb.set_image_size(400, 400)
# bev_cam_rgb.set_image_size(200, 200)
# bev_cam_rgb.set_image_size(*image_size)
settings.add_sensor(bev_cam_rgb)
# bev_cam_sem = Camera('CameraSemanticBEV', PostProcessing='SemanticSegmentation')
# # Note that at FOV=90, image width across ground plane is z*2 (if camera is parallel to ground)
# bev_cam_sem.set_position(x=0, y=0, z=z_BEV)
# bev_cam_sem.set_rotation(pitch=-90, roll=0, yaw=0)
# bev_cam_sem.set_image_size(*image_size)
# settings.add_sensor(bev_cam_sem)
# Let's add another camera producing ground-truth depth.
front_cam_depth = Camera('CameraDepth', PostProcessing='Depth')
front_cam_depth.set_image_size(*image_size)
front_cam_depth.set_position(*front_cam_position)
settings.add_sensor(front_cam_depth)
# Semantic segmentation is black! Even in the demo code of manual_control.py ... Might be an issue with graphics card / Unreal support?
# See https://github.com/carla-simulator/carla/issues/151
camera = Camera('CameraSemantic', PostProcessing='SemanticSegmentation')
camera.set(FOV=90.0)
camera.set_image_size(*image_size)
camera.set_position(*front_cam_position)
camera.set_rotation(pitch=0, yaw=0, roll=0)
settings.add_sensor(camera)
if use_lidar:
settings.add_sensor(create_lidar())
else:
log.info("Not adding lidar")
return settings
