def make_carla_settings(args):
"""Make a CarlaSettings object with the settings we need."""
settings = CarlaSettings()
settings.set(SynchronousMode=True,
SendNonPlayerAgentsInfo=True,
NumberOfVehicles=15,
NumberOfPedestrians=30,
WeatherId=random.choice([1, 3, 7, 8, 14]),
QualityLevel=args.quality_level)
settings.randomize_seeds()
camera0 = sensor.Camera('CameraRGB_main')
camera0.set_image_size(WINDOW_WIDTH, WINDOW_HEIGHT)
camera0.set_position(2.0, 0.0, 1.4)
camera0.set_rotation(0.0, 0.0, 0.0)
settings.add_sensor(camera0)
camera1 = sensor.Camera('CameraDepth', PostProcessing='Depth')
camera1.set_image_size(MINI_WINDOW_WIDTH, MINI_WINDOW_HEIGHT)
camera1.set_position(2.0, 0.0, 1.4)
camera1.set_rotation(0.0, 0.0, 0.0)
settings.add_sensor(camera1)
camera2 = sensor.Camera('CameraSemSeg',
PostProcessing='SemanticSegmentation')
camera2.set_image_size(MINI_WINDOW_WIDTH, MINI_WINDOW_HEIGHT)
camera2.set_position(2.0, 0.0, 1.4)
camera2.set_rotation(0.0, 0.0, 0.0)
settings.add_sensor(camera2)
cameraNN = sensor.Camera('CameraRGB')
cameraNN.set_image_size(H5_WINDOW_WIDTH, H5_WINDOW_HEIGHT)
cameraNN.set_position(2.0, 0.0, 1.4)
cameraNN.set_rotation(0.0, 0.0, 0.0)
settings.add_sensor(cameraNN)
if args.lidar:
lidar = sensor.Lidar('Lidar32')
lidar.set_position(0, 0, 2.5)
lidar.set_rotation(0, 0, 0)
lidar.set(Channels=32,
Range=50,
PointsPerSecond=100000,
RotationFrequency=10,
UpperFovLimit=10,
LowerFovLimit=-30)
settings.add_sensor(lidar)
return settings
def make_carla_settings():
"""Make a CarlaSettings object with the settings we need."""
settings = CarlaSettings()
settings.set(
SynchronousMode=False,
SendNonPlayerAgentsInfo=True,
NumberOfVehicles=15,
NumberOfPedestrians=30,
WeatherId=random.choice([1, 3, 7, 8, 14]))
settings.randomize_seeds()
# camera0 = sensor.Camera('CameraRGB')
# camera0.set_image_size(WINDOW_WIDTH, WINDOW_HEIGHT)
# camera0.set_position(200, 0, 140)
# camera0.set_rotation(0.0, 0.0, 0.0)
# settings.add_sensor(camera0)
# camera1 = sensor.Camera('CameraDepth', PostProcessing='Depth')
# camera1.set_image_size(MINI_WINDOW_WIDTH, MINI_WINDOW_HEIGHT)
# camera1.set_position(200, 0, 140)
# camera1.set_rotation(0.0, 0.0, 0.0)
# settings.add_sensor(camera1)
# camera2 = sensor.Camera('CameraSemSeg', PostProcessing='SemanticSegmentation')
# camera2.set_image_size(MINI_WINDOW_WIDTH, MINI_WINDOW_HEIGHT)
# camera2.set_position(200, 0, 140)
# camera2.set_rotation(0.0, 0.0, 0.0)
# settings.add_sensor(camera2)
lidar0 = sensor.Lidar('Lidar32')
lidar0.set_position(0, 0, 250)
lidar0.set_rotation(0, 0, 0)
lidar0.set(
Channels = 32,
Range = 5000,
PointsPerSecond = 640000,
RotationFrequency = 10,
UpperFovLimit = 10,
LowerFovLimit = -30,
ShowDebugPoints = False)
settings.add_sensor(lidar0)
return settings
def run_carla_client(args):
with make_connection(CarlaClient, args.host, args.port, timeout=15) as client:
logging.info('CarlaClient connected')
filename = '_out/test_episode_{:0>4d}/{:s}/{:0>6d}'
frames_per_episode = 300
episode = 0
while True:
episode += 1
settings = CarlaSettings()
settings.set(SendNonPlayerAgentsInfo=True, SynchronousMode=args.synchronous)
settings.randomize_seeds()
camera = sensor.Camera('DefaultCamera')
camera.set_image_size(300, 200) # Do not change this, hard-coded in test.
settings.add_sensor(camera)
lidar = sensor.Lidar('DefaultLidar')
settings.add_sensor(lidar)
logging.debug('sending CarlaSettings:\n%s', settings)
logging.info('new episode requested')
scene = client.load_settings(settings)
number_of_player_starts = len(scene.player_start_spots)
player_start = random.randint(0, max(0, number_of_player_starts - 1))
logging.info(
'start episode at %d/%d player start (%d frames)',
player_start,
number_of_player_starts,
frames_per_episode)
client.start_episode(player_start)
use_autopilot_control = (random.random() < 0.5)
reverse = (random.random() < 0.2)
for frame in range(0, frames_per_episode):
logging.debug('reading measurements...')
measurements, sensor_data = client.read_data()
images = [x for x in sensor_data.values() if isinstance(x, sensor.Image)]
logging.debug('received data of %d agents', len(measurements.non_player_agents))
if len(images) > 0:
assert (images[0].width, images[0].height) == (camera.ImageSizeX, camera.ImageSizeY)
if args.images_to_disk:
for name, data in sensor_data.items():
data.save_to_disk(filename.format(episode, name, frame))
logging.debug('sending control...')
control = measurements.player_measurements.autopilot_control
if not use_autopilot_control:
control.steer = random.uniform(-1.0, 1.0)
control.throttle = 0.3
control.hand_brake = False
control.reverse = reverse
client.send_control(
steer=control.steer,
throttle=control.throttle,
brake=control.brake,
hand_brake=control.hand_brake,
reverse=control.reverse)
def make_carla_settings():
"""Make a CarlaSettings object with the settings we need."""
settings = CarlaSettings()
settings.set(SendNonPlayerAgentsInfo=True,
SynchronousMode=True,
NumberOfVehicles=30,
NumberOfPedestrians=50,
WeatherId=1)
settings.set(DisableTwoWheeledVehicles=True)
settings.randomize_seeds() # IMPORTANT TO RANDOMIZE THE SEEDS EVERY TIME
camera0 = sensor.Camera('CentralSemanticSeg',
PostProcessing='SemanticSegmentation')
camera0.set_image_size(WINDOW_WIDTH, WINDOW_HEIGHT)
camera0.set(FOV=FOV)
camera0.set_position(2.0, 0.0, 1.4)
camera0.set_rotation(-15.0, 0, 0)
settings.add_sensor(camera0)
camera0 = sensor.Camera('CentralRGB')
camera0.set_image_size(WINDOW_WIDTH, WINDOW_HEIGHT)
camera0.set(FOV=FOV)
camera0.set_position(2.0, 0.0, 1.4)
camera0.set_rotation(-15.0, 0, 0)
settings.add_sensor(camera0)
camera0 = sensor.Camera('CentralDepth', PostProcessing='Depth')
camera0.set_image_size(WINDOW_WIDTH, WINDOW_HEIGHT)
camera0.set(FOV=FOV)
camera0.set_position(2.0, 0.0, 1.4)
camera0.set_rotation(-15.0, 0, 0)
settings.add_sensor(camera0)
camera0 = sensor.Camera('LeftSemanticSeg',
PostProcessing='SemanticSegmentation')
camera0.set_image_size(WINDOW_WIDTH, WINDOW_HEIGHT)
camera0.set(FOV=FOV)
camera0.set_position(2.0, 0.0, 1.4)
camera0.set_rotation(-15.0, -30.0, 0)
settings.add_sensor(camera0)
camera0 = sensor.Camera('LeftRGB')
camera0.set_image_size(WINDOW_WIDTH, WINDOW_HEIGHT)
camera0.set(FOV=FOV)
camera0.set_position(2.0, 0.0, 1.4)
camera0.set_rotation(-15.0, -30.0, 0)
settings.add_sensor(camera0)
camera0 = sensor.Camera('LeftDepth', PostProcessing='Depth')
camera0.set_image_size(WINDOW_WIDTH, WINDOW_HEIGHT)
camera0.set(FOV=FOV)
camera0.set_position(2.0, 0.0, 1.4)
camera0.set_rotation(-15.0, -30.0, 0)
settings.add_sensor(camera0)
camera0 = sensor.Camera('RightSemanticSeg',
PostProcessing='SemanticSegmentation')
camera0.set_image_size(WINDOW_WIDTH, WINDOW_HEIGHT)
camera0.set(FOV=FOV)
camera0.set_position(2.0, 0.0, 1.4)
camera0.set_rotation(-15.0, 30.0, 0)
settings.add_sensor(camera0)
camera0 = sensor.Camera('RightRGB')
camera0.set_image_size(WINDOW_WIDTH, WINDOW_HEIGHT)
camera0.set(FOV=FOV)
camera0.set_position(2.0, 0.0, 1.4)
camera0.set_rotation(-15.0, 30.0, 0)
settings.add_sensor(camera0)
camera0 = sensor.Camera('RightDepth', PostProcessing='Depth')
camera0.set_image_size(WINDOW_WIDTH, WINDOW_HEIGHT)
camera0.set(FOV=FOV)
camera0.set_position(2.0, 0.0, 1.4)
camera0.set_rotation(-15.0, 30.0, 0)
settings.add_sensor(camera0)
lidar = sensor.Lidar('Lidar32')
lidar.set_position(0, 0, 2.5)
lidar.set_rotation(0, 0, 0)
lidar.set(Channels=32,
Range=50,
PointsPerSecond=100000,
RotationFrequency=10,
UpperFovLimit=10,
LowerFovLimit=-30)
settings.add_sensor(lidar)
return settings
