def make_carla_settings(self):
if self.settings_filepath is None:
"""Make a CarlaSettings object with the settings we need."""
settings = CarlaSettings()
settings.set(SynchronousMode=True,
SendNonPlayerAgentsInfo=True,
NumberOfVehicles=5,
NumberOfPedestrians=60,
WeatherId=random.choice(
[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 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)
else:
# Alternatively, we can load these settings from a file.
with open(self.settings_filepath, 'r') as fp:
settings = fp.read()
return settings
def make_carla_settings(args):
"""Make a CarlaSettings object with the settings we need.
"""
settings = CarlaSettings()
# There is no need for non-agent info requests if there are no pedestrians
# or vehicles.
get_non_player_agents_info = False
if (NUM_PEDESTRIANS > 0 or NUM_VEHICLES > 0):
get_non_player_agents_info = True
# Base level settings
settings.set(
SynchronousMode=True,
SendNonPlayerAgentsInfo=get_non_player_agents_info,
NumberOfVehicles=NUM_VEHICLES,
NumberOfPedestrians=NUM_PEDESTRIANS,
SeedVehicles=SEED_VEHICLES,
SeedPedestrians=SEED_PEDESTRIANS,
WeatherId=SIMWEATHER,
QualityLevel=args.quality_level)
camera0 = sensor.Camera('CameraRGB')
camera0.set_image_size(1200, 800)
camera0.set_position(-1.0, 0.0, 4.5)
camera0.set_rotation(0.0, 0.0, 0.0)
camera0.set(FOV=90.0)
settings.add_sensor(camera0)
camera2 = sensor.Camera('CameraSemSeg', PostProcessing='SemanticSegmentation')
camera2.set_image_size(320, 240)
camera2.set_position(-1.0, 0.0, 4.5)
camera2.set_rotation(0.0, 0.0, 0.0)
settings.add_sensor(camera2)
return settings
def make_carla_settings(args):
"""Make a CarlaSettings object with the settings we need.
"""
settings = CarlaSettings()
settings = CarlaSettings()
settings.set(SynchronousMode=True,
SendNonPlayerAgentsInfo=False,
NumberOfVehicles=20,
NumberOfPedestrians=40,
WeatherId=1)
settings.randomize_seeds()
camera0 = sensor.Camera('CameraRGB')
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)
return settings
def carla_settings(self):
settings = CarlaSettings()
settings.set(SynchronousMode=False,
SendNonPlayerAgentsInfo=False,
NumberOfVehicles=0,
NumberOfPedestrians=0,
WeatherId=0)
settings.randomize_seeds()
camera0 = sensor.Camera('CameraCenter')
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('CameraLeft')
camera1.set_image_size(WINDOW_WIDTH, WINDOW_HEIGHT)
camera1.set_position(200, 0, 140)
camera1.set_rotation(0.0, 0.0, -30.0)
settings.add_sensor(camera1)
camera2 = sensor.Camera('CameraRight')
camera2.set_image_size(WINDOW_WIDTH, WINDOW_HEIGHT)
camera2.set_position(200, 0, 140)
camera2.set_rotation(0.0, 0.0, 30.0)
settings.add_sensor(camera2)
if self.map_view is not None:
camera3 = sensor.Camera('TPPCamera')
camera3.set_image_size(self.map_view.shape[1], WINDOW_HEIGHT // 2)
camera3.set_position(-450, 0, 400)
camera3.set_rotation(-30.0, 0.0, 0.0)
settings.add_sensor(camera3)
self.settings = 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')
if mixed_reality:
camera2.set_image_size(WINDOW_WIDTH, WINDOW_HEIGHT)
else:
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)
return settings
def make_carla_settings(args):
"""Make a CarlaSettings object with the settings we need."""
settings = CarlaSettings()
settings.set(
SynchronousMode=False,
SendNonPlayerAgentsInfo=True,
NumberOfVehicles=NUM_VEHICLES,
NumberOfPedestrians=NUM_PEDESTRIANS,
DisableTwoWheeledVehicles=NO_BIKE,
# WeatherId=random.choice([1, 3, 7, 8, 14]),
WeatherId=1,
QualityLevel=args.quality_level)
settings.randomize_seeds()
camera0 = sensor.Camera('CameraRGB')
camera0.set_image_size(WINDOW_WIDTH, WINDOW_HEIGHT)
camera0.set_position(0, 0.0, CAMERA_HEIGHT_POS)
camera0.set_rotation(0.0, 0.0, 0.0)
settings.add_sensor(camera0)
lidar = sensor.Lidar('Lidar32')
lidar.set_position(0, 0.0, LIDAR_HEIGHT_POS)
lidar.set_rotation(0, 0, 0)
lidar.set(Channels=40,
Range=MAX_RENDER_DEPTH_IN_METERS,
PointsPerSecond=720000,
RotationFrequency=10,
UpperFovLimit=7,
LowerFovLimit=-16)
settings.add_sensor(lidar)
""" Depth camera for filtering out occluded vehicles """
depth_camera = sensor.Camera('DepthCamera', PostProcessing='Depth')
depth_camera.set(FOV=90.0)
depth_camera.set_image_size(WINDOW_WIDTH, WINDOW_HEIGHT)
depth_camera.set_position(0, 0, CAMERA_HEIGHT_POS)
depth_camera.set_rotation(0, 0, 0)
settings.add_sensor(depth_camera)
# (Intrinsic) K Matrix
# | f 0 Cu
# | 0 f Cv
# | 0 0 1
# (Cu, Cv) is center of image
k = np.identity(3)
k[0, 2] = WINDOW_WIDTH_HALF
k[1, 2] = WINDOW_HEIGHT_HALF
f = WINDOW_WIDTH / \
(2.0 * math.tan(90.0 * math.pi / 360.0))
k[0, 0] = k[1, 1] = f
camera_to_car_transform = camera0.get_unreal_transform()
lidar_to_car_transform = lidar.get_transform() * Transform(
Rotation(yaw=90), Scale(z=-1))
return settings, k, camera_to_car_transform, lidar_to_car_transform
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)
# --------------------------- CENTRAL CAMERA ---------------------------
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)
# --------------------------- TOP CAMERA ---------------------------
camera0 = sensor.Camera('TopSemanticSeg', PostProcessing='SemanticSegmentation')
camera0.set_image_size(WINDOW_WIDTH, WINDOW_HEIGHT)
camera0.set(FOV=FOV)
camera0.set_position(12.0, 0.0, 15.0)
camera0.set_rotation(-90.0, 90.0, -90.0)
settings.add_sensor(camera0)
camera0 = sensor.Camera('TopRGB')
camera0.set_image_size(WINDOW_WIDTH, WINDOW_HEIGHT)
camera0.set(FOV=FOV)
camera0.set_position(12.0, 0.0, 15.0)
camera0.set_rotation(-90.0, 90.0, -90.0)
settings.add_sensor(camera0)
return settings
def make_carla_settings(args):
"""Make a CarlaSettings object with the settings we need."""
settings = CarlaSettings()
settings.set(
SynchronousMode=True,
SendNonPlayerAgentsInfo=True,
NumberOfVehicles=10,
NumberOfPedestrians=100,
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)
camera3 = sensor.Camera('CameraRGB_h5')
camera3.set_image_size(H5_WINDOW_WIDTH, H5_WINDOW_HEIGHT)
camera3.set_position(2.0, 0.0, 1.4)
camera3.set_rotation(0.0, 0.0, 0.0)
settings.add_sensor(camera3)
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(args):
"""Make a CarlaSettings object with the settings we need."""
########################################################################################################
# TODO
# Change this to add more cameras
# Remove segmentation, depth if we use our own
# Change the no of vehicles, pedestrians, weather
########################################################################################################
###################################### Default from carla ######################################
settings = CarlaSettings()
settings.set(SynchronousMode=False,
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')
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)
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(
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('CameraRGB')
camera0.set_image_size(WINDOW_WIDTH, WINDOW_HEIGHT)
camera0.set(FOV=100)
camera0.set_image_size(800, 600)
camera0.set_position(2.0, 0.0, 1.4)
camera0.set_rotation(-15.0, 0, 0)
settings.add_sensor(camera0)
return settings
# 65, 18 to 65, 16
# 18, 145 to 16, 145
# 79, 45 to 79 47
def make_carla_settings(args):
"""Make a CarlaSettings object with the settings we need.
"""
settings = CarlaSettings()
# There is no need for non-agent info requests if there are no pedestrians
# or vehicles.
get_non_player_agents_info = False
if (NUM_PEDESTRIANS > 0 or NUM_VEHICLES > 0):
get_non_player_agents_info = True
# Base level settings
settings.set(SynchronousMode=True,
SendNonPlayerAgentsInfo=get_non_player_agents_info,
NumberOfVehicles=NUM_VEHICLES,
NumberOfPedestrians=NUM_PEDESTRIANS,
SeedVehicles=SEED_VEHICLES,
SeedPedestrians=SEED_PEDESTRIANS,
WeatherId=SIMWEATHER,
QualityLevel=args.quality_level)
WINDOW_WIDTH = 800
WINDOW_HEIGHT = 600
camera0 = sensor.Camera('CameraRGB')
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)
return settings
def make_carla_settings(args):
"""Make a CarlaSettings object with the settings we need."""
settings = CarlaSettings()
settings.set(SynchronousMode=True,
SendNonPlayerAgentsInfo=True,
NumberOfVehicles=0,
NumberOfPedestrians=0,
WeatherId=random.choice([1, 3, 7, 8, 14]),
QualityLevel=args.quality_level)
settings.randomize_seeds()
#Camera type and placement is chosen
#comment out a camera block if not wanted
camera0 = sensor.Camera('CameraCenter')
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('CameraRight')
camera1.set_image_size(WINDOW_WIDTH, WINDOW_HEIGHT)
camera1.set_position(2.0, 1.5, 1.4)
camera1.set_rotation(0.0, 0.0, 0.0)
settings.add_sensor(camera1)
camera2 = sensor.Camera('CameraLeft')
camera2.set_image_size(WINDOW_WIDTH, WINDOW_HEIGHT)
camera2.set_position(2.0, -1.5, 1.4)
camera2.set_rotation(0.0, 0.0, 0.0)
settings.add_sensor(camera2)
#if lidar is chosen, placement of it
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(args):
"""Make a CarlaSettings object with the settings we need."""
model = lm('./model_semseg.hdf5')
settings = CarlaSettings()
settings.set(SynchronousMode=True,
SendNonPlayerAgentsInfo=True,
NumberOfVehicles=5,
NumberOfPedestrians=30,
WeatherId=random.choice(list(range(15))),
QualityLevel=args.quality_level)
settings.randomize_seeds()
camera0 = sensor.Camera('CameraRGB')
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_image_size(WINDOW_WIDTH, 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_image_size(WINDOW_WIDTH, WINDOW_HEIGHT)
camera2.set_position(2.0, 0.0, 1.4)
camera2.set_rotation(0.0, 0.0, 0.0)
settings.add_sensor(camera2)
# 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(args):
"""Make a CarlaSettings object with the settings we need."""
settings = CarlaSettings()
settings.set(SynchronousMode=True,
SendNonPlayerAgentsInfo=False,
NumberOfVehicles=30,
NumberOfPedestrians=0,
WeatherId=1,
QualityLevel='Epic')
settings.randomize_seeds()
camera0 = sensor.Camera('CameraRGB')
camera0.set_image_size(CAM_WINDOW_WIDTH, CAM_WINDOW_HEIGHT)
camera0.set_position(2.0, 0.0, 1.4)
camera0.set_rotation(-15.0, 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)
lidar = sensor.Lidar('Lidar32')
lidar.set_position(0, 0, 2.5)
lidar.set_rotation(0, 0, 0)
lidar.set(Channels=0,
Range=50,
PointsPerSecond=100000,
RotationFrequency=10,
UpperFovLimit=0,
LowerFovLimit=0)
settings.add_sensor(lidar)
return settings
def make_carla_settings(enable_lidar):
"""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)
if enable_lidar:
lidar = sensor.Lidar('Lidar32')
lidar.set_position(0, 0, 250)
lidar.set_rotation(0, 0, 0)
lidar.set(Channels=32,
Range=5000,
PointsPerSecond=100000,
RotationFrequency=10,
UpperFovLimit=10,
LowerFovLimit=-30)
settings.add_sensor(lidar)
return settings
def make_carla_settings(args):
"""Make a CarlaSettings object with the settings we need."""
settings = CarlaSettings()
settings.set(SynchronousMode=False,
SendNonPlayerAgentsInfo=True,
NumberOfVehicles=10,
NumberOfPedestrians=5,
WeatherId=random.choice([1, 3, 7, 8, 14]),
QualityLevel=args.quality_level)
settings.randomize_seeds()
camera0 = sensor.Camera('CameraRGB')
camera0.set_image_size(WINDOW_WIDTH, WINDOW_HEIGHT)
camera0.set_position(0.30, 0, 1.30)
camera0.set_rotation(0.0, 0.0, 0.0)
settings.add_sensor(camera0)
return settings
def make_carla_settings():
"""Make a CarlaSettings object with the settings we need."""
settings = CarlaSettings()
settings.set(SendNonPlayerAgentsInfo=True, SynchronousMode=True)
settings.set(DisableTwoWheeledVehicles=True)
settings.randomize_seeds()
# Add a carla camera.
camera0 = sensor.Camera('CameraRGB')
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)
return settings
def make_carla_settings(args):
"""Make a CarlaSettings object with the settings we need."""
settings = CarlaSettings()
settings.set(SynchronousMode=True,
SendNonPlayerAgentsInfo=True,
NumberOfVehicles=5,
NumberOfPedestrians=5,
WeatherId=1,
QualityLevel='Low',
DisableTwoWheeledVehicles=True,
SeedVehicles=123456789,
SeedPedestrians=123456789)
camera0 = sensor.Camera('CameraRGB')
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)
return settings
def make_carla_settings(args, vehicle_tot):
# 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()
settings.set(SynchronousMode=False,
SendNonPlayerAgentsInfo=True,
NumberOfVehicles=vehicle_tot,
NumberOfPedestrians=0,
WeatherId=1,
QualityLevel=args.quality_level)
settings.randomize_seeds()
camera0 = sensor.Camera('CameraRGB')
camera0.set_image_size(WINDOW_WIDTH, WINDOW_HEIGHT)
px, py, pz = 2.0, 0.0, 1.4 # Default (Front)
rx, ry, rz = 0.0, 0.0, 0.0
if args.camera == "Driver":
px = -0.3
py = -0.5
pz = 1.1
elif args.camera == "Hood":
px = 1.0
py = 0.0
pz = 1.4
elif args.camera == "Top":
px = -5.5
py = 0.0
pz = 3.0
rx = -10.0
camera0.set_position(px, py, pz)
camera0.set_rotation(rx, ry, rz)
settings.add_sensor(camera0)
return settings
def make_carla_settings(args):
"""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]),
QualityLevel=args.quality_level)
settings.randomize_seeds()
camera0 = sensor.Camera('CameraSemSeg',
PostProcessing='SemanticSegmentation')
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)
#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)
return settings
def make_carla_settings():
"""Make a CarlaSettings object with the settings we need."""
settings = CarlaSettings()
settings.set(SynchronousMode=True,
SendNonPlayerAgentsInfo=True,
NumberOfVehicles=120,
NumberOfPedestrians=140,
WeatherId=weather_choice,
SeedVehicles=random.randint(0, 123456),
SeedPedestrians=random.randint(0, 123456))
# settings.randomize_seeds()
camera0 = sensor.Camera('CameraFront')
camera0.set(FOV=100)
camera0.set_image_size(WINDOW_WIDTH, WINDOW_HEIGHT)
camera0.set_position(1.35, 0, 1.40)
camera0.set_rotation(-15.0, 0.0, 0.0)
settings.add_sensor(camera0)
camera1 = sensor.Camera('CameraLeft')
camera1.set_image_size(MINI_WINDOW_WIDTH, MINI_WINDOW_HEIGHT)
camera1.set_position(1.30, -0.50, 1.40)
camera1.set_rotation(-20.0, 300.0, 0.0)
settings.add_sensor(camera1)
camera2 = sensor.Camera('CameraRight')
camera2.set_image_size(MINI_WINDOW_WIDTH, MINI_WINDOW_HEIGHT)
camera2.set_position(1.30, 0.50, 1.40)
camera2.set_rotation(-20.0, 60.0, 0.0)
settings.add_sensor(camera2)
# camera3 = sensor.Camera('CameraFrontDepth', PostProcessing='Depth')
# camera3.set(FOV=100)
# camera3.set_image_size(WINDOW_WIDTH, WINDOW_HEIGHT)
# camera3.set_position(135, 0, 140)
# camera3.set_rotation(-15.0, 0.0, 0.0)
# settings.add_sensor(camera3)
# camera4 = sensor.Camera('CameraLeftDepth', PostProcessing='Depth')
# camera4.set_image_size(MINI_WINDOW_WIDTH, MINI_WINDOW_HEIGHT)
# camera4.set_position(130, -50, 140)
# camera4.set_rotation(-20.0, 300.0, 0.0)
# settings.add_sensor(camera4)
# camera5 = sensor.Camera('CameraRightDepth', PostProcessing='Depth')
# camera5.set_image_size(MINI_WINDOW_WIDTH, MINI_WINDOW_HEIGHT)
# camera5.set_position(130, 50, 140)
# camera5.set_rotation(-20.0, 60.0, 0.0)
# settings.add_sensor(camera5)
# camera6 = sensor.Camera('CameraFrontSeg', PostProcessing='SemanticSegmentation')
# camera6.set(FOV=100)
# camera6.set_image_size(WINDOW_WIDTH, WINDOW_HEIGHT)
# camera6.set_position(135, 0, 140)
# camera6.set_rotation(-15.0, 0.0, 0.0)
# settings.add_sensor(camera6)
# camera7 = sensor.Camera('CameraLeftSeg', PostProcessing='SemanticSegmentation')
# camera7.set_image_size(MINI_WINDOW_WIDTH, MINI_WINDOW_HEIGHT)
# camera7.set_position(130, -50, 140)
# camera7.set_rotation(-20.0, 300.0, 0.0)
# settings.add_sensor(camera7)
# camera8 = sensor.Camera('CameraRightSeg', PostProcessing='SemanticSegmentation')
# camera8.set_image_size(MINI_WINDOW_WIDTH, MINI_WINDOW_HEIGHT)
# camera8.set_position(130, 50, 140)
# camera8.set_rotation(-20.0, 60.0, 0.0)
# settings.add_sensor(camera8)
return settings
def _initialize_carla(self):
# Initialize settings
settings = CarlaSettings()
settings.set(
SynchronousMode=True,
NumberOfVehicles=self._settings["number_of_vehicles"],
NumberOfPedestrians=self._settings["number_of_pedastrians"],
WeatherId=self._settings["weather_id"],
QualityLevel=self._settings["quality_level"],
SendNonPlayerAgentsInfo=True,
)
settings.randomize_seeds()
output_image_width = self._settings["output_image_width"]
output_image_height = self._settings["output_image_height"]
# Add a game camera 1 and 2
game_camera = sensor.Camera("GameCamera")
game_camera.set_image_size(
self._settings["window_width"], self._settings["window_height"]
)
game_camera.set_position(2.0, 0.0, 1.4)
game_camera.set_rotation(0.0, 0.0, 0.0)
settings.add_sensor(game_camera)
game_camera_3p = sensor.Camera("GameCamera3p")
game_camera_3p.set_image_size(
self._settings["window_width"], self._settings["window_height"]
)
game_camera_3p.set_position(-5, 0.0, 3)
game_camera_3p.set_rotation(-15, 0.0, 0)
settings.add_sensor(game_camera_3p)
# Add RGB center camera
rgb_camera_center = sensor.Camera("RGBCameraCenter")
rgb_camera_center.set_image_size(output_image_width, output_image_height)
rgb_camera_center.set_position(2.0, 0.0, 1.4)
rgb_camera_center.set_rotation(0.0, 0.0, 0.0)
settings.add_sensor(rgb_camera_center)
# Add RGB left camera
rgb_camera_left = sensor.Camera("RGBCameraLeft")
rgb_camera_left.set_image_size(output_image_width, output_image_height)
rgb_camera_left.set_position(2.0, -1, 1.4)
rgb_camera_left.set_rotation(0.0, 0.0, 0.0)
settings.add_sensor(rgb_camera_left)
# Add RGB right camera
rgb_camera_right = sensor.Camera("RGBCameraRight")
rgb_camera_right.set_image_size(output_image_width, output_image_height)
rgb_camera_right.set_position(2.0, 1, 1.4)
rgb_camera_right.set_rotation(0.0, 0.0, 0.0)
settings.add_sensor(rgb_camera_right)
# Add depth camera
depth_camera = sensor.Camera("DepthCamera", PostProcessing="Depth")
depth_camera.set_image_size(output_image_width, output_image_height)
depth_camera.set_position(2.0, 0.0, 1.4)
depth_camera.set_rotation(0.0, 0.0, 0.0)
settings.add_sensor(depth_camera)
# Add semantic segmentation camera
sem_seg_camera = sensor.Camera(
"SemSegCamera", PostProcessing="SemanticSegmentation"
)
sem_seg_camera.set_image_size(output_image_width, output_image_height)
sem_seg_camera.set_position(2.0, 0.0, 1.4)
sem_seg_camera.set_rotation(0.0, 0.0, 0.0)
settings.add_sensor(sem_seg_camera)
self._carla_settings = settings
logging.debug("Carla initialized")
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
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 run_carla_client(args):
with make_carla_client(args.host, args.port) as client:
print('CarlaClient connected')
while True:
settings = CarlaSettings()
settings.set(
SynchronousMode=True,
SendNonPlayerAgentsInfo=True,
NumberOfVehicles=0,
NumberOfPedestrians=0,
WeatherId=3, #1, 3, 7, 8, 14
QualityLevel=args.quality_level)
settings.randomize_seeds()
# 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.
camera0 = sensor.Camera('CameraRGB', PostProcessing='SceneFinal')
# Set image resolution in pixels.
w = 800
h = 600
camera0.set_image_size(800, 600)
# Set its position relative to the car in meters.
camera0.set_position(0.30, 0, 4)
settings.add_sensor(camera0)
# Let's add another camera producing ground-truth depth.
depth_camera = sensor.Camera('CameraDepth', PostProcessing='Depth')
depth_camera.set_image_size(800, 600)
depth_camera.set_position(x=0.30, y=0, z=4)
settings.add_sensor(depth_camera)
if args.lidar:
lidar = Lidar('Lidar32')
lidar.set_position(0, 0, 2.50)
lidar.set_rotation(0, 0, 0)
lidar.set(Channels=32,
Range=50,
PointsPerSecond=100000,
RotationFrequency=10,
UpperFovLimit=10,
LowerFovLimit=-30)
settings.add_sensor(lidar)
scene = client.load_settings(settings)
# Choose one player start at random.
number_of_player_starts = len(scene.player_start_spots)
player_start = random.randint(0, max(0,
number_of_player_starts - 1))
print('Starting new episode at %r...' % scene.map_name)
client.start_episode(player_start)
action_model = roughPPO.actor_model((h, w, 3), (3, 1), (20, 2))
critic_model = roughPPO.critic_model((h, w, 3), (3, 1), (20, 2),
(2, 1))
actor_action = [0, 0]
critic_score = 0
ppo_check = 0
# Iterate every frame in the episode.
ppo_iter_count = 0
while True:
# Read the data produced by the server this frame.
measurements, sensor_data = client.read_data()
# print_measurements(measurements)
main_image = sensor_data.get("CameraRGB", None)
image_array = image_converter.to_rgb_array(main_image)
point_cloud = image_converter.depth_to_local_point_cloud(
sensor_data['CameraDepth'], image_array, max_depth=1000)
image_array = cv2.cvtColor(image_array, cv2.COLOR_RGB2BGR)
cv2.imshow("FrontCam View", image_array)
reverse = 0
try:
steer_val = 0
bez_mask, coord_trajectory, trajectory, world_x_left, world_x_right, world_z_left, world_z_right = floodfill(
image_array, point_cloud)
track_point_yaw = trajectory[-5]
yaw_error = np.arctan(
(0 - track_point_yaw[0]) / (track_point_yaw[1]))
state_update_long(trajectory)
state_update_lat(world_x_left, world_x_right, yaw_error)
if ppo_check == 1:
reward_score = roughPPO.reward(actor_action,
world_x_left,
world_x_right)
if len(SDC_data_store.throttle_queue) < 50:
SDC_data_store.throttle_queue.append(
actor_action[0])
SDC_data_store.steer_queue.append(actor_action[1])
SDC_data_store.rewards_queue.append(reward_score)
SDC_data_store.critic_score.append(critic_score)
else:
print("IDHAR!!!!!!!!!!")
SDC_data_store.throttle_queue.popleft()
SDC_data_store.throttle_queue.append(
actor_action[0])
SDC_data_store.steer_queue.popleft()
SDC_data_store.steer_queue.append(actor_action[1])
SDC_data_store.rewards_queue.popleft()
SDC_data_store.rewards_queue.append(reward_score)
SDC_data_store.critic_score.popleft()
SDC_data_store.critic_score.append(reward_score)
if (len(SDC_data_store.rewards_queue) > 1):
returns, advs = roughPPO.advantages(
list(SDC_data_store.critic_score),
list(SDC_data_store.rewards_queue))
loss = roughPPO.ppo_loss(
advs, SDC_data_store.rewards_queue,
SDC_data_store.critic_score)
action_model.compile(optimizer=Adam(lr=1e-3),
loss=loss)
critic_model.compile(optimizer=Adam(lr=1e-3),
loss='mse')
print("LOSS : " + str(loss))
ppo_check = 0
if ppo_iter_count % 20 == 0 and ppo_iter_count > 0 and ppo_check == 0:
ppo_check = 1
action_output, critic_output = ppo_input(
measurements, trajectory, image_array,
action_model, critic_model)
actor_action = action_output[0]
critic_score = critic_output[0][0]
throttle_a = actor_action[0]
steer_val = actor_action[1]
else:
throttle_a = PID_throttle(trajectory, reverse)
cv2.imshow("bez", bez_mask)
steer_val = PID_steer(trajectory, reverse,
world_x_left, world_x_right)
check = SDC_data_store.shadow_check
client.send_control(steer=steer_val * check,
throttle=throttle_a * check + 0.5 *
(1 - check),
brake=0.0,
hand_brake=False,
reverse=False)
SDC_data_store.turn_value = steer_val
except Exception as e:
print(e)
client.send_control(steer=SDC_data_store.turn_value *
check,
throttle=1,
brake=0.85,
hand_brake=True,
reverse=False)
cv2.waitKey(1)
if SDC_data_store.count % 10 == 0:
print("frame: ", SDC_data_store.count)
# if SDC_data_store.count%10==0:
# SDC_data_store.sum_cte = 0
SDC_data_store.count += 1
print("*********\n")
ppo_iter_count += 1
