def run(self):
settings = CarlaSettings()
settings.add_camera(Camera('DefaultCamera'))
camera2 = Camera('Camera2')
camera2.set(PostProcessing='Depth', CameraFOV=120)
camera2.set_image_size(1924, 1028)
settings.add_camera(camera2)
self.run_carla_client(settings, 3, 100)
def get_default_carla_settings(args):
settings = CarlaSettings(
SynchronousMode=args.synchronous,
SendNonPlayerAgentsInfo=False,
NumberOfVehicles=20,
NumberOfPedestrians=40,
WeatherId=1)
settings.add_sensor(Camera('Camera1'))
return str(settings)
def build_experiments(self):
"""
Creates the whole set of experiment objects,
The experiments created depends on the selected Town.
"""
# We check the town, based on that we define the town related parameters
# The size of the vector is related to the number of tasks, inside each
# task there is also multiple poses ( start end, positions )
if self._city_name == 'Town01':
poses_tasks = [[[7, 3]], [[138, 17]], [[140, 134]], [[140, 134]]]
vehicles_tasks = [0, 0, 0, 20]
pedestrians_tasks = [0, 0, 0, 50]
else:
poses_tasks = [[[4, 2]], [[37, 76]], [[19, 66]], [[19, 66]]]
vehicles_tasks = [0, 0, 0, 15]
pedestrians_tasks = [0, 0, 0, 50]
# We set the camera
# This single RGB camera is used on every experiment
camera = Camera('CameraRGB')
camera.set(FOV=100)
camera.set_image_size(800, 600)
camera.set_position(2.0, 0.0, 1.4)
camera.set_rotation(-15.0, 0, 0)
# Based on the parameters, creates a vector with experiment objects.
experiments_vector = []
for weather in self.weathers:
for iteration in range(len(poses_tasks)):
poses = poses_tasks[iteration]
vehicles = vehicles_tasks[iteration]
pedestrians = pedestrians_tasks[iteration]
conditions = CarlaSettings()
conditions.set(
SendNonPlayerAgentsInfo=True,
NumberOfVehicles=vehicles,
NumberOfPedestrians=pedestrians,
WeatherId=weather
)
# Add all the cameras that were set for this experiments
conditions.add_sensor(camera)
experiment = Experiment()
experiment.set(
Conditions=conditions,
Poses=poses,
Task=iteration,
Repetitions=1
)
experiments_vector.append(experiment)
return experiments_vector
def run(self):
settings = CarlaSettings()
settings.set(
SynchronousMode=True,
SendNonPlayerAgentsInfo=True,
NumberOfVehicles=60,
NumberOfPedestrians=90)
settings.add_camera(Camera('DefaultCamera'))
self.run_carla_client(settings, 3, 100)
def build_experiments(self):
"""
Creates the whole set of experiment objects,
The experiments created depend on the selected Town.
"""
# We set the camera
# This single RGB camera is used on every experiment
camera = Camera('CameraRGB')
camera.set(FOV=100)
camera.set_image_size(800, 600)
camera.set_position(2.0, 0.0, 1.4)
camera.set_rotation(-15.0, 0, 0)
if self._city_name == 'Town01':
poses_tasks = self._poses_town01()
vehicles_tasks = [0, 0, 0, 20]
pedestrians_tasks = [0, 0, 0, 50]
else:
poses_tasks = self._poses_town02()
vehicles_tasks = [0, 0, 0, 15]
pedestrians_tasks = [0, 0, 0, 50]
experiments_vector = []
for weather in self.weathers:
for iteration in range(len(poses_tasks)):
poses = poses_tasks[iteration]
vehicles = vehicles_tasks[iteration]
pedestrians = pedestrians_tasks[iteration]
conditions = CarlaSettings()
conditions.set(
SendNonPlayerAgentsInfo=True,
NumberOfVehicles=vehicles,
NumberOfPedestrians=pedestrians,
WeatherId=weather
)
# Add all the cameras that were set for this experiments
conditions.add_sensor(camera)
experiment = Experiment()
experiment.set(
Conditions=conditions,
Poses=poses,
Task=iteration,
Repetitions=1
)
experiments_vector.append(experiment)
return experiments_vector
def _reset(self):
self.num_steps = 0
self.total_reward = 0
self.prev_measurement = None
self.prev_image = None
self.episode_id = datetime.today().strftime("%Y-%m-%d_%H-%M-%S_%f")
self.measurements_file = None
# 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()
self.scenario = random.choice(self.config["scenarios"])
assert self.scenario["city"] == self.city, (self.scenario, self.city)
self.weather = random.choice(self.scenario["weather_distribution"])
settings.set(
SynchronousMode=True,
SendNonPlayerAgentsInfo=True,
NumberOfVehicles=self.scenario["num_vehicles"],
NumberOfPedestrians=self.scenario["num_pedestrians"],
WeatherId=self.weather)
settings.randomize_seeds()
if self.config["use_depth_camera"]:
camera1 = Camera("CameraDepth", PostProcessing="Depth")
camera1.set_image_size(self.config["render_x_res"],
self.config["render_y_res"])
camera1.set_position(30, 0, 130)
settings.add_sensor(camera1)
camera2 = Camera("CameraRGB")
camera2.set_image_size(self.config["render_x_res"],
self.config["render_y_res"])
camera2.set_position(30, 0, 130)
settings.add_sensor(camera2)
# Setup start and end positions
scene = self.client.load_settings(settings)
positions = scene.player_start_spots
self.start_pos = positions[self.scenario["start_pos_id"]]
self.end_pos = positions[self.scenario["end_pos_id"]]
self.start_coord = [
self.start_pos.location.x // 100, self.start_pos.location.y // 100
]
self.end_coord = [
self.end_pos.location.x // 100, self.end_pos.location.y // 100
]
print("Start pos {} ({}), end {} ({})".format(
self.scenario["start_pos_id"], self.start_coord,
self.scenario["end_pos_id"], self.end_coord))
# Notify the server that we want to start the episode at the
# player_start index. This function blocks until the server is ready
# to start the episode.
print("Starting new episode...")
self.client.start_episode(self.scenario["start_pos_id"])
image, py_measurements = self._read_observation()
self.prev_measurement = py_measurements
return self.encode_obs(self.preprocess_image(image), py_measurements)
def run_carla_client(args):
with make_connection(CarlaClient, args.host, args.port, timeout=15) as client:
logging.info('CarlaClient connected')
filename = '_images/episode_{:0>3d}/image_{:0>5d}.png'
frames_per_episode = 300
episode = 0
while True:
episode += 1
settings = CarlaSettings()
settings.set(SendNonPlayerAgentsInfo=True,SynchronousMode=args.synchronous)
settings.randomize_seeds()
camera = Camera('DefaultCamera')
camera.set_image_size(300, 200) # Do not change this, hard-coded in test.
settings.add_camera(camera)
logging.debug('sending CarlaSettings:\n%s', settings)
logging.info('new episode requested')
scene = client.request_new_episode(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_ai_control = (random.random() < 0.5)
reverse = (random.random() < 0.2)
for frame in range(0, frames_per_episode):
logging.debug('reading measurements...')
measurements, images = client.read_measurements()
logging.debug('received data of %d agents', len(measurements.non_player_agents))
assert len(images) == 1
assert (images[0].width, images[0].height) == (camera.ImageSizeX, camera.ImageSizeY)
if args.images_to_disk:
images[0].save_to_disk(filename.format(episode, frame))
logging.debug('sending control...')
control = measurements.player_measurements.ai_control
if not use_ai_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 build_experiments(self):
"""
Creates the whole set of experiment objects,
The experiments created depend on the selected Town.
"""
# We set the camera
# This single RGB camera is used on every experiment
camera = Camera('rgb')
camera.set(FOV=100)
camera.set_image_size(800, 600)
camera.set_position(2.0, 0.0, 1.4)
camera.set_rotation(-15.0, 0, 0)
poses_tasks = self._poses()
vehicles_tasks = [0, 20, 100]
pedestrians_tasks = [0, 50, 250]
task_names = ['empty', 'normal', 'cluttered']
experiments_vector = []
for weather in self.weathers:
for iteration in range(len(poses_tasks)):
poses = poses_tasks[iteration]
vehicles = vehicles_tasks[iteration]
pedestrians = pedestrians_tasks[iteration]
conditions = CarlaSettings()
conditions.set(SendNonPlayerAgentsInfo=True,
NumberOfVehicles=vehicles,
NumberOfPedestrians=pedestrians,
WeatherId=weather)
conditions.set(DisableTwoWheeledVehicles=True)
# Add all the cameras that were set for this experiments
conditions.add_sensor(camera)
experiment = Experiment()
experiment.set(Conditions=conditions,
Poses=poses,
Task=iteration,
TaskName=task_names[iteration],
Repetitions=1)
experiments_vector.append(experiment)
return experiments_vector
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)
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('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)
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 run(self):
settings = CarlaSettings()
settings.set(SynchronousMode=True,
SendNonPlayerAgentsInfo=True,
NumberOfVehicles=60,
NumberOfPedestrians=90)
settings.add_sensor(Camera('DefaultCamera'))
self.run_carla_client(settings, 3, 100)
def view_start_positions(args):
# We assume the CARLA server is already waiting for a client to connect at
# host:port. The same way as in the client example.
with make_carla_client(args.host, args.port) as client:
print('CarlaClient connected')
# We load the default settings to the client.
scene = client.load_settings(CarlaSettings())
print("Received the start positions")
# We get the number of player starts, in order to detect the city.
number_of_player_starts = len(scene.player_start_spots)
if number_of_player_starts > 100: # WARNING: unsafe way to check for city, see issue #313
image = mpimg.imread("carla/planner/Town01.png")
carla_map = CarlaMap('Town01', 16.53, 50)
else:
image = mpimg.imread("carla/planner/Town02.png")
carla_map = CarlaMap('Town02', 16.53, 50)
_, ax = plt.subplots(1)
ax.imshow(image)
if args.positions == 'all':
positions_to_plot = range(len(scene.player_start_spots))
else:
positions_to_plot = map(int, args.positions.split(','))
for position in positions_to_plot:
# Check if position is valid
if position >= len(scene.player_start_spots):
raise RuntimeError('Selected position is invalid')
# Convert world to pixel coordinates
pixel = carla_map.convert_to_pixel([
scene.player_start_spots[position].location.x,
scene.player_start_spots[position].location.y,
scene.player_start_spots[position].location.z
])
circle = Circle((pixel[0], pixel[1]),
12,
color='r',
label='A point')
ax.add_patch(circle)
if not args.no_labels:
plt.text(pixel[0], pixel[1], str(position), size='x-small')
plt.show()
def run(self):
settings = CarlaSettings()
settings.add_sensor(Camera('DefaultCamera'))
camera2 = Camera('Camera2')
camera2.set(PostProcessing='Depth', CameraFOV=120)
camera2.set_image_size(1924, 1028)
settings.add_sensor(camera2)
self.run_carla_client(settings, 3, 100)
def build_experiments(self):
"""
Creates the whole set of experiment objects,
The experiments created depends on the selected Town.
"""
# We check the town, based on that we define the town related parameters
# The size of the vector is related to the number of tasks, inside each
# task there is also multiple poses ( start end, positions )
if self._city_name == 'Town01':
poses_tasks = [[[7, 3]], [[138, 17]], [[140, 134]], [[140, 134]]]
vehicles_tasks = [0, 0, 0, 20]
pedestrians_tasks = [0, 0, 0, 50]
else:
poses_tasks = [[[4, 2]], [[37, 76]], [[19, 66]], [[19, 66]]]
vehicles_tasks = [0, 0, 0, 15]
pedestrians_tasks = [0, 0, 0, 50]
# We set the camera
# This single RGB camera is used on every experiment
camera = Camera('CameraRGB')
camera.set(FOV=100)
camera.set_image_size(800, 600)
camera.set_position(2.0, 0.0, 1.4)
camera.set_rotation(-15.0, 0, 0)
# Based on the parameters, creates a vector with experiment objects.
experiments_vector = []
for weather in self.weathers:
for iteration in range(len(poses_tasks)):
poses = poses_tasks[iteration]
vehicles = vehicles_tasks[iteration]
pedestrians = pedestrians_tasks[iteration]
conditions = CarlaSettings()
conditions.set(
SendNonPlayerAgentsInfo=True,
NumberOfVehicles=vehicles,
NumberOfPedestrians=pedestrians,
WeatherId=weather
)
# Add all the cameras that were set for this experiments
conditions.add_sensor(camera)
experiment = Experiment()
experiment.set(
Conditions=conditions,
Poses=poses,
Task=iteration,
Repetitions=1
)
experiments_vector.append(experiment)
return experiments_vector
def default_settings():
settings = CarlaSettings()
settings.set(
SynchronousMode=True,
SendNonPlayerAgentsInfo=True,
NumberOfVehicles=0,
NumberOfPedestrians=0,
WeatherId=1, # random.choice([1, 3, 7, 8, 14]),
PlayerVehicle='/Game/Blueprints/Vehicles/Mustang/Mustang.Mustang_C',
QualityLevel='Epic')
settings.randomize_seeds()
camera_RGB = Camera('CameraRGB')
camera_RGB.set_image_size(256, 256)
camera_RGB.set_position(1, 0, 2.50)
settings.add_sensor(camera_RGB)
camera_seg = Camera('CameraSegmentation',
PostProcessing='SemanticSegmentation')
camera_seg.set_image_size(256, 256)
camera_seg.set_position(1, 0, 2.50)
settings.add_sensor(camera_seg)
return settings
def reset(self):
"""
:return:
"""
settings = CarlaSettings()
settings.set(SynchronousMode=True,
SendNonPlayerAgentsInfo=True,
NumberOfVehicles=20,
NumberOfPedestrians=40,
WeatherId=random.choice([1, 3, 7, 8, 14]),
QualityLevel='Epic')
# CAMERA
camera0 = Camera('CameraRGB', PostProcessing='SceneFinal')
# Set image resolution in pixels.
camera0.set_image_size(800, 600)
# Set its position relative to the car in meters.
camera0.set_position(0.30, 0, 1.30)
settings.add_sensor(camera0)
# Let's add another camera producing ground-truth depth.
# camera1 = Camera('CameraDepth', PostProcessing='Depth')
# camera1.set_image_size(800, 600)
# camera1.set_position(0.30, 0, 1.30)
# settings.add_sensor(camera1)
# 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 = self.carla_client.load_settings(settings)
self.pre_image = None
self.cur_image = None
self.pre_measurements = None
self.cur_measurements = None
# define a random starting point of the agent for the appropriate trainning
number_of_player_starts = len(scene.player_start_spots)
player_start = random.randint(0, max(0, number_of_player_starts - 1))
# player_start = 140
self.carla_client.start_episode(player_start)
print('Starting new episode at %r, %d...' %
(scene.map_name, player_start))
# TODO: read and return status after reset
return
def _build_experiments(self):
"""
Creates the whole set of experiment objects,
The experiments created depend on the selected Town.
"""
# We set the camera
# This single RGB camera is used on every experiment
camera = Camera('CameraRGB')
camera.set(FOV=100)
camera.set_image_size(800, 600)
camera.set_position(200, 0, 140)
camera.set_rotation(-15.0, 0, 0)
weathers = [1, 3, 6, 8, 4, 14]
if self._city_name == 'Town01':
poses_tasks = self._poses_town01()
vehicles_tasks = [0, 0, 0, 20]
pedestrians_tasks = [0, 0, 0, 50]
else:
poses_tasks = self._poses_town02()
vehicles_tasks = [0, 0, 0, 15]
pedestrians_tasks = [0, 0, 0, 50]
experiments_vector = []
for weather in weathers:
for iteration in range(len(poses_tasks)):
poses = poses_tasks[iteration]
vehicles = vehicles_tasks[iteration]
pedestrians = pedestrians_tasks[iteration]
conditions = CarlaSettings()
conditions.set(SynchronousMode=True,
SendNonPlayerAgentsInfo=True,
NumberOfVehicles=vehicles,
NumberOfPedestrians=pedestrians,
WeatherId=weather,
SeedVehicles=123456789,
SeedPedestrians=123456789)
# Add all the cameras that were set for this experiments
conditions.add_sensor(camera)
experiment = Experiment()
experiment.set(Conditions=conditions,
Poses=poses,
Id=iteration,
Repetitions=1)
experiments_vector.append(experiment)
return experiments_vector
def __init__(self,
name,
flags,
camera_setups=[],
lidar_stream_names=[],
log_file_name=None,
csv_file_name=None):
super(CarlaOperator, self).__init__(name)
self._flags = flags
self._logger = setup_logging(self.name, log_file_name)
self._csv_logger = setup_csv_logging(self.name + '-csv', csv_file_name)
self.message_num = 0
if self._flags.carla_high_quality:
quality = 'Epic'
else:
quality = 'Low'
self.settings = CarlaSettings()
self.settings.set(
SynchronousMode=self._flags.carla_synchronous_mode,
SendNonPlayerAgentsInfo=True,
NumberOfVehicles=self._flags.carla_num_vehicles,
NumberOfPedestrians=self._flags.carla_num_pedestrians,
WeatherId=self._flags.carla_weather,
QualityLevel=quality)
self.settings.randomize_seeds()
self.lidar_streams = []
for (camera_stream_name, camera_type, image_size,
pos) in camera_setups:
self.__add_camera(name=camera_stream_name,
postprocessing=camera_type,
image_size=image_size,
position=pos)
for lidar_stream_name in lidar_stream_names:
self.__add_lidar(name=lidar_stream_name)
self.agent_id_map = {}
self.pedestrian_count = 0
def build_experiments(self):
"""
Creates the whole set of experiment objects,
The experiments created depend on the selected Town.
"""
# We set the camera
# This single RGB camera is used on every experiment
camera = Camera('CameraRGB')
camera.set(FOV=100)
camera.set_image_size(800, 600)
camera.set_position(2.0, 0.0, 1.4)
camera.set_rotation(-15.0, 0, 0)
if self._city_name == 'Town01':
poses_tasks = self._poses_town01()
vehicles_tasks = [25]
pedestrians_tasks = [25]
else:
poses_tasks = self._poses_town02()
vehicles_tasks = [0, 25]
pedestrians_tasks = [0, 25]
experiments_vector = []
#weathers = [1,3,6,8]
for weather in self.weathers:
#prinst(weather , vehicles_tasks)
for scenario in range(len(vehicles_tasks)):
for iteration in range(len(poses_tasks)):
#print(f"interation : {iteration} , scenario:{scenario}")
poses = poses_tasks[iteration]
#print("poses re",poses)
vehicles = vehicles_tasks[scenario]
#print("Vehicles: ",vehicles)
pedestrians = pedestrians_tasks[scenario]
#print("pedestrians: ",pedestrians)
conditions = CarlaSettings()
conditions.set(SendNonPlayerAgentsInfo=True,
NumberOfVehicles=vehicles,
NumberOfPedestrians=pedestrians,
WeatherId=weather)
# Add all the cameras that were set for this experiments
conditions.add_sensor(camera)
experiment = Experiment()
experiment.set(Conditions=conditions,
Poses=poses,
Task=iteration,
Repetitions=1)
experiments_vector.append(experiment)
return experiments_vector
def build_experiments(self):
"""
Creates the whole set of experiment objects,
The experiments created depend on the selected Town.
"""
# We set the camera
# This single RGB camera is used on every experiment
camera = Camera('rgb')
camera.set(FOV=90)
camera.set_image_size(300, 300)
camera.set_position(0.2, 0.0, 0.85)
camera.set_rotation(-3.0, 0, 0)
poses_tasks = self._poses()
vehicles_tasks = [0, 0, 0, 15]
pedestrians_tasks = [0, 0, 0, 50]
experiments_vector = []
for weather in self.weathers:
for iteration in range(len(poses_tasks)):
poses = poses_tasks[iteration]
vehicles = vehicles_tasks[iteration]
pedestrians = pedestrians_tasks[iteration]
conditions = CarlaSettings()
conditions.set(
SendNonPlayerAgentsInfo=True,
NumberOfVehicles=vehicles,
NumberOfPedestrians=pedestrians,
WeatherId=weather,
QualityLevel='Epic'
)
# Add all the cameras that were set for this experiments
conditions.add_sensor(camera)
experiment = Experiment()
experiment.set(
Conditions=conditions,
Poses=poses,
Task=iteration,
Repetitions=1
)
experiments_vector.append(experiment)
return experiments_vector
def generate_settings(args, sync_mode=True):
settings = CarlaSettings()
settings.set(SynchronousMode=sync_mode,
SendNonPlayerAgentsInfo=False,
NumberOfVehicles=0,
NumberOfPedestrians=0,
WeatherId=args.weather,
QualityLevel=args.quality_level)
settings.randomize_seeds()
return settings
def make_carla_settings(args):
"""Make a CarlaSettings object with the settings we need."""
settings = CarlaSettings()
settings.set(SynchronousMode=False,
SendNonPlayerAgentsInfo=False,
NumberOfVehicles=0,
NumberOfPedestrians=0,
WeatherId=random.choice([1, 3, 7, 8, 14]),
QualityLevel=args.quality_level)
settings.randomize_seeds()
return settings
def _make_carla_client(self, host, port):
while True:
try:
self.logger.info(
"Trying to make client on port {}".format(port))
self._client = CarlaClient(host, port, timeout=100)
self._client.connect()
self._client.load_settings(CarlaSettings(QualityLevel='Low'))
self._client.start_episode(0)
self.logger.info(
"Successfully made client on port {}".format(port))
break
except TCPConnectionError as error:
self.logger.debug('Got TCPConnectionError..sleeping for 1')
self.logger.error(error)
time.sleep(1)
def gen_settings(args):
settings = CarlaSettings()
settings.set(
SynchronousMode=True,
SendNonPlayerAgentsInfo=False,
NumberOfVehicles=0,
NumberOfPedestrians=0,
WeatherId=args.weather,
QualityLevel=args.quality_level)
settings.randomize_seeds()
camera_pos_x = 2
camera_pos_y = 0
camera_pos_z = 1
camera = Camera("MainCamera")
camera.set_image_size(800, 600)
camera.set_position(camera_pos_x, camera_pos_y, camera_pos_z)
settings.add_sensor(camera)
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,
SeedVehicles='00000',
WeatherId=1,
QualityLevel=args.quality_level)
settings.randomize_seeds()
return settings
def _make_carla_client(self, host, port):
for _ in range(
20
): # Try to connect for up to 20 times (usually connects first attempt if everything is correct)
try:
self.logger.info(
"Trying to make client on port {}".format(port))
self._client = CarlaClient(host, port, timeout=100)
self._client.connect()
self._client.load_settings(CarlaSettings(QualityLevel='Low'))
self._client.start_episode(0)
self.logger.info(
"Successfully made client on port {}".format(port))
break
except TCPConnectionError as error:
self.logger.debug('Got TCPConnectionError..sleeping for 1')
self.logger.error(error)
time.sleep(1)
def make_carla_settings(args):
'''
Creates a CarlaSettings object.
It configures the sensors, pedestrians, vehicles, weather, etc.
'''
settings = CarlaSettings()
settings.set(SynchronousMode=True,
SendNonPlayerAgentsInfo=True,
NumberOfVehicles=args.vehicles,
NumberOfPedestrians=args.pedestrians,
WeatherId=random.choice([1, 3, 7, 8, 14]),
QualityLevel=args.quality_level)
settings.randomize_seeds()
# The default camera captures RGB images of the scene.
camera0 = Camera('CameraRGB')
# Set image resolution in pixels.
camera0.set_image_size(800, 600)
# Set its position relative to the car in meters.
camera0.set_position(0.30, 0, 1.30)
settings.add_sensor(camera0)
return settings
def get_carla_settings(settings_file=None):
if settings_file is None:
# 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=True,
SendNonPlayerAgentsInfo=False,
NumberOfVehicles=0,
NumberOfPedestrians=0,
# 8-14 are sunset; we want easy first
WeatherId=random.choice(range(0, 11)),
QualityLevel='Epic'
)
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 = Camera('CameraRGB')
# Set image resolution in pixels.
camera0.set_image_size(carla_config.render_width,
carla_config.render_height)
# Set its position relative to the car in meters.
camera0.set_position(0.30, 0, 1.30)
settings.add_sensor(camera0)
else:
# Alternatively, we can load these settings from a file.
with open(settings_file, 'r') as fp:
settings = fp.read()
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 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 = CarlaSettings()
settings.set(SynchronousMode=True,
SendNonPlayerAgentsInfo=False,
NumberOfVehicles=2,
NumberOfPedestrians=10,
WeatherId=1)
#settings.randomize_seeds()
camera1 = Camera('CameraDepth', PostProcessing='Depth', FOV=fov)
camera1.set_image_size(*image_size)
camera1.set_position(*camera_local_pos)
camera1.set_rotation(*camera_local_rotation)
settings.add_sensor(camera1)
camera2 = Camera('CameraRGB', PostProcessing='SceneFinal', FOV=fov)
camera2.set_image_size(*image_size)
camera2.set_position(*camera_local_pos)
camera2.set_rotation(*camera_local_rotation)
settings.add_sensor(camera2)
return settings, camera2
def setup_client_and_server(self, reconnect_client_only=False):
# open the server
if not reconnect_client_only:
self.server = self._open_server()
self.server_pid = self.server.pid # To kill incase child process gets lost
print("setup server, out:", self.server_pid)
while True:
try:
self.game = CarlaClient(self.host, self.port, timeout=99999999)
self.game.connect(
connection_attempts=100) # It's taking a very long time for the server process to spawn, so the client needs to wait or try sufficient no. of times lol
self.game.load_settings(CarlaSettings())
self.game.start_episode(0)
self.is_game_setup = self.server and self.game
print("setup client")
return
except TCPConnectionError as error:
print(error)
time.sleep(1)
def reset(self):
"""
Resets the state of the environment and returns an initial observation.
:return: observation (object): the initial observation of the space.
"""
# load Carla settings
settings = CarlaSettings()
settings = self._load_settings(settings)
scene = self.carla_client.load_settings(settings)
# define a random starting point of the agent for the appropriate training
number_of_player_starts = len(scene.player_start_spots)
player_start = self.rng.randint(0, max(0, number_of_player_starts - 1))
self.carla_client.start_episode(player_start)
print(f'Starting new episode at {scene.map_name}, {player_start}...')
# read and return status after reset
self.cur_measurements, self.cur_image = self._read_data()
state = self._state(
self.cur_image, self.cur_image
) #possibly revise the state to be some operation of several images.
meas = self.cur_measurements
return state, meas
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 view_start_positions(args):
# We assume the CARLA server is already waiting for a client to connect at
# host:port. The same way as in the client example.
with make_carla_client(args.host, args.port) as client:
print('CarlaClient connected')
# We load the default settings to the client.
scene = client.load_settings(CarlaSettings())
print("Received the start positions")
try:
image = mpimg.imread('carla/planner/%s.png' % scene.map_name)
carla_map = CarlaMap(scene.map_name, 0.1653, 50)
except IOError as exception:
logging.error(exception)
logging.error('Cannot find map "%s"', scene.map_name)
sys.exit(1)
fig, ax = plt.subplots(1)
plt.ion()
ax.imshow(image)
if args.positions == 'all':
positions_to_plot = range(len(scene.player_start_spots))
else:
positions_to_plot = map(int, args.positions.split(','))
while True:
measurements, sensor_data = client.read_data()
current_x = measurements.player_measurements.transform.location.x
current_y = measurements.player_measurements.transform.location.y
pixel = carla_map.convert_to_pixel([current_x, current_y, 0])
circle = Circle((pixel[0], pixel[1]), 12, color='k', label='car')
ax.add_patch(circle)
plt.pause(0.05)
def start_game(args):
pygame.init()
with make_carla_client(args.host, args.port) as client:
settings = CarlaSettings()
settings.set(
SynchronousMode=False,
SendNonPlayerAgentsInfo=True,
NumberOfVehicles=3,
NumberOfPedestrians=40,
WeatherId=1,
QualityLevel="Low")
settings.randomize_seeds()
scene = client.load_settings(settings)
screen, img, dim, scale = setup_game_window(scene)
town_map = CarlaMap(scene.map_name, 0.1653, 50)
client.start_episode(7)
while running:
manage_events(pygame.event.get())
screen.blit(img, (0, 0))
play_frame(client, town_map, screen, dim, scale)
pygame.display.flip()
def run_carla_client(args):
skip_frames = 100 # 100 # at 10 fps
number_of_episodes = args.n_episode
frames_per_episode = args.n_frame
# n_weather = 14 # weathers starts from 1
# n_player_start_spots = 152 # Town01
n_player_start_spots = 83 # Town02
weathers = number_of_episodes * [2] # CloudyNoon
start_spots = list(range(n_player_start_spots))
random.shuffle(start_spots)
assert number_of_episodes < n_player_start_spots
start_spots = start_spots[:number_of_episodes]
# weathers = list(range(number_of_episodes))
# # random.shuffle(weathers)
# weathers = [w % 14 + 1 for w in weathers]
# https://carla.readthedocs.io/en/latest/carla_settings/
# number_of_episodes = n_weather*n_player_start_spots
# frames_per_episode = args.n_frame
# weathers, start_spots = np.meshgrid(list(range(1, n_weather+1)), list(range(n_player_start_spots)))
# weathers = weathers.flatten()
# start_spots = start_spots.flatten()
if not os.path.isdir(args.out_dir):
os.makedirs(args.out_dir)
np.savetxt(join(args.out_dir, 'weathers.txt'), weathers, fmt='%d')
np.savetxt(join(args.out_dir, 'start-spots.txt'), start_spots, fmt='%d')
# We assume the CARLA server is already waiting for a client to connect at
# host:port. To create a connection we can use the `make_carla_client`
# context manager, it creates a CARLA client object and starts the
# connection. It will throw an exception if something goes wrong. The
# context manager makes sure the connection is always cleaned up on exit.
with make_carla_client(args.host, args.port) as client:
print('CarlaClient connected')
for episode in range(number_of_episodes):
# Start a new episode.
if args.settings_filepath is None:
# 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=True,
SendNonPlayerAgentsInfo=True,
NumberOfVehicles=20,
NumberOfPedestrians=40,
WeatherId=weathers[episode],
# WeatherId=random.randrange(14) + 1,
# WeatherId=random.choice([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 = Camera('RGB')
# Set image resolution in pixels.
camera0.set(FOV=args.cam_fov)
camera0.set_image_size(args.x_res, args.y_res)
# Set its position relative to the car in meters.
camera0.set_position(*args.cam_offset)
camera0.set_rotation(*args.cam_rotation)
settings.add_sensor(camera0)
# Let's add another camera producing ground-truth depth.
camera1 = Camera('Depth', PostProcessing='Depth')
camera1.set(FOV=args.cam_fov)
camera1.set_image_size(args.x_res, args.y_res)
camera1.set_position(*args.cam_offset)
camera1.set_rotation(*args.cam_rotation)
settings.add_sensor(camera1)
camera2 = Camera('SegRaw',
PostProcessing='SemanticSegmentation')
camera2.set(FOV=args.cam_fov)
camera2.set_image_size(args.x_res, args.y_res)
camera2.set_position(*args.cam_offset)
camera2.set_rotation(*args.cam_rotation)
settings.add_sensor(camera2)
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)
else:
# Alternatively, we can load these settings from a file.
with open(args.settings_filepath, 'r') as fp:
settings = fp.read()
# Now we load these settings into the server. The server replies
# with a scene description containing the available start spots for
# the player. Here we can provide a CarlaSettings object or a
# CarlaSettings.ini file as string.
scene = client.load_settings(settings)
# Choose one player start at random.
# number_of_player_starts = len(scene.player_start_spots)
# player_start = random.randrange(number_of_player_starts)
player_start = start_spots[episode]
# Notify the server that we want to start the episode at the
# player_start index. This function blocks until the server is ready
# to start the episode.
print('Starting new episode...')
client.start_episode(player_start)
frame = 0
save_frame_idx = 0
# extra_frames = 0
# last_control = None
# last_control_changed = 0
# while frame < skip_frames + frames_per_episode + extra_frames:
# Iterate every frame in the episode.
for frame in range(skip_frames + frames_per_episode):
# Read the data produced by the server this frame.
measurements, sensor_data = client.read_data()
# Print some of the measurements.
print_measurements(measurements)
# Save the images to disk if requested.
if args.save_images_to_disk and frame >= skip_frames \
and (frame - skip_frames) % args.save_every_n_frames == 0:
# if last_control_changed < frame - args.save_every_n_frames:
# extra_frames += args.save_every_n_frames
# last_control_changed += args.save_every_n_frames
# else:
save_frame_idx += 1
for name, measurement in sensor_data.items():
filename = args.out_filename_format.format(
episode + 1, name, save_frame_idx)
measurement.save_to_disk(filename)
# We can access the encoded data of a given image as numpy
# array using its "data" property. For instance, to get the
# depth value (normalized) at pixel X, Y
#
# depth_array = sensor_data['CameraDepth'].data
# value_at_pixel = depth_array[Y, X]
#
# Now we have to send the instructions to control the vehicle.
# If we are in synchronous mode the server will pause the
# simulation until we send this control.
if not args.autopilot:
client.send_control(steer=random.uniform(-1.0, 1.0),
throttle=0.5,
brake=0.0,
hand_brake=False,
reverse=False)
else:
# Together with the measurements, the server has sent the
# control that the in-game autopilot would do this frame. We
# can enable autopilot by sending back this control to the
# server. We can modify it if wanted, here for instance we
# will add some noise to the steer.
control = measurements.player_measurements.autopilot_control
# if last_control:
# for v1, v2 in zip(control.values(), last_control.values()):
# if v1 != v2:
# last_control_changed = frame
# break
control.steer += random.uniform(-0.1, 0.1)
client.send_control(control)
def run_carla_client(args):
# Here we will run 3 episodes with 300 frames each.
number_of_episodes = 3
frames_per_episode = 300
# We assume the CARLA server is already waiting for a client to connect at
# host:port. To create a connection we can use the `make_carla_client`
# context manager, it creates a CARLA client object and starts the
# connection. It will throw an exception if something goes wrong. The
# context manager makes sure the connection is always cleaned up on exit.
with make_carla_client(args.host, args.port) as client:
print('CarlaClient connected')
for episode in range(0, number_of_episodes):
# Start a new episode.
if args.settings_filepath is None:
# 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=True,
SendNonPlayerAgentsInfo=True,
NumberOfVehicles=20,
NumberOfPedestrians=40,
WeatherId=random.choice([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 = Camera('CameraRGB')
# Set image resolution in pixels.
camera0.set_image_size(800, 600)
# Set its position relative to the car in meters.
camera0.set_position(0.30, 0, 1.30)
settings.add_sensor(camera0)
# Let's add another camera producing ground-truth depth.
camera1 = Camera('CameraDepth', PostProcessing='Depth')
camera1.set_image_size(800, 600)
camera1.set_position(0.30, 0, 1.30)
settings.add_sensor(camera1)
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)
else:
# Alternatively, we can load these settings from a file.
with open(args.settings_filepath, 'r') as fp:
settings = fp.read()
# Now we load these settings into the server. The server replies
# with a scene description containing the available start spots for
# the player. Here we can provide a CarlaSettings object or a
# CarlaSettings.ini file as string.
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))
# Notify the server that we want to start the episode at the
# player_start index. This function blocks until the server is ready
# to start the episode.
print('Starting new episode at %r...' % scene.map_name)
client.start_episode(player_start)
# Iterate every frame in the episode.
for frame in range(0, frames_per_episode):
# Read the data produced by the server this frame.
measurements, sensor_data = client.read_data()
# Print some of the measurements.
print_measurements(measurements)
# Save the images to disk if requested.
if args.save_images_to_disk:
for name, measurement in sensor_data.items():
filename = args.out_filename_format.format(episode, name, frame)
measurement.save_to_disk(filename)
# We can access the encoded data of a given image as numpy
# array using its "data" property. For instance, to get the
# depth value (normalized) at pixel X, Y
#
# depth_array = sensor_data['CameraDepth'].data
# value_at_pixel = depth_array[Y, X]
#
# Now we have to send the instructions to control the vehicle.
# If we are in synchronous mode the server will pause the
# simulation until we send this control.
if not args.autopilot:
client.send_control(
steer=random.uniform(-1.0, 1.0),
throttle=0.5,
brake=0.0,
hand_brake=False,
reverse=False)
else:
# Together with the measurements, the server has sent the
# control that the in-game autopilot would do this frame. We
# can enable autopilot by sending back this control to the
# server. We can modify it if wanted, here for instance we
# will add some noise to the steer.
control = measurements.player_measurements.autopilot_control
control.steer += random.uniform(-0.1, 0.1)
client.send_control(control)
def run_carla_client(host, port, far):
# Here we will run a single episode with 300 frames.
number_of_frames = 3000
frame_step = 100 # Save one image every 100 frames
output_folder = '_out'
image_size = [800, 600]
camera_local_pos = [0.3, 0.0, 1.3] # [X, Y, Z]
camera_local_rotation = [0, 0, 0] # [pitch(Y), yaw(Z), roll(X)]
fov = 70
# Connect with the server
with make_carla_client(host, port) as client:
print('CarlaClient connected')
# Here we load the settings.
settings = CarlaSettings()
settings.set(
SynchronousMode=True,
SendNonPlayerAgentsInfo=False,
NumberOfVehicles=20,
NumberOfPedestrians=40,
WeatherId=random.choice([1, 3, 7, 8, 14]))
settings.randomize_seeds()
camera1 = Camera('CameraDepth', PostProcessing='Depth', FOV=fov)
camera1.set_image_size(*image_size)
camera1.set_position(*camera_local_pos)
camera1.set_rotation(*camera_local_rotation)
settings.add_sensor(camera1)
camera2 = Camera('CameraRGB', PostProcessing='SceneFinal', FOV=fov)
camera2.set_image_size(*image_size)
camera2.set_position(*camera_local_pos)
camera2.set_rotation(*camera_local_rotation)
settings.add_sensor(camera2)
client.load_settings(settings)
# Start at location index id '0'
client.start_episode(0)
# Compute the camera transform matrix
camera_to_car_transform = camera2.get_unreal_transform()
# Iterate every frame in the episode except for the first one.
for frame in range(1, number_of_frames):
# Read the data produced by the server this frame.
measurements, sensor_data = client.read_data()
# Save one image every 'frame_step' frames
if not frame % frame_step:
# Start transformations time mesure.
timer = StopWatch()
# RGB image [[[r,g,b],..[r,g,b]],..[[r,g,b],..[r,g,b]]]
image_RGB = to_rgb_array(sensor_data['CameraRGB'])
# 2d to (camera) local 3d
# We use the image_RGB to colorize each 3D point, this is optional.
# "max_depth" is used to keep only the points that are near to the
# camera, meaning 1.0 the farest points (sky)
point_cloud = depth_to_local_point_cloud(
sensor_data['CameraDepth'],
image_RGB,
max_depth=far
)
# (Camera) local 3d to world 3d.
# Get the transform from the player protobuf transformation.
world_transform = Transform(
measurements.player_measurements.transform
)
# Compute the final transformation matrix.
car_to_world_transform = world_transform * camera_to_car_transform
# Car to World transformation given the 3D points and the
# transformation matrix.
point_cloud.apply_transform(car_to_world_transform)
# End transformations time mesure.
timer.stop()
# Save PLY to disk
# This generates the PLY string with the 3D points and the RGB colors
# for each row of the file.
point_cloud.save_to_disk(os.path.join(
output_folder, '{:0>5}.ply'.format(frame))
)
print_message(timer.milliseconds(), len(point_cloud), frame)
client.send_control(
measurements.player_measurements.autopilot_control
)
def run_carla_client(args):
# Here we will run 3 episodes with 300 frames each.
number_of_episodes = 5
cut_per_episode = 40
frames_per_cut = 200
# We assume the CARLA server is already waiting for a client to connect at
# host:port. To create a connection we can use the `make_carla_client`
# context manager, it creates a CARLA client object and starts the
# connection. It will throw an exception if something goes wrong. The
# context manager makes sure the connection is always cleaned up on exit.
with make_carla_client(args.host, args.port) as client:
print('CarlaClient connected')
for episode in range(0, number_of_episodes):
print("input any key to continue...")
start = input()
# each episode dir store a set of traindata. if dir not existed, then make it
pathdir = '/home/kadn/dataTrain/episode_{:0>3}'.format(episode)
mkdir(pathdir)
# 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=True,
SendNonPlayerAgentsInfo=True,
NumberOfVehicles=20,
NumberOfPedestrians=40,
# WeatherId=random.choice([1, 3, 7, 8, 14]),
WeatherId = 1,
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 = Camera('CameraRGB')
# Set image resolution in pixels.
camera0.set_image_size(88, 200)
# Set its position relative to the car in meters.
camera0.set_position(0.30, 0, 1.30)
settings.add_sensor(camera0)
# Let's add another camera producing ground-truth depth.
camera1 = Camera('CameraDepth', PostProcessing='Depth')
camera1.set_image_size(200, 88)
camera1.set_position(0.30, 0, 1.30)
settings.add_sensor(camera1)
camera2 = Camera('CameraSemSeg', PostProcessing='SemanticSegmentation')
camera2.set_image_size(88, 200)
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 = Lidar('Lidar32')
lidar.set_position(0, 0, 2.50)
lidar.set_rotation(0, 0, 0)
lidar.set(
Channels=0,
Range=30,
PointsPerSecond=200000,
RotationFrequency=10,
UpperFovLimit=0,
LowerFovLimit=0)
settings.add_sensor(lidar)
# else:
#
# # Alternatively, we can load these settings from a file.
# with open(args.settings_filepath, 'r') as fp:
# settings = fp.read()
# Now we load these settings into the server. The server replies
# with a scene description containing the available start spots for
# the player. Here we can provide a CarlaSettings object or a
# CarlaSettings.ini file as string.
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))
player_start = 1
# Notify the server that we want to start the episode at the
# player_start index. This function blocks until the server is ready
# to start the episode.
print('Starting new episode at %r...' % scene.map_name)
# Start a new episode.
client.start_episode(player_start)
for cut_per_episode in range(0,cut_per_episode):
num = fileCounter(pathdir)
filename = "data_{:0>6}.h5".format(num)
filepath = pathdir + '/' + filename
f = h5py.File(filepath, "w")
rgb_file = f.create_dataset("rgb", (200, 88, 200), np.uint8)
seg_file = f.create_dataset("seg", (200, 88, 200), np.uint8)
lidar_file = f.create_dataset('lidar',(200,200,200),np.uint8)
startendpoint = f.create_dataset('startend',(1,2),np.float32)
targets_file = f.create_dataset("targets", (200, 28), np.float32)
index_file = 0
# Iterate every frame in the episode.
for frame in range(0, frames_per_cut):
# Read the data produced by the server this frame.
measurements, sensor_data = client.read_data()
# get data and store
sensors, targets_data = record_train_data(measurements,sensor_data)
rgb_file[:,:,index_file] = sensors['rgb']
seg_file[:,:,index_file] = sensors['seg']
lidar_file[:,:,index_file] = sensors['lidar']
targets_file[index_file,:] = targets_data
index_file += 1
# We can access the encoded data of a given image as numpy
# array using its "data" property. For instance, to get the
# depth value (normalized) at pixel X, Y
#
# depth_array = sensor_data['CameraDepth'].data
# value_at_pixel = depth_array[Y, X]
#
# Now we have to send the instructions to control the vehicle.
# If we are in synchronous mode the server will pause the
# simulation until we send this control.
if args.autopilot:
client.send_control(
steer=0,
throttle=0.8,
brake=0.0,
hand_brake=False,
reverse=False)
else:
# Together with the measurements, the server has sent the
# control that the in-game autopilot would do this frame. We
# can enable autopilot by sending back this control to the
# server. We can modify it if wanted, here for instance we
# will add some noise to the steer.
control = measurements.player_measurements.autopilot_control
control.steer += random.uniform(-0.05, 0.05)
client.send_control(control)
def run(self):
settings = CarlaSettings()
settings.add_camera(Camera('DefaultCamera'))
self.run_carla_client(settings, 1, 2000, use_ai_control=True)
def run(self):
settings = CarlaSettings()
settings.add_camera(Camera('DefaultCamera'))
self.run_carla_client(settings, 5, 200)
def run(self):
settings = CarlaSettings(SynchronousMode=True)
settings.add_camera(Camera('DefaultCamera'))
self.run_carla_client(settings, 3, 200)
def run_carla_clients(args):
filename = '_images_repeatability/server{:d}/{:0>6d}.png'
with make_carla_client(args.host1, args.port1) as client1:
logging.info('1st client connected')
with make_carla_client(args.host2, args.port2) as client2:
logging.info('2nd client connected')
settings = CarlaSettings()
settings.set(
SynchronousMode=True,
SendNonPlayerAgentsInfo=True,
NumberOfVehicles=50,
NumberOfPedestrians=50,
WeatherId=random.choice([1, 3, 7, 8, 14]))
settings.randomize_seeds()
if args.images_to_disk:
camera = Camera('DefaultCamera')
camera.set_image_size(800, 600)
settings.add_sensor(camera)
scene1 = client1.load_settings(settings)
scene2 = client2.load_settings(settings)
number_of_player_starts = len(scene1.player_start_spots)
assert number_of_player_starts == len(scene2.player_start_spots)
player_start = random.randint(0, max(0, number_of_player_starts - 1))
logging.info(
'start episode at %d/%d player start (run forever, press ctrl+c to cancel)',
player_start,
number_of_player_starts)
client1.start_episode(player_start)
client2.start_episode(player_start)
frame = 0
while True:
frame += 1
meas1, sensor_data1 = client1.read_data()
meas2, sensor_data2 = client2.read_data()
player1 = meas1.player_measurements
player2 = meas2.player_measurements
images1 = [x for x in sensor_data1.values() if isinstance(x, Image)]
images2 = [x for x in sensor_data2.values() if isinstance(x, Image)]
control1 = player1.autopilot_control
control2 = player2.autopilot_control
try:
assert len(images1) == len(images2)
assert len(meas1.non_player_agents) == len(meas2.non_player_agents)
assert player1.transform.location.x == player2.transform.location.x
assert player1.transform.location.y == player2.transform.location.y
assert player1.transform.location.z == player2.transform.location.z
assert control1.steer == control2.steer
assert control1.throttle == control2.throttle
assert control1.brake == control2.brake
assert control1.hand_brake == control2.hand_brake
assert control1.reverse == control2.reverse
except AssertionError:
logging.exception('assertion failed')
if args.images_to_disk:
assert len(images1) == 1
images1[0].save_to_disk(filename.format(1, frame))
images2[0].save_to_disk(filename.format(2, frame))
client1.send_control(control1)
client2.send_control(control2)
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 run_carla_client(host, port, autopilot_on, save_images_to_disk, image_filename_format):
# Here we will run 3 episodes with 300 frames each.
number_of_episodes = 3
frames_per_episode = 300
# We assume the CARLA server is already waiting for a client to connect at
# host:port. To create a connection we can use the `make_carla_client`
# context manager, it creates a CARLA client object and starts the
# connection. It will throw an exception if something goes wrong. The
# context manager makes sure the connection is always cleaned up on exit.
with make_carla_client(host, port) as client:
print('CarlaClient connected')
for episode in range(0, number_of_episodes):
# Start a new episode.
# Create a CarlaSettings object. This object is a handy wrapper
# around the CarlaSettings.ini file. Here we set the configuration
# we want for the new episode.
settings = CarlaSettings()
settings.set(
SynchronousMode=True,
NumberOfVehicles=30,
NumberOfPedestrians=50,
WeatherId=random.choice([1, 3, 7, 8, 14]))
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 = Camera('CameraRGB')
# Set image resolution in pixels.
camera0.set_image_size(800, 600)
# Set its position relative to the car in centimeters.
camera0.set_position(30, 0, 130)
settings.add_camera(camera0)
# Let's add another camera producing ground-truth depth.
camera1 = Camera('CameraDepth', PostProcessing='Depth')
camera1.set_image_size(800, 600)
camera1.set_position(30, 0, 130)
settings.add_camera(camera1)
print('Requesting new episode...')
# Now we request a new episode with these settings. The server
# replies with a scene description containing the available start
# spots for the player. Here instead of a CarlaSettings object we
# could also provide a CarlaSettings.ini file as string.
scene = client.request_new_episode(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))
# Notify the server that we want to start the episode at
# `player_start`. This function blocks until the server is ready to
# start the episode.
client.start_episode(player_start)
# Iterate every frame in the episode.
for frame in range(0, frames_per_episode):
# Read the measurements and images produced by the server this
# frame.
measurements, images = client.read_measurements()
# Print some of the measurements we received.
print_player_measurements(measurements.player_measurements)
# Save the images to disk if requested.
if save_images_to_disk:
for n, image in enumerate(images):
image.save_to_disk(image_filename_format.format(episode, n, frame))
# Now we have to send the instructions to control the vehicle.
# If we are in synchronous mode the server will pause the
# simulation until we send this control.
if not autopilot_on:
client.send_control(
steer=random.uniform(-1.0, 1.0),
throttle=0.3,
brake=False,
hand_brake=False,
reverse=False)
else:
# Together with the measurements, the server has sent the
# control that the in-game AI would do this frame. We can
# enable autopilot by sending back this control to the
# server. Here we will also add some noise to the steer.
control = measurements.player_measurements.ai_control
control.steer += random.uniform(-0.1, 0.1)
client.send_control(control)
print('Done.')
return True
