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)
return settings
def run_driving_benchmark(agent,
experiment_suite,
city_name='Town01',
log_name='Test',
continue_experiment=False,
host='127.0.0.1',
port=2000):
while True:
try:
with make_carla_client(host, port) as client:
# Hack to fix for the issue 310, we force a reset, so it does not get
# the positions on first server reset.
client.load_settings(CarlaSettings())
client.start_episode(0)
# We instantiate the driving benchmark, that is the engine used to
# benchmark an agent. The instantiation starts the log process, sets
benchmark = DrivingBenchmark(
city_name=city_name,
name_to_save=log_name + '_' +
type(experiment_suite).__name__ + '_' + city_name,
continue_experiment=continue_experiment)
# This function performs the benchmark. It returns a dictionary summarizing
# the entire execution.
benchmark_summary = benchmark.benchmark_agent(
experiment_suite, agent, client)
print("")
print("")
print(
"----- Printing results for training weathers (Seen in Training) -----"
)
print("")
print("")
av = results_printer.print_summary(
benchmark_summary, experiment_suite.train_weathers,
benchmark.get_path())
open(
'/home/rsi/Desktop/CAL/PythonClient/_benchmarks_results/' +
log_name + '_av_succ_' + str(av) + '.txt', 'w')
print("")
print("")
print(
"----- Printing results for test weathers (Unseen in Training) -----"
)
print("")
print("")
results_printer.print_summary(benchmark_summary,
experiment_suite.test_weathers,
benchmark.get_path())
break
except TCPConnectionError as error:
logging.error(error)
time.sleep(2)
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 _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(0.1, 0, 1.7)
settings.add_sensor(camera1)
camera2 = Camera("CameraRGB")
camera2.set_image_size(self.config["render_x_res"],
self.config["render_y_res"])
camera2.set_position(0.1, 0, 1.7)
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 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 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 run(self):
settings = CarlaSettings(QualityLevel='Low')
settings.add_sensor(Lidar('DefaultLidar'))
settings.add_sensor(Camera('DefaultCamera'))
settings.add_sensor(Camera('DefaultDepth', PostProcessing='Depth'))
settings.add_sensor(
Camera('DefaultSemSeg', PostProcessing='SemanticSegmentation'))
self.run_carla_client(settings, 3, 200)
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 depend on the selected Town.
"""
# We set the camera
# This single RGB camera is used on every experiment
camera = Camera('CameraRGB')
camera.set(FOV=90)
camera.set_image_size(800, 600)
camera.set_position(1.44, 0.0, 1.2)
camera.set_rotation(0, 0, 0)
if self._city_name == 'Town01':
poses_tasks = self._poses_town01()
vehicles_tasks = [0, 20, 100]
pedestrians_tasks = [0, 50, 250]
else:
poses_tasks = self._poses_town02()
vehicles_tasks = [0, 15, 70]
pedestrians_tasks = [0, 50, 150]
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,
Repetitions=1
)
experiments_vector.append(experiment)
return experiments_vector
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', 0.1653, 50)
else:
image = mpimg.imread("carla/planner/Town02.png")
carla_map = CarlaMap('Town02', 0.1653, 50)
fig, 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.axis('off')
plt.show()
fig.savefig('town_positions.pdf',
orientation='landscape',
bbox_inches='tight')
def make_base_settings():
return CarlaSettings(WeatherId=1,
SendNonPlayerAgentsInfo=False,
SynchronousMode=False,
NumberOfVehicles=20,
NumberOfPedestrians=30,
SeedVehicles=123456789,
SeedPedestrians=123456789,
QualityLevel='Epic')
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 _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 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 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:
print(scene.map_name)
image = mpimg.imread('./environment/%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)
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.axis('off')
plt.show()
fig.savefig('town_positions.pdf',
orientation='landscape',
bbox_inches='tight')
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 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 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 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 __init__(self,
client,
frame_skip=1,
cam_width=800,
cam_height=600,
town_string='Town01'):
super(StraightDriveEnv, self).__init__()
self.frame_skip = frame_skip
self.client = client
self._planner = Planner(town_string)
camera0 = Camera('CameraRGB')
camera0.set(CameraFOV=100)
camera0.set_image_size(cam_height, cam_width)
camera0.set_position(200, 0, 140)
camera0.set_rotation(-15.0, 0, 0)
self.start_goal_pairs = [[36, 40], [39, 35], [110, 114], [7,
3], [0, 4],
[68, 50], [61, 59], [47, 64], [147, 90],
[33, 87], [26, 19], [80, 76], [45, 49],
[55, 44], [29, 107], [95, 104], [84, 34],
[53, 67], [22, 17], [91, 148], [20, 107],
[78, 70], [95, 102], [68, 44], [45, 69]]
vehicles = 0
pedestrians = 0
weather = 1
settings = CarlaSettings()
settings.set(
SynchronousMode=True,
SendNonPlayerAgentsInfo=True,
NumberOfVehicles=vehicles,
NumberOfPedestrians=pedestrians,
WeatherId=weather,
)
settings.randomize_seeds()
settings.add_sensor(camera0)
self.scene = self.client.load_settings(settings)
img_shape = (cam_width, cam_height, 3)
self.observation_space = spaces.Tuple(
(spaces.Box(-np.inf, np.inf, (3, )), spaces.Box(0, 255,
img_shape)))
self.action_space = spaces.Box(-np.inf, np.inf, shape=(3, ))
self.prev_state = np.array([0., 0., 0.])
self.prev_collisions = np.array([0., 0., 0.])
self.prev_intersections = np.array([0., 0.])
def setup_carla_client(self, client, params):
self.client = client
self.param_sensors = params.get('sensors', {})
self.carla_settings = CarlaSettings()
self.carla_settings.set(
SendNonPlayerAgentsInfo=params.get('SendNonPlayerAgentsInfo',
True),
NumberOfVehicles=params.get('NumberOfVehicles', 20),
NumberOfPedestrians=params.get('NumberOfPedestrians', 40),
WeatherId=params.get('WeatherId', random.choice([1, 3, 7, 8, 14])),
SynchronousMode=params.get('SynchronousMode', True),
QualityLevel=params.get('QualityLevel', 'Low'))
self.carla_settings.randomize_seeds()
def reset(self):
# connect to server
self._client = CarlaClient(self._host, self._port, self._timeout)
self._client.connect()
# settings
index = random.randint(0, 4) # Last one is for testing
# print(index)
# index = 0
seed = npc_vehicle_seeds[index]
start_list_index = start_list_indices[index]
settings = CarlaSettings()
settings.set(SynchronousMode=True,
SendNonPlayerAgentsInfo=True,
NumberOfVehicles=1,
NumberOfPedestrians=0,
SeedVehicles=seed,
SeedPedestrians=123456789,
WeatherId=weathers[index])
self._client.load_settings(settings)
self._client.start_episode(start_list_index)
# simulator init stage
for i in range(10):
measurements, _ = self._client.read_data()
self._client.send_control(steer=0,
throttle=0,
brake=0,
hand_brake=False,
reverse=False)
self._client.send_control(steer=0,
throttle=0,
brake=0,
hand_brake=False,
reverse=False)
# Reset Flags
self._reset = True
self._history_path = np.zeros([self._history_path_num, 4])
self._cur_steer = 0
self._his_steer = 0
observation = self._observe()
self._observation = observation
return observation
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.
Sets exactly three vehicles and pedestrians, with random weather conditions.
"""
settings = CarlaSettings()
settings.set(
SynchronousMode=False,
SendNonPlayerAgentsInfo=True,
NumberOfVehicles=3,
NumberOfPedestrians=3,
WeatherId=random.choice([1, 3, 7, 8, 14]),
QualityLevel=QUALITY_LEVEL)
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)
# --------------------------- 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 _reset(self):
self.num_steps = 0
self.prev_measurement = 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.weather = random.choice(self.config["weather"])
settings.set(SynchronousMode=True,
SendNonPlayerAgentsInfo=True,
NumberOfVehicles=self.config["num_vehicles"],
NumberOfPedestrians=self.config["num_pedestrians"],
WeatherId=self.weather)
settings.randomize_seeds()
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)
scene = self.client.load_settings(settings)
# Choose one player start at random.
number_of_player_starts = len(scene.player_start_spots)
if self.config["random_starting_location"]:
self.player_start = random.randint(
0, max(0, number_of_player_starts - 1))
else:
self.player_start = 0
# 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.player_start)
image, py_measurements = self._read_observation()
self.prev_measurement = py_measurements
return self.preprocess_image(image)
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, 0, 0, 20]
pedestrians_tasks = [0, 0, 0, 50]
task_names = ['straight', 'one_curve', 'navigation', 'navigation_dyn']
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()
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 __init__(self,
name,
flags,
auto_pilot,
camera_setups=[],
lidar_setups=[],
log_file_name=None,
csv_file_name=None):
super(CarlaLegacyOperator, 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._auto_pilot = auto_pilot
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._transforms = {}
# Add cameras to the simulation.
for cs in camera_setups:
self.__add_camera(cs)
self._transforms[cs.name] = cs.get_transform()
# Add lidars to the simulation.
for ls in lidar_setups:
self.__add_lidar(ls)
self._transforms[ls.name] = ls.get_transform()
self.agent_id_map = {}
self.pedestrian_count = 0
# Initialize the control state.
self.control = {
'steer': 0.0,
'throttle': 0.0,
'brake': 0.0,
'hand_brake': False,
'reverse': False
}
# Register custom serializers for Messages and WatermarkMessages
ray.register_custom_serializer(Message, use_pickle=True)
ray.register_custom_serializer(WatermarkMessage, use_pickle=True)
