def visualize_pedestrian():
config = parse_arguments()
client = carla.Client(config.host, config.port)
client.set_timeout(5.0)
world = client.get_world()
carla_map = world.get_map()
walker_blueprints = world.get_blueprint_library().filter("walker.*")
spawn_point = carla_map.get_spawn_points()[0]
pedestrian = None
spectator = world.get_spectator()
for blueprint in walker_blueprints:
try:
print("Showing pedestrian", blueprint)
pedestrian = world.spawn_actor(blueprint, spawn_point)
world.wait_for_tick()
iterations = 40
theta = np.linspace(0, 1*math.pi, iterations)
phi = (5/6 / 2)*math.pi
r = 2
for jdx in range(iterations):
transform = carlautil.spherical_to_camera_watcher_transform(
r, theta[jdx], phi, location=pedestrian.get_location())
# transform = carlautil.strafe_transform(
# transform, right=0, above=0)
spectator.set_transform(transform)
world.wait_for_tick()
finally:
if pedestrian:
pedestrian.destroy()
def __set_random_frame(self,
spectator,
transform,
vehicle=None,
strafe_camera=False,
xy_shift_camera=True):
"""
TODO: the camera transform should be relative
to the yaw of vehicle transform, not just vehicle location
"""
r = random.uniform(*self.range_r)
theta = random.uniform(*self.range_theta)
phi = random.uniform(*self.range_phi)
_transform = carla.Transform(
transform.location, carla.Rotation(yaw=transform.rotation.yaw))
if xy_shift_camera:
# NOTE: the Audi A2 has dimensions (3.70 m, 1.79 m)
x_shift = random.uniform(-self.max_shift, self.max_shift)
y_shift = random.uniform(-self.max_shift, self.max_shift)
_transform.location += carla.Location(x=x_shift, y=y_shift)
_transform = carlautil.spherical_to_camera_watcher_transform(
r, theta, phi, pin=_transform)
if strafe_camera and vehicle:
# NOTE: GIRAFFE does not do camera strafing, it does camera shifting
near_frac = vehicle.bounding_box.extent.x
ratio_f = near_frac / self.range_r[0]
strafe_amt = r * ratio_f - near_frac
right_strafe = random.uniform(-strafe_amt, strafe_amt)
above_strafe = random.uniform(-strafe_amt, strafe_amt)
_transform = carlautil.strafe_transform(_transform,
right=right_strafe,
above=above_strafe)
spectator.set_transform(_transform)
def demo_night_lights(self, spectator, vehicle):
"""
NOTE: for CARLA 0.9.11/12, not all cars have lights
"""
iterations = 300
theta = np.linspace(-math.pi / 2, (3 / 2) * math.pi, iterations)
phi = (1 / 3) * math.pi
r = (self.near_r + self.far_r) / 2.
original_lightstate = vehicle.get_light_state()
vls = carla.VehicleLightState
light_state = vls(vls.LowBeam | vls.Interior | vls.Reverse
| vls.Position)
vehicle.set_light_state(light_state)
weather = self.world.get_weather()
weather.sun_altitude_angle = -15
self.world.set_weather(weather)
for jdx in range(iterations):
# set spectator orientation and position
transform = carlautil.spherical_to_camera_watcher_transform(
r, theta[jdx], phi, location=vehicle.get_location())
transform = carlautil.strafe_transform(transform, right=0, above=0)
spectator.set_transform(transform)
# wait for server before continuing
if jdx == 0 or jdx == iterations - 1:
for _ in range(50):
self.world.wait_for_tick()
else:
self.world.wait_for_tick()
vehicle.set_light_state(original_lightstate)
def demo_all_lights(self, spectator, vehicle):
iterations = 150
theta = np.linspace(-math.pi/2, math.pi/2, iterations)
phi = math.pi / 4
r = 5
sun_altitude_angles = np.linspace(1, -19, iterations)
original_lightstate = vehicle.get_light_state()
light_types = ["Position", "LowBeam", "HighBeam", "Brake",
"RightBlinker", "LeftBlinker", "Reverse", "Fog",
"Interior", "Special1", "Special2", "All"]
for light_type in light_types:
print(f"Demonstrating vehicle {light_type} lights.")
vehicle.set_light_state(getattr(carla.VehicleLightState, light_type))
for jdx in range(iterations):
# set spectator orientation and position
transform = carlautil.spherical_to_camera_watcher_transform(
r, theta[jdx], phi, location=vehicle.get_location())
transform = carlautil.strafe_transform(transform, right=0, above=0)
spectator.set_transform(transform)
# set weather
weather = self.world.get_weather()
weather.sun_altitude_angle = sun_altitude_angles[jdx]
self.world.set_weather(weather)
# wait for server before continuing
if jdx == 0 or jdx == iterations - 1:
for _ in range(50): self.world.wait_for_tick()
else:
self.world.wait_for_tick()
vehicle.set_light_state(original_lightstate)
def inspect_vehicle():
config = parse_arguments()
client = carla.Client(config.host, config.port)
client.set_timeout(10.0)
world = client.get_world()
carla_map = world.get_map()
blueprint = world.get_blueprint_library().find("vehicle.audi.a2")
spawn_point = carla_map.get_spawn_points()[0]
vehicle = None
try:
vehicle = world.spawn_actor(blueprint, spawn_point)
world.wait_for_tick()
transform = carlautil.spherical_to_camera_watcher_transform(
3, math.pi, math.pi*(1/6),
location=vehicle.get_location())
world.get_spectator().set_transform(transform)
world.wait_for_tick()
def get_forward_vector():
""" The vehicle's forward vector is a unit vector """
f = vehicle.get_transform().get_forward_vector()
f = np.array([f.x, f.y, f.z])
print( np.linalg.norm(f) )
def get_bounding_box():
bb = vehicle.bounding_box
e = bb.extent
print(np.array([e.x, e.y, e.z])*2)
# get_bounding_box()
finally:
if vehicle:
vehicle.destroy()
def __set_random_frame(self,
spectator,
vehicle,
strafe_camera=False,
xy_shift_camera=True):
r = random.uniform(self.near_r, self.far_r)
theta = random.uniform(0, 2 * math.pi)
phi = random.uniform((5 / 14) * math.pi, (1 / 6) * math.pi)
location = vehicle.get_location()
if xy_shift_camera:
# NOTE: the Audi A2 has dimensions (3.70 m, 1.79 m)
x_shift = random.uniform(self.min_shift, self.max_shift)
y_shift = random.uniform(self.min_shift, self.max_shift)
location += carla.Location(x=x_shift, y=y_shift)
transform = carlautil.spherical_to_camera_watcher_transform(
r, theta, phi, location=location)
if strafe_camera:
# NOTE: GIRAFFE does not do camera strafing, it does camera shifting
near_frac = vehicle.bounding_box.extent.x
ratio_f = near_frac / self.near_r
strafe_amt = r * ratio_f - near_frac
right_strafe = random.uniform(-strafe_amt, strafe_amt)
above_strafe = random.uniform(-strafe_amt, strafe_amt)
transform = carlautil.strafe_transform(transform,
right=right_strafe,
above=above_strafe)
spectator.set_transform(transform)
def visualize_distances():
config = parse_arguments()
client = carla.Client(config.host, config.port)
client.set_timeout(10.0)
world = client.get_world()
carla_map = world.get_map()
blueprints = world.get_blueprint_library().filter("vehicle.*")
blueprints = [x for x in blueprints if int(x.get_attribute("number_of_wheels")) == 4]
blueprints = [x for x in blueprints if not x.id.endswith('isetta')]
blueprints = [x for x in blueprints if not x.id.endswith('carlacola')]
blueprints = [x for x in blueprints if not x.id.endswith('firetruck')]
blueprints = [x for x in blueprints if not x.id.endswith('cybertruck')]
blueprints = [x for x in blueprints if not x.id.endswith('ambulance')]
blueprints = [x for x in blueprints if not x.id.endswith('sprinter')]
blueprints = [x for x in blueprints if not x.id.endswith('t2')]
# blueprint = world.get_blueprint_library().find("vehicle.audi.a2")
blueprint = random.choice(blueprints)
spawn_point = carla_map.get_spawn_points()[0]
vehicle = None
try:
vehicle = world.spawn_actor(blueprint, spawn_point)
transform = carlautil.spherical_to_camera_watcher_transform(
3, math.pi, math.pi*(1/6),
pin=spawn_point.location)
world.get_spectator().set_transform(transform)
thickness = 0.2
color = carla.Color(r=255, g=0, b=0, a=100)
life_time = 6
loc = carlautil.to_location_ndarray(spawn_point.location)
scale = 2.
z = loc[2] + 0.5
box = np.array([[-1., -1.], [1., -1.], [1., 1.], [-1., 1.]])
box = (box*scale) + loc[:2]
world.debug.draw_line(
carla.Location(box[0, 0], box[0, 1], z),
carla.Location(box[1, 0], box[1, 1], z),
thickness=thickness, color=color, life_time=life_time)
world.debug.draw_line(
carla.Location(box[1, 0], box[1, 1], z),
carla.Location(box[2, 0], box[2, 1], z),
thickness=thickness, color=color, life_time=life_time)
world.debug.draw_line(
carla.Location(box[2, 0], box[2, 1], z),
carla.Location(box[3, 0], box[3, 1], z),
thickness=thickness, color=color, life_time=life_time)
world.debug.draw_line(
carla.Location(box[3, 0], box[3, 1], z),
carla.Location(box[0, 0], box[0, 1], z),
thickness=thickness, color=color, life_time=life_time)
time.sleep(life_time)
world.wait_for_tick()
finally:
if vehicle:
vehicle.destroy()
def visualize_wheel_turning_2():
"""
Q: is the steering immediate?
A: no it takes time. Small steering rate (i.e. setting steer=0.2) is fast.
The larger the change in steering, the longer it takes the wheels to change from
the current angle to the intended angle.
https://github.com/carla-simulator/carla/issues/4655
"""
config = parse_arguments()
client = carla.Client(config.host, config.port)
client.set_timeout(10.0)
world = client.get_world()
carla_map = world.get_map()
blueprint = world.get_blueprint_library().find("vehicle.audi.a2")
spawn_point = carla_map.get_spawn_points()[0]
vehicle = None
try:
vehicle = world.spawn_actor(blueprint, spawn_point)
world.wait_for_tick()
phys_control = vehicle.get_physics_control()
wheel = phys_control.wheels[1]
transform = carlautil.spherical_to_camera_watcher_transform(
3, math.pi, math.pi*(1/6),
location=vehicle.get_location())
world.get_spectator().set_transform(transform)
for _ in range(100): world.wait_for_tick()
world.wait_for_tick()
vehicle.apply_control(carla.VehicleControl(steer=0.2))
world.wait_for_tick()
time.sleep(0.5)
world.wait_for_tick()
vehicle.apply_control(carla.VehicleControl(steer=0.0))
world.wait_for_tick()
time.sleep(0.5)
world.wait_for_tick()
vehicle.apply_control(carla.VehicleControl(steer=0.5))
world.wait_for_tick()
time.sleep(0.5)
world.wait_for_tick()
vehicle.apply_control(carla.VehicleControl(steer=0.0))
world.wait_for_tick()
time.sleep(0.5)
world.wait_for_tick()
vehicle.apply_control(carla.VehicleControl(steer=1.0))
world.wait_for_tick()
time.sleep(0.5)
for _ in range(200): world.wait_for_tick()
finally:
if vehicle:
vehicle.destroy()
def demo_azimuthal_rotation(world, spectator, vehicle, iterations=300):
theta = np.linspace(0, 2*math.pi, iterations)
phi = math.pi / 4
r = 4
for jdx in range(iterations):
transform = carlautil.spherical_to_camera_watcher_transform(
r, theta[jdx], phi, location=vehicle.get_location())
transform = carlautil.strafe_transform(transform, right=0, above=0)
spectator.set_transform(transform)
if jdx == 0 or jdx == iterations - 1:
for _ in range(50): world.wait_for_tick()
else:
world.wait_for_tick()
def visualize_wheel_turning_1():
"""This method shows that setting steer = 1.0 makes the vehicle
turn to the max steering angle."""
config = parse_arguments()
client = carla.Client(config.host, config.port)
client.set_timeout(10.0)
world = client.get_world()
carla_map = world.get_map()
blueprint = world.get_blueprint_library().find("vehicle.audi.a2")
spawn_point = carla_map.get_spawn_points()[0]
vehicle = None
try:
vehicle = world.spawn_actor(blueprint, spawn_point)
world.wait_for_tick()
phys_control = vehicle.get_physics_control()
wheel = phys_control.wheels[1]
transform = carlautil.spherical_to_camera_watcher_transform(
3, math.pi, math.pi*(1/6),
location=vehicle.get_location())
world.get_spectator().set_transform(transform)
# Q1: does applying steering control once persist across many ticks?
world.wait_for_tick()
vehicle.apply_control(carla.VehicleControl(steer=1.0))
world.wait_for_tick()
phys_control = vehicle.get_physics_control()
wheel = phys_control.wheels[1]
location = vehicle.get_location()
transform = vehicle.get_transform()
end = location + 5*transform.get_forward_vector()
world.debug.draw_line(location, end,
thickness=0.1, life_time=15.0)
# Q2: does steer=1.0 correspond with wheel.max_steer_angle?
location = vehicle.get_location()
transform = vehicle.get_transform()
theta = math.radians(90 - wheel.max_steer_angle)
direction = math.sin(theta)*transform.get_forward_vector() \
+ math.cos(theta)*transform.get_right_vector()
end = location + 5*direction
world.debug.draw_line(location, end,
thickness=0.1, life_time=15.0)
# A1: yes it does.
for _ in range(800): world.wait_for_tick()
finally:
if vehicle:
vehicle.destroy()
def demo_radius(self, spectator, vehicle):
iterations = 100
theta = math.pi / 2
phi = math.pi / 4
r = np.linspace(self.near_r, 5, iterations)
for jdx in range(iterations):
transform = carlautil.spherical_to_camera_watcher_transform(
r[jdx], theta, phi, location=vehicle.get_location())
transform = carlautil.strafe_transform(transform, right=0, above=0)
spectator.set_transform(transform)
if jdx == 0 or jdx == iterations - 1:
for _ in range(50): self.world.wait_for_tick()
else:
self.world.wait_for_tick()
def demo_polar_rotation(self, spectator, vehicle):
iterations = 200
theta = math.pi / 3
phi = np.linspace((5/14)*math.pi, (1/6)*math.pi, iterations)
r = 4
for jdx in range(iterations):
transform = carlautil.spherical_to_camera_watcher_transform(
r, theta, phi[jdx], location=vehicle.get_location())
transform = carlautil.strafe_transform(transform, right=0, above=0)
spectator.set_transform(transform)
if jdx == 0 or jdx == iterations - 1:
for _ in range(50): self.world.wait_for_tick()
else:
self.world.wait_for_tick()
def __set_random_frame(self, spectator, vehicle):
r = random.uniform(self.near_r, 4.5)
theta = random.uniform(0, 2*math.pi)
phi = random.uniform((5/14)*math.pi, (1/6)*math.pi)
near_frac = vehicle.bounding_box.extent.x
ratio_f = near_frac / self.near_r
strafe_amt = r*ratio_f - near_frac
right_strafe = random.uniform(-strafe_amt, strafe_amt)
above_strafe = random.uniform(-strafe_amt, strafe_amt)
transform = carlautil.spherical_to_camera_watcher_transform(
r, theta, phi, location=vehicle.get_location())
transform = carlautil.strafe_transform(transform,
right=right_strafe, above=above_strafe)
spectator.set_transform(transform)
def demo_shift(self, spectator, vehicle):
iterations = 100
theta = math.pi / 2
phi = math.pi / 4
r = np.linspace(self.near_r, 5, iterations)
near_frac = vehicle.bounding_box.extent.x
ratio_f = near_frac / self.near_r
for jdx in range(iterations):
transform = carlautil.spherical_to_camera_watcher_transform(
r[jdx], theta, phi, location=vehicle.get_location())
transform = carlautil.strafe_transform(transform,
right=r[jdx]*ratio_f - near_frac,
above=r[jdx]*ratio_f - near_frac)
spectator.set_transform(transform)
if jdx == 0 or jdx == iterations - 1:
for _ in range(50): self.world.wait_for_tick()
else:
self.world.wait_for_tick()
def inspect_entity_dimensions():
config = parse_arguments()
client = carla.Client(config.host, config.port)
client.set_timeout(5.0)
world = client.get_world()
carla_map = world.get_map()
spawn_point = carla_map.get_spawn_points()[0]
# vehicle blueprints
blueprints = world.get_blueprint_library().filter("vehicle.*")
blueprints = [x for x in blueprints if int(x.get_attribute("number_of_wheels")) == 4]
blueprints = [x for x in blueprints if not x.id.endswith('isetta')]
blueprints = [x for x in blueprints if not x.id.endswith('carlacola')]
blueprints = [x for x in blueprints if not x.id.endswith('firetruck')]
blueprints = [x for x in blueprints if not x.id.endswith('cybertruck')]
blueprints = [x for x in blueprints if not x.id.endswith('ambulance')]
blueprints = [x for x in blueprints if not x.id.endswith('sprinter')]
blueprints = [x for x in blueprints if not x.id.endswith('t2')]
# walker blueprints
walker_blueprints = world.get_blueprint_library().filter("walker.*")
vehicle = None
pedestrian = None
spectator = world.get_spectator()
logging = util.AttrDict(
vehicle=util.AttrDict(
xs=[],
d2s=[],
d3s=[]
),
pedestrian=util.AttrDict(
xs=[],
d2s=[],
d3s=[]
)
)
for blueprint in blueprints:
try:
vehicle = world.spawn_actor(blueprint, spawn_point)
world.wait_for_tick()
transform = carlautil.spherical_to_camera_watcher_transform(
5, math.pi, math.pi*(1/6),
pin=spawn_point.location)
spectator.set_transform(transform)
world.wait_for_tick()
x = carlautil.actor_to_bbox_ndarray(vehicle)
d2 = np.linalg.norm(x[:2] / 2)
d3 = np.linalg.norm(x / 2)
logging.vehicle.xs.append(x)
logging.vehicle.d2s.append(d2)
logging.vehicle.d3s.append(d3)
print(blueprint.id)
print(x)
time.sleep(0.1)
finally:
if vehicle:
vehicle.destroy()
vehicle = None
world.wait_for_tick()
for blueprint in walker_blueprints:
try:
pedestrian = world.spawn_actor(blueprint, spawn_point)
world.wait_for_tick()
transform = carlautil.spherical_to_camera_watcher_transform(
5, math.pi, math.pi*(1/6),
pin=spawn_point.location)
spectator.set_transform(transform)
world.wait_for_tick()
x = carlautil.actor_to_bbox_ndarray(pedestrian)
d2 = np.linalg.norm(x[:2] / 2)
d3 = np.linalg.norm(x / 2)
logging.pedestrian.xs.append(x)
logging.pedestrian.d2s.append(d2)
logging.pedestrian.d3s.append(d3)
finally:
if pedestrian:
pedestrian.destroy()
pedestrian = None
for k, entity in logging.items():
entity.xs = np.stack(entity.xs)
entity.d2s = np.stack(entity.d2s)
entity.d3s = np.stack(entity.d3s)
print(f"Vehicle dimensions { np.max(logging.vehicle.xs, 0) }")
print(f" max 2D distance from origin { np.max(logging.vehicle.d2s) }")
print(f" max 3D distance from origin { np.max(logging.vehicle.d3s) }")
print(f"Pedestrian dimensions { np.mean(logging.pedestrian.xs, 0) }")
print(f" max 2D distance from origin { np.max(logging.pedestrian.d2s) }")
print(f" max 3D distance from origin { np.max(logging.pedestrian.d3s) }")
def visualize_vehicles_in_the_dark():
"""Cars with lights:
audi.tt
mercedes.sprinter
dodge.charger_police
mercedes.coupe_2020
dodge.charger_police_2020
mini.cooper_s_2021
bh crossbike
lincoln.mkz_2020
lincoln.mkz_2017
ford.mustnge
tesla ybertruck
ford ambulance
nissan patrol_2021
yamaha yzf
chevrolet impala
volkswagen t2
diamondback century
tesla model3
carlamotos firetruck
audi etron
dodge charger_2020
gazelle omafiets
harley-deavidson low_rider
"""
config = parse_arguments()
client = carla.Client(config.host, config.port)
client.set_timeout(5.0)
world = client.get_world()
carla_map = world.get_map()
weather = world.get_weather()
weather.sun_altitude_angle = -15
world.set_weather(weather)
vehicle_blueprints = world.get_blueprint_library().filter("vehicle.*")
spawn_point = carla_map.get_spawn_points()[0]
vehicle = None
pedestrian = None
spectator = world.get_spectator()
for blueprint in vehicle_blueprints:
try:
print("Showing vehicle", blueprint)
vehicle = world.spawn_actor(blueprint, spawn_point)
world.wait_for_tick()
vls = carla.VehicleLightState
light_state = vls(vls.LowBeam | vls.Interior | vls.Reverse | vls.Position)
vehicle.set_light_state(light_state)
iterations = 100
theta = np.linspace(0, 1*math.pi, iterations)
phi = math.pi / 4
r = 5
for jdx in range(iterations):
transform = carlautil.spherical_to_camera_watcher_transform(
r, theta[jdx], phi, location=vehicle.get_location())
# transform = carlautil.strafe_transform(
# transform, right=0, above=0)
spectator.set_transform(transform)
world.wait_for_tick()
finally:
if vehicle:
vehicle.destroy()
def visualize_wheel_turning_3():
config = parse_arguments()
client = carla.Client(config.host, config.port)
client.set_timeout(10.0)
world = client.get_world()
carla_map = world.get_map()
blueprint = world.get_blueprint_library().find("vehicle.audi.a2")
spawn_point = carla_map.get_spawn_points()[0]
vehicle = None
vwl = carla.VehicleWheelLocation
try:
vehicle = world.spawn_actor(blueprint, spawn_point)
for _ in range(20): world.wait_for_tick()
transform = carlautil.spherical_to_camera_watcher_transform(
3, math.pi, math.pi*(1/6),
location=vehicle.get_location())
world.get_spectator().set_transform(transform)
for _ in range(20): world.wait_for_tick()
fl_angles = dict()
fr_angles = dict()
def plot(snapshot):
fl_angle = vehicle.get_wheel_steer_angle(vwl.FL_Wheel)
fr_angle = vehicle.get_wheel_steer_angle(vwl.FR_Wheel)
fl_angles[snapshot.timestamp.elapsed_seconds] = fl_angle
fr_angles[snapshot.timestamp.elapsed_seconds] = fr_angle
def derivative(x, y):
assert len(x) == len(y)
dy = [None]*(len(x) - 1)
for i in range(len(x) - 1):
dy[i] = (y[i + 1] - y[i]) / (x[i + 1] - x[i])
assert len(x[:-1]) == len(dy)
return x[:-1], dy
## Block 1
callback_id = world.on_tick(plot)
"""get_wheel_steer_angle() returns angle in degrees between
45 and 70 deg so the actual turning is more like 57.5 deg.
The wheel on the side the car is turning turns a higher angle.
Wheels reach max turns from 0 in 0.2 seconds so 287.5 deg/s."""
steering_choices = [0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0]
# steering_choices = [0.6]
for steer in steering_choices:
for _ in range(6): world.wait_for_tick()
time.sleep(0.8)
for _ in range(6): world.wait_for_tick()
vehicle.apply_control(carla.VehicleControl(steer=steer))
for _ in range(6): world.wait_for_tick()
time.sleep(0.8)
for _ in range(6): world.wait_for_tick()
vehicle.apply_control(carla.VehicleControl(steer=0))
for _ in range(6): world.wait_for_tick()
time.sleep(0.8)
world.remove_on_tick(callback_id)
world.wait_for_tick()
fig, axes = plt.subplots(1, 2, figsize=(20,10))
_time, _angles = util.unzip(fl_angles.items())
axes[0].plot(_time, _angles, "-bo", label="FL_Wheel")
_time, _dangles = derivative(_time, _angles)
axes[1].plot(_time, _dangles, "-bo", label="FL_Wheel")
_time, _angles = util.unzip(fr_angles.items())
axes[0].plot(_time, _angles, "-ro", label="FR_Wheel")
_time, _dangles = derivative(_time, _angles)
axes[1].plot(_time, _dangles, "-ro", label="FR_Wheel")
axes[0].legend()
fig.savefig("out/steer")
# plt.show()
finally:
if vehicle:
vehicle.destroy()
vehicle = None
