carla/PythonAPI/examples/visualize_multiple_sensors.py

388 lines
13 KiB
Python

#!/usr/bin/env python
# Copyright (c) 2020 Computer Vision Center (CVC) at the Universitat Autonoma de
# Barcelona (UAB).
#
# This work is licensed under the terms of the MIT license.
# For a copy, see <https://opensource.org/licenses/MIT>.
"""
Script that render multiple sensors in the same pygame window
By default, it renders four cameras, one LiDAR and one Semantic LiDAR.
It can easily be configure for any different number of sensors.
To do that, check lines 290-308.
"""
import glob
import os
import sys
try:
sys.path.append(glob.glob('../carla/dist/carla-*%d.%d-%s.egg' % (
sys.version_info.major,
sys.version_info.minor,
'win-amd64' if os.name == 'nt' else 'linux-x86_64'))[0])
except IndexError:
pass
import carla
import argparse
import random
import time
import numpy as np
try:
import pygame
from pygame.locals import K_ESCAPE
from pygame.locals import K_q
except ImportError:
raise RuntimeError('cannot import pygame, make sure pygame package is installed')
class CustomTimer:
def __init__(self):
try:
self.timer = time.perf_counter
except AttributeError:
self.timer = time.time
def time(self):
return self.timer()
class DisplayManager:
def __init__(self, grid_size, window_size):
pygame.init()
pygame.font.init()
self.display = pygame.display.set_mode(window_size, pygame.HWSURFACE | pygame.DOUBLEBUF)
self.grid_size = grid_size
self.window_size = window_size
self.sensor_list = []
def get_window_size(self):
return [int(self.window_size[0]), int(self.window_size[1])]
def get_display_size(self):
return [int(self.window_size[0]/self.grid_size[1]), int(self.window_size[1]/self.grid_size[0])]
def get_display_offset(self, gridPos):
dis_size = self.get_display_size()
return [int(gridPos[1] * dis_size[0]), int(gridPos[0] * dis_size[1])]
def add_sensor(self, sensor):
self.sensor_list.append(sensor)
def get_sensor_list(self):
return self.sensor_list
def render(self):
if not self.render_enabled():
return
for s in self.sensor_list:
s.render()
pygame.display.flip()
def destroy(self):
for s in self.sensor_list:
s.destroy()
def render_enabled(self):
return self.display != None
class SensorManager:
def __init__(self, world, display_man, sensor_type, transform, attached, sensor_options, display_pos):
self.surface = None
self.world = world
self.display_man = display_man
self.display_pos = display_pos
self.sensor = self.init_sensor(sensor_type, transform, attached, sensor_options)
self.sensor_options = sensor_options
self.timer = CustomTimer()
self.time_processing = 0.0
self.tics_processing = 0
self.display_man.add_sensor(self)
def init_sensor(self, sensor_type, transform, attached, sensor_options):
if sensor_type == 'RGBCamera':
camera_bp = self.world.get_blueprint_library().find('sensor.camera.rgb')
disp_size = self.display_man.get_display_size()
camera_bp.set_attribute('image_size_x', str(disp_size[0]))
camera_bp.set_attribute('image_size_y', str(disp_size[1]))
for key in sensor_options:
camera_bp.set_attribute(key, sensor_options[key])
camera = self.world.spawn_actor(camera_bp, transform, attach_to=attached)
camera.listen(self.save_rgb_image)
return camera
elif sensor_type == 'LiDAR':
lidar_bp = self.world.get_blueprint_library().find('sensor.lidar.ray_cast')
lidar_bp.set_attribute('range', '100')
lidar_bp.set_attribute('dropoff_general_rate', lidar_bp.get_attribute('dropoff_general_rate').recommended_values[0])
lidar_bp.set_attribute('dropoff_intensity_limit', lidar_bp.get_attribute('dropoff_intensity_limit').recommended_values[0])
lidar_bp.set_attribute('dropoff_zero_intensity', lidar_bp.get_attribute('dropoff_zero_intensity').recommended_values[0])
for key in sensor_options:
lidar_bp.set_attribute(key, sensor_options[key])
lidar = self.world.spawn_actor(lidar_bp, transform, attach_to=attached)
lidar.listen(self.save_lidar_image)
return lidar
elif sensor_type == 'SemanticLiDAR':
lidar_bp = self.world.get_blueprint_library().find('sensor.lidar.ray_cast_semantic')
lidar_bp.set_attribute('range', '100')
for key in sensor_options:
lidar_bp.set_attribute(key, sensor_options[key])
lidar = self.world.spawn_actor(lidar_bp, transform, attach_to=attached)
lidar.listen(self.save_semanticlidar_image)
return lidar
elif sensor_type == "Radar":
radar_bp = self.world.get_blueprint_library().find('sensor.other.radar')
for key in sensor_options:
radar_bp.set_attribute(key, sensor_options[key])
radar = self.world.spawn_actor(radar_bp, transform, attach_to=attached)
radar.listen(self.save_radar_image)
return radar
else:
return None
def get_sensor(self):
return self.sensor
def save_rgb_image(self, image):
t_start = self.timer.time()
image.convert(carla.ColorConverter.Raw)
array = np.frombuffer(image.raw_data, dtype=np.dtype("uint8"))
array = np.reshape(array, (image.height, image.width, 4))
array = array[:, :, :3]
array = array[:, :, ::-1]
if self.display_man.render_enabled():
self.surface = pygame.surfarray.make_surface(array.swapaxes(0, 1))
t_end = self.timer.time()
self.time_processing += (t_end-t_start)
self.tics_processing += 1
def save_lidar_image(self, image):
t_start = self.timer.time()
disp_size = self.display_man.get_display_size()
lidar_range = 2.0*float(self.sensor_options['range'])
points = np.frombuffer(image.raw_data, dtype=np.dtype('f4'))
points = np.reshape(points, (int(points.shape[0] / 4), 4))
lidar_data = np.array(points[:, :2])
lidar_data *= min(disp_size) / lidar_range
lidar_data += (0.5 * disp_size[0], 0.5 * disp_size[1])
lidar_data = np.fabs(lidar_data) # pylint: disable=E1111
lidar_data = lidar_data.astype(np.int32)
lidar_data = np.reshape(lidar_data, (-1, 2))
lidar_img_size = (disp_size[0], disp_size[1], 3)
lidar_img = np.zeros((lidar_img_size), dtype=np.uint8)
lidar_img[tuple(lidar_data.T)] = (255, 255, 255)
if self.display_man.render_enabled():
self.surface = pygame.surfarray.make_surface(lidar_img)
t_end = self.timer.time()
self.time_processing += (t_end-t_start)
self.tics_processing += 1
def save_semanticlidar_image(self, image):
t_start = self.timer.time()
disp_size = self.display_man.get_display_size()
lidar_range = 2.0*float(self.sensor_options['range'])
points = np.frombuffer(image.raw_data, dtype=np.dtype('f4'))
points = np.reshape(points, (int(points.shape[0] / 6), 6))
lidar_data = np.array(points[:, :2])
lidar_data *= min(disp_size) / lidar_range
lidar_data += (0.5 * disp_size[0], 0.5 * disp_size[1])
lidar_data = np.fabs(lidar_data) # pylint: disable=E1111
lidar_data = lidar_data.astype(np.int32)
lidar_data = np.reshape(lidar_data, (-1, 2))
lidar_img_size = (disp_size[0], disp_size[1], 3)
lidar_img = np.zeros((lidar_img_size), dtype=np.uint8)
lidar_img[tuple(lidar_data.T)] = (255, 255, 255)
if self.display_man.render_enabled():
self.surface = pygame.surfarray.make_surface(lidar_img)
t_end = self.timer.time()
self.time_processing += (t_end-t_start)
self.tics_processing += 1
def save_radar_image(self, radar_data):
t_start = self.timer.time()
points = np.frombuffer(radar_data.raw_data, dtype=np.dtype('f4'))
points = np.reshape(points, (len(radar_data), 4))
t_end = self.timer.time()
self.time_processing += (t_end-t_start)
self.tics_processing += 1
def render(self):
if self.surface is not None:
offset = self.display_man.get_display_offset(self.display_pos)
self.display_man.display.blit(self.surface, offset)
def destroy(self):
self.sensor.destroy()
def run_simulation(args, client):
"""This function performed one test run using the args parameters
and connecting to the carla client passed.
"""
display_manager = None
vehicle = None
vehicle_list = []
timer = CustomTimer()
try:
# Getting the world and
world = client.get_world()
original_settings = world.get_settings()
if args.sync:
traffic_manager = client.get_trafficmanager(8000)
settings = world.get_settings()
traffic_manager.set_synchronous_mode(True)
settings.synchronous_mode = True
settings.fixed_delta_seconds = 0.05
world.apply_settings(settings)
# Instanciating the vehicle to which we attached the sensors
bp = world.get_blueprint_library().filter('charger_2020')[0]
vehicle = world.spawn_actor(bp, random.choice(world.get_map().get_spawn_points()))
vehicle_list.append(vehicle)
vehicle.set_autopilot(True)
# Display Manager organize all the sensors an its display in a window
# If can easily configure the grid and the total window size
display_manager = DisplayManager(grid_size=[2, 3], window_size=[args.width, args.height])
# Then, SensorManager can be used to spawn RGBCamera, LiDARs and SemanticLiDARs as needed
# and assign each of them to a grid position,
SensorManager(world, display_manager, 'RGBCamera', carla.Transform(carla.Location(x=0, z=2.4), carla.Rotation(yaw=-90)),
vehicle, {}, display_pos=[0, 0])
SensorManager(world, display_manager, 'RGBCamera', carla.Transform(carla.Location(x=0, z=2.4), carla.Rotation(yaw=+00)),
vehicle, {}, display_pos=[0, 1])
SensorManager(world, display_manager, 'RGBCamera', carla.Transform(carla.Location(x=0, z=2.4), carla.Rotation(yaw=+90)),
vehicle, {}, display_pos=[0, 2])
SensorManager(world, display_manager, 'RGBCamera', carla.Transform(carla.Location(x=0, z=2.4), carla.Rotation(yaw=180)),
vehicle, {}, display_pos=[1, 1])
SensorManager(world, display_manager, 'LiDAR', carla.Transform(carla.Location(x=0, z=2.4)),
vehicle, {'channels' : '64', 'range' : '100', 'points_per_second': '250000', 'rotation_frequency': '20'}, display_pos=[1, 0])
SensorManager(world, display_manager, 'SemanticLiDAR', carla.Transform(carla.Location(x=0, z=2.4)),
vehicle, {'channels' : '64', 'range' : '100', 'points_per_second': '100000', 'rotation_frequency': '20'}, display_pos=[1, 2])
#Simulation loop
call_exit = False
time_init_sim = timer.time()
while True:
# Carla Tick
if args.sync:
world.tick()
else:
world.wait_for_tick()
# Render received data
display_manager.render()
for event in pygame.event.get():
if event.type == pygame.QUIT:
call_exit = True
elif event.type == pygame.KEYDOWN:
if event.key == K_ESCAPE or event.key == K_q:
call_exit = True
break
if call_exit:
break
finally:
if display_manager:
display_manager.destroy()
client.apply_batch([carla.command.DestroyActor(x) for x in vehicle_list])
world.apply_settings(original_settings)
def main():
argparser = argparse.ArgumentParser(
description='CARLA Sensor tutorial')
argparser.add_argument(
'--host',
metavar='H',
default='127.0.0.1',
help='IP of the host server (default: 127.0.0.1)')
argparser.add_argument(
'-p', '--port',
metavar='P',
default=2000,
type=int,
help='TCP port to listen to (default: 2000)')
argparser.add_argument(
'--sync',
action='store_true',
help='Synchronous mode execution')
argparser.add_argument(
'--async',
dest='sync',
action='store_false',
help='Asynchronous mode execution')
argparser.set_defaults(sync=True)
argparser.add_argument(
'--res',
metavar='WIDTHxHEIGHT',
default='1280x720',
help='window resolution (default: 1280x720)')
args = argparser.parse_args()
args.width, args.height = [int(x) for x in args.res.split('x')]
try:
client = carla.Client(args.host, args.port)
client.set_timeout(5.0)
run_simulation(args, client)
except KeyboardInterrupt:
print('\nCancelled by user. Bye!')
if __name__ == '__main__':
main()