#!/usr/bin/env python # Copyright (c) 2019 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 . 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 random import time def main(): actor_list = [] # In this tutorial script, we are going to add a vehicle to the simulation # and let it drive in autopilot. We will also create a camera attached to # that vehicle, and save all the images generated by the camera to disk. try: # First of all, we need to create the client that will send the requests # to the simulator. Here we'll assume the simulator is accepting # requests in the localhost at port 2000. client = carla.Client('localhost', 2000) client.set_timeout(2.0) # Once we have a client we can retrieve the world that is currently # running. world = client.get_world() # The world contains the list blueprints that we can use for adding new # actors into the simulation. blueprint_library = world.get_blueprint_library() # Now let's filter all the blueprints of type 'vehicle' and choose one # at random. bp = random.choice(blueprint_library.filter('vehicle')) # A blueprint contains the list of attributes that define a vehicle's # instance, we can read them and modify some of them. For instance, # let's randomize its color. if bp.has_attribute('color'): color = random.choice(bp.get_attribute('color').recommended_values) bp.set_attribute('color', color) # Now we need to give an initial transform to the vehicle. We choose a # random transform from the list of recommended spawn points of the map. transform = random.choice(world.get_map().get_spawn_points()) # So let's tell the world to spawn the vehicle. vehicle = world.spawn_actor(bp, transform) # It is important to note that the actors we create won't be destroyed # unless we call their "destroy" function. If we fail to call "destroy" # they will stay in the simulation even after we quit the Python script. # For that reason, we are storing all the actors we create so we can # destroy them afterwards. actor_list.append(vehicle) print('created %s' % vehicle.type_id) # Let's put the vehicle to drive around. vehicle.set_autopilot(True) # Let's add now a "depth" camera attached to the vehicle. Note that the # transform we give here is now relative to the vehicle. camera_bp = blueprint_library.find('sensor.camera.depth') camera_transform = carla.Transform(carla.Location(x=1.5, z=2.4)) camera = world.spawn_actor(camera_bp, camera_transform, attach_to=vehicle) actor_list.append(camera) print('created %s' % camera.type_id) # Now we register the function that will be called each time the sensor # receives an image. In this example we are saving the image to disk # converting the pixels to gray-scale. cc = carla.ColorConverter.LogarithmicDepth camera.listen(lambda image: image.save_to_disk('_out/%06d.png' % image.frame, cc)) # Oh wait, I don't like the location we gave to the vehicle, I'm going # to move it a bit forward. location = vehicle.get_location() location.x += 40 vehicle.set_location(location) print('moved vehicle to %s' % location) # But the city now is probably quite empty, let's add a few more # vehicles. transform.location += carla.Location(x=40, y=-3.2) transform.rotation.yaw = -180.0 for _ in range(0, 10): transform.location.x += 8.0 bp = random.choice(blueprint_library.filter('vehicle')) # This time we are using try_spawn_actor. If the spot is already # occupied by another object, the function will return None. npc = world.try_spawn_actor(bp, transform) if npc is not None: actor_list.append(npc) npc.set_autopilot() print('created %s' % npc.type_id) time.sleep(5) finally: print('destroying actors') camera.destroy() client.apply_batch([carla.command.DestroyActor(x) for x in actor_list]) print('done.') if __name__ == '__main__': main()