carla学习笔记(二)_world.wait_for_tick

主要是学习自带的example中的spawn_npc.py的源码.

发现前一天学的很多代码都可以在这里找到原型,觉得还是要先把example代码学习完,在读一下doc才能更深入的了解carla.

#!/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 <https://opensource.org/licenses/MIT>.
 
"""Spawn NPCs into the simulation"""
 
import glob
"""
glob()函数是python的glob模块中的方法,是种文件通配符,glob()函数可以查找符合自己要求的文件，
glob模块中的函数,有三个:glob.glob(pathname,*,recursive=False)
"""
import os
import sys
import time
 
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
"""
os.name该变量返回当前操作系统的类型,当前只注册了3个值：分别是posix , nt , java， 对应linux/windows/java虚拟机
"""
 
import carla
 
from carla import VehicleLightState as vls
 
import argparse
# argparse 是一种类似于python字典的数据结构
# 我们可以用args.参数名来获取参数
import logging
from numpy import random
 
def main():
    argparser = argparse.ArgumentParser(
        description=__doc__)
    argparser.add_argument(
        '--host',
        # 主机127.0.0.1
        metavar='H',
        default='127.0.0.1',
        help='IP of the host server (default: 127.0.0.1)')
    argparser.add_argument(
        '-p', '--port',
        # 端口2000
        metavar='P',
        default=2000,
        type=int,
        help='TCP port to listen to (default: 2000)')
    argparser.add_argument(
        '-n', '--number-of-vehicles',
        # 默认车辆个数
        metavar='N',
        default=10,
        type=int,
        help='number of vehicles (default: 10)')
    argparser.add_argument(
        '-w', '--number-of-walkers',
        # 默认行人数
        metavar='W',
        default=50,
        type=int,
        help='number of walkers (default: 50)')
    argparser.add_argument(
        '--safe',
        # 大概是安全系数?
        action='store_true',
        help='avoid spawning vehicles prone to accidents')
    argparser.add_argument(
        '--filterv',
        # 选择车辆的某种参数
        metavar='PATTERN',
        default='vehicle.*',
        help='vehicles filter (default: "vehicle.*")')
    argparser.add_argument(
        '--filterw',
        # 选择行人的某种参数
        metavar='PATTERN',
        default='walker.pedestrian.*',
        help='pedestrians filter (default: "walker.pedestrian.*")')
    argparser.add_argument(
        '--tm-port',
        # traffic_manager的参数
        metavar='P',
        default=8000,
        type=int,
        help='port to communicate with TM (default: 8000)')
    argparser.add_argument(
        '--sync',
        # 同步模式
        action='store_true',
        help='Synchronous mode execution')
    argparser.add_argument(
        '--hybrid',
        # 异步模式
        action='store_true',
        help='Enanble')
    argparser.add_argument(
        '-s', '--seed',
        # 生成设备的种子??
        metavar='S',
        type=int,
        help='Random device seed')
    argparser.add_argument(
        '--car-lights-on',
        # 车灯开启
        action='store_true',
        default=False,
        help='Enanble car lights')
    # 封装到了args里面
    args = argparser.parse_args()
 
    # 日志,先可以不用过多了解
    logging.basicConfig(format='%(levelname)s: %(message)s', level=logging.INFO)
 
    # 生成的车辆list
    vehicles_list = []
    # 生成的行人的list
    walkers_list = []
    # 所有的ID
    all_id = []
    # 获取客户端
    client = carla.Client(args.host, args.port)
    # 设定时序?
    client.set_timeout(10.0)
    # 现将同步模式关闭
    synchronous_master = False
    # 随机数种子,返回时间戳?
    random.seed(args.seed if args.seed is not None else int(time.time()))
 
    try:
        # 获取仿真世界
        world = client.get_world()
        # 设置tm相关的参数,要管理大量的车辆必须使用tm
        # 先设置tm的端口
        traffic_manager = client.get_trafficmanager(args.tm_port)
        # 设置tm的安全距离为1米
        traffic_manager.set_global_distance_to_leading_vehicle(1.0)
        # 将物理引擎打开
        if args.hybrid:
            traffic_manager.set_hybrid_physics_mode(True)
            # 生成随机数相关?
        if args.seed is not None:
            traffic_manager.set_random_device_seed(args.seed)
 
        # 把同步模式打开
        if args.sync:
            settings = world.get_settings()
            traffic_manager.set_synchronous_mode(True)
            if not settings.synchronous_mode:
                synchronous_master = True
                settings.synchronous_mode = True
                # 设置0.05秒一帧?
                settings.fixed_delta_seconds = 0.05
                # 将相关的设置应用到仿真世界中去
                world.apply_settings(settings)
            else:
                synchronous_master = False
 
        # 获取仿真世界里面的蓝图,主要用filter获取所有的车辆
        blueprints = world.get_blueprint_library().filter(args.filterv)
        # 获取仿真世界里面的蓝图,主要用filter获取所有的行人模型
        blueprintsWalkers = world.get_blueprint_library().filter(args.filterw)
 
        # 保证安全,避免产生的车辆容易发生故障?
        if args.safe:
            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('cybertruck')]
            blueprints = [x for x in blueprints if not x.id.endswith('t2')]
 
        # 将车辆以id来排序
        blueprints = sorted(blueprints, key=lambda bp: bp.id)
 
        # 获取world中可以生成车辆的点
        spawn_points = world.get_map().get_spawn_points()
        # 生成点的个数
        number_of_spawn_points = len(spawn_points)
 
        # 如果车辆的个数少于点的个数,那么打乱点的顺序,否则就会报错,先忽略报错
        if args.number_of_vehicles < number_of_spawn_points:
            random.shuffle(spawn_points)
        elif args.number_of_vehicles > number_of_spawn_points:
            msg = 'requested %d vehicles, but could only find %d spawn points'
            logging.warning(msg, args.number_of_vehicles, number_of_spawn_points)
            args.number_of_vehicles = number_of_spawn_points
 
        # 这部分主要是carla中的命令,可能是为了方便?
        # @todo cannot import these directly.
        # 控制所有生成actor
        SpawnActor = carla.command.SpawnActor
        # 控制车辆的自动驾驶开关
        SetAutopilot = carla.command.SetAutopilot
        # 控制车的灯
        SetVehicleLightState = carla.command.SetVehicleLightState
        # 控制某种属性,默认值是0
        FutureActor = carla.command.FutureActor
 
        # --------------
        # Spawn vehicles
        # --------------
        batch = []
        # 给spawn_points加上序号0,1,2,3...
        for n, transform in enumerate(spawn_points):
            # 若n大于要求的数量就报错
            if n >= args.number_of_vehicles:
                break
            # 随机选择一辆车的蓝图,下面全是随机选择并设置车的相关属性
            blueprint = random.choice(blueprints)
            if blueprint.has_attribute('color'):
                color = random.choice(blueprint.get_attribute('color').recommended_values)
                blueprint.set_attribute('color', color)
            if blueprint.has_attribute('driver_id'):
                driver_id = random.choice(blueprint.get_attribute('driver_id').recommended_values)
                blueprint.set_attribute('driver_id', driver_id)
            blueprint.set_attribute('role_name', 'autopilot')
 
            # 设置车灯的一些属性
            # prepare the light state of the cars to spawn
            light_state = vls.NONE
            if args.car_lights_on:
                light_state = vls.Position | vls.LowBeam | vls.LowBeam
 
            # 将随机好的车辆生成并设置驾驶模式和车灯开启相关
            # spawn the cars and set their autopilot and light state all together
            batch.append(SpawnActor(blueprint, transform)
                .then(SetAutopilot(FutureActor, True, traffic_manager.get_port()))
                .then(SetVehicleLightState(FutureActor, light_state)))
 
        # 生成同步模式相关
        for response in client.apply_batch_sync(batch, synchronous_master):
            if response.error:
                logging.error(response.error)
            else:
                vehicles_list.append(response.actor_id)
 
        # -------------
        # Spawn Walkers
        # -------------
        # some settings
        percentagePedestriansRunning = 0.0      # how many pedestrians will run
        percentagePedestriansCrossing = 0.0     # how many pedestrians will walk through the road
        # 1. take all the random locations to spawn
        # 主要是将carla的transform的数据格式放入spawn_point中
        spawn_points = []
        for i in range(args.number_of_walkers):
            spawn_point = carla.Transform()
            # 只能针对walks使用,在sidewalk上使用
            loc = world.get_random_location_from_navigation()
            if (loc != None):
                spawn_point.location = loc
                spawn_points.append(spawn_point)
        # 2. we spawn the walker object
        # 设置行人的速度
        batch = []
        walker_speed = []
        for spawn_point in spawn_points:
            walker_bp = random.choice(blueprintsWalkers)
            # set as not invincible
            # 设置无敌?
            if walker_bp.has_attribute('is_invincible'):
                walker_bp.set_attribute('is_invincible', 'false')
            # set the max speed
            if walker_bp.has_attribute('speed'):
                if (random.random() > percentagePedestriansRunning):
                    # walking
                    walker_speed.append(walker_bp.get_attribute('speed').recommended_values[1])
                else:
                    # running
                    walker_speed.append(walker_bp.get_attribute('speed').recommended_values[2])
            else:
                print("Walker has no speed")
                walker_speed.append(0.0)
            batch.append(SpawnActor(walker_bp, spawn_point))
        results = client.apply_batch_sync(batch, True)
        walker_speed2 = []
        for i in range(len(results)):
            if results[i].error:
                logging.error(results[i].error)
            else:
                walkers_list.append({"id": results[i].actor_id})
                walker_speed2.append(walker_speed[i])
        walker_speed = walker_speed2
        # 3. we spawn the walker controller
        # 设置一个行人的控制器
        batch = []
        # 在蓝图库中找到行人ai控制器
        walker_controller_bp = world.get_blueprint_library().find('controller.ai.walker')
        for i in range(len(walkers_list)):
            batch.append(SpawnActor(walker_controller_bp, carla.Transform(), walkers_list[i]["id"]))
        results = client.apply_batch_sync(batch, True)
        for i in range(len(results)):
            if results[i].error:
                logging.error(results[i].error)
            else:
                walkers_list[i]["con"] = results[i].actor_id
        # 4. we put altogether the walkers and controllers id to get the objects from their id
        for i in range(len(walkers_list)):
            all_id.append(walkers_list[i]["con"])
            all_id.append(walkers_list[i]["id"])
        all_actors = world.get_actors(all_id)
 
        # wait for a tick to ensure client receives the last transform of the walkers we have just created
        if not args.sync or not synchronous_master:
            world.wait_for_tick()
        else:
            world.tick()
 
        # 5. initialize each controller and set target to walk to (list is [controler, actor, controller, actor ...])
        # set how many pedestrians can cross the road
        # 设置行人的控制相关
        world.set_pedestrians_cross_factor(percentagePedestriansCrossing)
        for i in range(0, len(all_id), 2):
            # start walker
            all_actors[i].start()
            # set walk to random point
            all_actors[i].go_to_location(world.get_random_location_from_navigation())
            # max speed
            all_actors[i].set_max_speed(float(walker_speed[int(i/2)]))
 
        print('spawned %d vehicles and %d walkers, press Ctrl+C to exit.' % (len(vehicles_list), len(walkers_list)))
 
        # example of how to use parameters
        traffic_manager.global_percentage_speed_difference(30.0)
 
        while True:
            if args.sync and synchronous_master:
                world.tick()
            else:
                world.wait_for_tick()
 
    finally:
        # 主要是恢复初始化
 
        if args.sync and synchronous_master:
            settings = world.get_settings()
            settings.synchronous_mode = False
            settings.fixed_delta_seconds = None
            world.apply_settings(settings)
 
        print('\ndestroying %d vehicles' % len(vehicles_list))
        client.apply_batch([carla.command.DestroyActor(x) for x in vehicles_list])
 
        # stop walker controllers (list is [controller, actor, controller, actor ...])
        for i in range(0, len(all_id), 2):
            all_actors[i].stop()
 
        print('\ndestroying %d walkers' % len(walkers_list))
        client.apply_batch([carla.command.DestroyActor(x) for x in all_id])
 
        time.sleep(0.5)
 
if __name__ == '__main__':
 
    try:
        main()
    except KeyboardInterrupt:
        pass
    finally:
        print('\ndone.')

在学习的过程中,想到了昨天调用cv2的包,突发奇想,想把spectator的视角用imshow独立的窗口展示出来,但自己上手后没有成功,可能是imshow的格式属性不对,也可能是别的问题.需要在后续的学习中可以实现.