mirror of
https://github.com/gryf/coach.git
synced 2025-12-17 11:10:20 +01:00
pre-release 0.10.0
This commit is contained in:
Gal Novik
357
rl_coach/environments/carla_environment.py
Normal file
357
rl_coach/environments/carla_environment.py
Normal file
@@ -0,0 +1,357 @@
|
||||
import random
|
||||
import sys
|
||||
from os import path, environ
|
||||
|
||||
from rl_coach.filters.observation.observation_to_uint8_filter import ObservationToUInt8Filter
|
||||
|
||||
from rl_coach.filters.observation.observation_rgb_to_y_filter import ObservationRGBToYFilter
|
||||
|
||||
try:
|
||||
if 'CARLA_ROOT' in environ:
|
||||
sys.path.append(path.join(environ.get('CARLA_ROOT'), 'PythonClient'))
|
||||
from carla.client import CarlaClient
|
||||
from carla.settings import CarlaSettings
|
||||
from carla.tcp import TCPConnectionError
|
||||
from carla.sensor import Camera
|
||||
from carla.client import VehicleControl
|
||||
except ImportError:
|
||||
from rl_coach.logger import failed_imports
|
||||
failed_imports.append("CARLA")
|
||||
|
||||
import logging
|
||||
import subprocess
|
||||
from rl_coach.environments.environment import Environment, EnvironmentParameters, LevelSelection
|
||||
from rl_coach.spaces import BoxActionSpace, ImageObservationSpace, StateSpace, \
|
||||
VectorObservationSpace
|
||||
from rl_coach.utils import get_open_port, force_list
|
||||
from enum import Enum
|
||||
import os
|
||||
import signal
|
||||
from typing import List, Union
|
||||
from rl_coach.base_parameters import VisualizationParameters
|
||||
from rl_coach.filters.filter import InputFilter, NoOutputFilter
|
||||
from rl_coach.filters.observation.observation_rescale_to_size_filter import ObservationRescaleToSizeFilter
|
||||
from rl_coach.filters.observation.observation_stacking_filter import ObservationStackingFilter
|
||||
import numpy as np
|
||||
|
||||
|
||||
# enum of the available levels and their path
|
||||
class CarlaLevel(Enum):
|
||||
TOWN1 = "/Game/Maps/Town01"
|
||||
TOWN2 = "/Game/Maps/Town02"
|
||||
|
||||
key_map = {
|
||||
'BRAKE': (274,), # down arrow
|
||||
'GAS': (273,), # up arrow
|
||||
'TURN_LEFT': (276,), # left arrow
|
||||
'TURN_RIGHT': (275,), # right arrow
|
||||
'GAS_AND_TURN_LEFT': (273, 276),
|
||||
'GAS_AND_TURN_RIGHT': (273, 275),
|
||||
'BRAKE_AND_TURN_LEFT': (274, 276),
|
||||
'BRAKE_AND_TURN_RIGHT': (274, 275),
|
||||
}
|
||||
|
||||
CarlaInputFilter = InputFilter(is_a_reference_filter=True)
|
||||
CarlaInputFilter.add_observation_filter('forward_camera', 'rescaling',
|
||||
ObservationRescaleToSizeFilter(ImageObservationSpace(np.array([128, 180, 3]),
|
||||
high=255)))
|
||||
CarlaInputFilter.add_observation_filter('forward_camera', 'to_grayscale', ObservationRGBToYFilter())
|
||||
CarlaInputFilter.add_observation_filter('forward_camera', 'to_uint8', ObservationToUInt8Filter(0, 255))
|
||||
CarlaInputFilter.add_observation_filter('forward_camera', 'stacking', ObservationStackingFilter(4))
|
||||
|
||||
CarlaOutputFilter = NoOutputFilter()
|
||||
|
||||
|
||||
class CameraTypes(Enum):
|
||||
FRONT = "forward_camera"
|
||||
LEFT = "left_camera"
|
||||
RIGHT = "right_camera"
|
||||
SEGMENTATION = "segmentation"
|
||||
DEPTH = "depth"
|
||||
LIDAR = "lidar"
|
||||
|
||||
|
||||
class CarlaEnvironmentParameters(EnvironmentParameters):
|
||||
class Quality(Enum):
|
||||
LOW = "Low"
|
||||
EPIC = "Epic"
|
||||
|
||||
def __init__(self):
|
||||
super().__init__()
|
||||
self.frame_skip = 3 # the frame skip affects the fps of the server directly. fps = 30 / frameskip
|
||||
self.server_height = 512
|
||||
self.server_width = 720
|
||||
self.camera_height = 128
|
||||
self.camera_width = 180
|
||||
self.config = None #'environments/CarlaSettings.ini' # TODO: remove the config to prevent confusion
|
||||
self.level = 'town1'
|
||||
self.quality = self.Quality.LOW
|
||||
self.cameras = [CameraTypes.FRONT]
|
||||
self.weather_id = [1]
|
||||
self.verbose = True
|
||||
self.episode_max_time = 100000 # miliseconds for each episode
|
||||
self.allow_braking = False
|
||||
self.default_input_filter = CarlaInputFilter
|
||||
self.default_output_filter = CarlaOutputFilter
|
||||
|
||||
@property
|
||||
def path(self):
|
||||
return 'rl_coach.environments.carla_environment:CarlaEnvironment'
|
||||
|
||||
|
||||
class CarlaEnvironment(Environment):
|
||||
def __init__(self, level: LevelSelection,
|
||||
seed: int, frame_skip: int, human_control: bool, custom_reward_threshold: Union[int, float],
|
||||
visualization_parameters: VisualizationParameters,
|
||||
server_height: int, server_width: int, camera_height: int, camera_width: int,
|
||||
verbose: bool, config: str, episode_max_time: int,
|
||||
allow_braking: bool, quality: CarlaEnvironmentParameters.Quality,
|
||||
cameras: List[CameraTypes], weather_id: List[int], **kwargs):
|
||||
super().__init__(level, seed, frame_skip, human_control, custom_reward_threshold, visualization_parameters)
|
||||
|
||||
# server configuration
|
||||
self.server_height = server_height
|
||||
self.server_width = server_width
|
||||
self.port = get_open_port()
|
||||
self.host = 'localhost'
|
||||
self.map = self.env_id
|
||||
|
||||
# client configuration
|
||||
self.verbose = verbose
|
||||
self.quality = quality
|
||||
self.cameras = cameras
|
||||
self.weather_id = weather_id
|
||||
self.episode_max_time = episode_max_time
|
||||
self.allow_braking = allow_braking
|
||||
self.camera_width = camera_width
|
||||
self.camera_height = camera_height
|
||||
|
||||
# state space
|
||||
self.state_space = StateSpace({
|
||||
"measurements": VectorObservationSpace(4, measurements_names=["forward_speed", "x", "y", "z"])
|
||||
})
|
||||
for camera in self.cameras:
|
||||
self.state_space[camera.value] = ImageObservationSpace(
|
||||
shape=np.array([self.camera_height, self.camera_width, 3]),
|
||||
high=255)
|
||||
|
||||
# setup server settings
|
||||
self.config = config
|
||||
if self.config:
|
||||
# load settings from file
|
||||
with open(self.config, 'r') as fp:
|
||||
self.settings = fp.read()
|
||||
else:
|
||||
# hard coded settings
|
||||
self.settings = CarlaSettings()
|
||||
self.settings.set(
|
||||
SynchronousMode=True,
|
||||
SendNonPlayerAgentsInfo=False,
|
||||
NumberOfVehicles=15,
|
||||
NumberOfPedestrians=30,
|
||||
WeatherId=random.choice(force_list(self.weather_id)),
|
||||
QualityLevel=self.quality.value)
|
||||
self.settings.randomize_seeds()
|
||||
|
||||
self.settings = self._add_cameras(self.settings, self.cameras, self.camera_width, self.camera_height)
|
||||
|
||||
# open the server
|
||||
self.server = self._open_server()
|
||||
|
||||
logging.disable(40)
|
||||
|
||||
# open the client
|
||||
self.game = CarlaClient(self.host, self.port, timeout=99999999)
|
||||
self.game.connect()
|
||||
scene = self.game.load_settings(self.settings)
|
||||
|
||||
# get available start positions
|
||||
positions = scene.player_start_spots
|
||||
self.num_pos = len(positions)
|
||||
self.iterator_start_positions = 0
|
||||
|
||||
# action space
|
||||
self.action_space = BoxActionSpace(shape=2, low=np.array([-1, -1]), high=np.array([1, 1]))
|
||||
|
||||
# human control
|
||||
if self.human_control:
|
||||
# convert continuous action space to discrete
|
||||
self.steering_strength = 0.5
|
||||
self.gas_strength = 1.0
|
||||
self.brake_strength = 0.5
|
||||
self.action_space = PartialDiscreteActionSpaceMap(
|
||||
target_actions=[[0., 0.],
|
||||
[0., -self.steering_strength],
|
||||
[0., self.steering_strength],
|
||||
[self.gas_strength, 0.],
|
||||
[-self.brake_strength, 0],
|
||||
[self.gas_strength, -self.steering_strength],
|
||||
[self.gas_strength, self.steering_strength],
|
||||
[self.brake_strength, -self.steering_strength],
|
||||
[self.brake_strength, self.steering_strength]],
|
||||
target_action_space=self.action_space,
|
||||
descriptions=['NO-OP', 'TURN_LEFT', 'TURN_RIGHT', 'GAS', 'BRAKE',
|
||||
'GAS_AND_TURN_LEFT', 'GAS_AND_TURN_RIGHT',
|
||||
'BRAKE_AND_TURN_LEFT', 'BRAKE_AND_TURN_RIGHT']
|
||||
)
|
||||
|
||||
# map keyboard keys to actions
|
||||
for idx, action in enumerate(self.action_space.descriptions):
|
||||
for key in key_map.keys():
|
||||
if action == key:
|
||||
self.key_to_action[key_map[key]] = idx
|
||||
|
||||
self.num_speedup_steps = 30
|
||||
|
||||
# measurements
|
||||
self.autopilot = None
|
||||
|
||||
# env initialization
|
||||
self.reset_internal_state(True)
|
||||
|
||||
# render
|
||||
if self.is_rendered:
|
||||
image = self.get_rendered_image()
|
||||
self.renderer.create_screen(image.shape[1], image.shape[0])
|
||||
|
||||
def _add_cameras(self, settings, cameras, camera_width, camera_height):
|
||||
# add a front facing camera
|
||||
if CameraTypes.FRONT in cameras:
|
||||
camera = Camera(CameraTypes.FRONT.value)
|
||||
camera.set_image_size(camera_width, camera_height)
|
||||
camera.set_position(0.2, 0, 1.3)
|
||||
camera.set_rotation(8, 0, 0)
|
||||
settings.add_sensor(camera)
|
||||
|
||||
# add a left facing camera
|
||||
if CameraTypes.LEFT in cameras:
|
||||
camera = Camera(CameraTypes.LEFT.value)
|
||||
camera.set_image_size(camera_width, camera_height)
|
||||
camera.set_position(0.2, 0, 1.3)
|
||||
camera.set_rotation(8, -30, 0)
|
||||
settings.add_sensor(camera)
|
||||
|
||||
# add a right facing camera
|
||||
if CameraTypes.RIGHT in cameras:
|
||||
camera = Camera(CameraTypes.RIGHT.value)
|
||||
camera.set_image_size(camera_width, camera_height)
|
||||
camera.set_position(0.2, 0, 1.3)
|
||||
camera.set_rotation(8, 30, 0)
|
||||
settings.add_sensor(camera)
|
||||
|
||||
# add a front facing depth camera
|
||||
if CameraTypes.DEPTH in cameras:
|
||||
camera = Camera(CameraTypes.DEPTH.value)
|
||||
camera.set_image_size(camera_width, camera_height)
|
||||
camera.set_position(0.2, 0, 1.3)
|
||||
camera.set_rotation(8, 30, 0)
|
||||
camera.PostProcessing = 'Depth'
|
||||
settings.add_sensor(camera)
|
||||
|
||||
# add a front facing semantic segmentation camera
|
||||
if CameraTypes.SEGMENTATION in cameras:
|
||||
camera = Camera(CameraTypes.SEGMENTATION.value)
|
||||
camera.set_image_size(camera_width, camera_height)
|
||||
camera.set_position(0.2, 0, 1.3)
|
||||
camera.set_rotation(8, 30, 0)
|
||||
camera.PostProcessing = 'SemanticSegmentation'
|
||||
settings.add_sensor(camera)
|
||||
|
||||
return settings
|
||||
|
||||
def _open_server(self):
|
||||
# TODO: get experiment path
|
||||
log_path = path.join('./logs/', "CARLA_LOG_{}.txt".format(self.port))
|
||||
with open(log_path, "wb") as out:
|
||||
cmd = [path.join(environ.get('CARLA_ROOT'), 'CarlaUE4.sh'), self.map,
|
||||
"-benchmark", "-carla-server", "-fps={}".format(30 / self.frame_skip),
|
||||
"-world-port={}".format(self.port),
|
||||
"-windowed -ResX={} -ResY={}".format(self.server_width, self.server_height),
|
||||
"-carla-no-hud"]
|
||||
|
||||
if self.config:
|
||||
cmd.append("-carla-settings={}".format(self.config))
|
||||
p = subprocess.Popen(cmd, stdout=out, stderr=out)
|
||||
|
||||
return p
|
||||
|
||||
def _close_server(self):
|
||||
os.killpg(os.getpgid(self.server.pid), signal.SIGKILL)
|
||||
|
||||
def _update_state(self):
|
||||
# get measurements and observations
|
||||
measurements = []
|
||||
while type(measurements) == list:
|
||||
measurements, sensor_data = self.game.read_data()
|
||||
self.state = {}
|
||||
|
||||
for camera in self.cameras:
|
||||
self.state[camera.value] = sensor_data[camera.value].data
|
||||
|
||||
self.location = [measurements.player_measurements.transform.location.x,
|
||||
measurements.player_measurements.transform.location.y,
|
||||
measurements.player_measurements.transform.location.z]
|
||||
|
||||
is_collision = measurements.player_measurements.collision_vehicles != 0 \
|
||||
or measurements.player_measurements.collision_pedestrians != 0 \
|
||||
or measurements.player_measurements.collision_other != 0
|
||||
|
||||
speed_reward = measurements.player_measurements.forward_speed - 1
|
||||
if speed_reward > 30.:
|
||||
speed_reward = 30.
|
||||
self.reward = speed_reward \
|
||||
- (measurements.player_measurements.intersection_otherlane * 5) \
|
||||
- (measurements.player_measurements.intersection_offroad * 5) \
|
||||
- is_collision * 100 \
|
||||
- np.abs(self.control.steer) * 10
|
||||
|
||||
# update measurements
|
||||
self.measurements = [measurements.player_measurements.forward_speed] + self.location
|
||||
self.autopilot = measurements.player_measurements.autopilot_control
|
||||
|
||||
# action_p = ['%.2f' % member for member in [self.control.throttle, self.control.steer]]
|
||||
# screen.success('REWARD: %.2f, ACTIONS: %s' % (self.reward, action_p))
|
||||
|
||||
if (measurements.game_timestamp >= self.episode_max_time) or is_collision:
|
||||
# screen.success('EPISODE IS DONE. GameTime: {}, Collision: {}'.format(str(measurements.game_timestamp),
|
||||
# str(is_collision)))
|
||||
self.done = True
|
||||
|
||||
self.state['measurements'] = self.measurements
|
||||
|
||||
def _take_action(self, action):
|
||||
self.control = VehicleControl()
|
||||
self.control.throttle = np.clip(action[0], 0, 1)
|
||||
self.control.steer = np.clip(action[1], -1, 1)
|
||||
self.control.brake = np.abs(np.clip(action[0], -1, 0))
|
||||
if not self.allow_braking:
|
||||
self.control.brake = 0
|
||||
self.control.hand_brake = False
|
||||
self.control.reverse = False
|
||||
|
||||
self.game.send_control(self.control)
|
||||
|
||||
def _restart_environment_episode(self, force_environment_reset=False):
|
||||
self.iterator_start_positions += 1
|
||||
if self.iterator_start_positions >= self.num_pos:
|
||||
self.iterator_start_positions = 0
|
||||
|
||||
try:
|
||||
self.game.start_episode(self.iterator_start_positions)
|
||||
except:
|
||||
self.game.connect()
|
||||
self.game.start_episode(self.iterator_start_positions)
|
||||
|
||||
# start the game with some initial speed
|
||||
for i in range(self.num_speedup_steps):
|
||||
self._take_action([1.0, 0])
|
||||
|
||||
def get_rendered_image(self) -> np.ndarray:
|
||||
"""
|
||||
Return a numpy array containing the image that will be rendered to the screen.
|
||||
This can be different from the observation. For example, mujoco's observation is a measurements vector.
|
||||
:return: numpy array containing the image that will be rendered to the screen
|
||||
"""
|
||||
image = [self.state[camera.value] for camera in self.cameras]
|
||||
image = np.vstack(image)
|
||||
return image
|
||||
Reference in New Issue
Block a user