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updated CARLA to allow the usage of predefined experiment suites

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itaicaspi-intel
2018-09-14 18:07:24 +03:00
parent e8a2b679d1
commit f8d3574b8c
3 changed files with 37 additions and 23 deletions
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48
rl_coach/environments/carla_environment.py
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@@ -153,15 +153,6 @@ class CarlaEnvironment(Environment):
self.camera_width = camera_width self.camera_width = camera_width
self.camera_height = camera_height 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 # setup server settings
self.experiment_suite = experiment_suite self.experiment_suite = experiment_suite
self.config = config self.config = config
@@ -195,17 +186,27 @@ class CarlaEnvironment(Environment):
self.game = CarlaClient(self.host, self.port, timeout=99999999) self.game = CarlaClient(self.host, self.port, timeout=99999999)
self.game.connect() self.game.connect()
if self.experiment_suite: if self.experiment_suite:
self.current_experiment = self.experiment_suite.get_experiments()[0] self.current_experiment_idx = 0
scene = self.game.load_settings(self.current_experiment.conditions) self.current_experiment = self.experiment_suite.get_experiments()[self.current_experiment_idx]
self.scene = self.game.load_settings(self.current_experiment.conditions)
else: else:
scene = self.game.load_settings(self.settings) self.scene = self.game.load_settings(self.settings)
# get available start positions # get available start positions
self.positions = scene.player_start_spots self.positions = self.scene.player_start_spots
self.num_positions = len(self.positions) self.num_positions = len(self.positions)
self.current_start_position_idx = 0 self.current_start_position_idx = 0
self.current_pose = 0 self.current_pose = 0
# state space
self.state_space = StateSpace({
"measurements": VectorObservationSpace(4, measurements_names=["forward_speed", "x", "y", "z"])
})
for camera in self.scene.sensors:
self.state_space[camera.name] = ImageObservationSpace(
shape=np.array([self.camera_height, self.camera_width, 3]),
high=255)
# action space # action space
self.action_space = BoxActionSpace(shape=2, low=np.array([-1, -1]), high=np.array([1, 1])) self.action_space = BoxActionSpace(shape=2, low=np.array([-1, -1]), high=np.array([1, 1]))
@@ -342,8 +343,8 @@ class CarlaEnvironment(Environment):
measurements, sensor_data = self.game.read_data() measurements, sensor_data = self.game.read_data()
self.state = {} self.state = {}
for camera in self.cameras: for camera in self.scene.sensors:
self.state[camera.value] = sensor_data[camera.value].data self.state[camera.name] = sensor_data[camera.name].data
self.location = [measurements.player_measurements.transform.location.x, self.location = [measurements.player_measurements.transform.location.x,
measurements.player_measurements.transform.location.y, measurements.player_measurements.transform.location.y,
@@ -398,12 +399,25 @@ class CarlaEnvironment(Environment):
self.game.send_control(self.control) self.game.send_control(self.control)
def _load_experiment(self, experiment_idx):
self.current_experiment = self.experiment_suite.get_experiments()[experiment_idx]
self.scene = self.game.load_settings(self.current_experiment.conditions)
self.positions = self.scene.player_start_spots
self.num_positions = len(self.positions)
self.current_start_position_idx = 0
self.current_pose = 0
def _restart_environment_episode(self, force_environment_reset=False): def _restart_environment_episode(self, force_environment_reset=False):
# select start and end positions # select start and end positions
if self.experiment_suite: if self.experiment_suite:
# if an expeirent suite is available, follow its given poses # if an expeirent suite is available, follow its given poses
if self.current_pose >= len(self.current_experiment.poses):
# load a new experiment
self.current_experiment_idx = (self.current_experiment_idx + 1) % len(self.experiment_suite.get_experiments())
self._load_experiment(self.current_experiment_idx)
self.current_start_position_idx = self.current_experiment.poses[self.current_pose][0] self.current_start_position_idx = self.current_experiment.poses[self.current_pose][0]
self.current_goal = self.current_experiment.poses[self.current_pose][1] self.current_goal = self.positions[self.current_experiment.poses[self.current_pose][1]]
self.current_pose += 1 self.current_pose += 1
else: else:
# go over all the possible positions in a cyclic manner # go over all the possible positions in a cyclic manner
@@ -428,6 +442,6 @@ class CarlaEnvironment(Environment):
This can be different from the observation. For example, mujoco's observation is a measurements vector. 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 :return: numpy array containing the image that will be rendered to the screen
""" """
image = [self.state[camera.value] for camera in self.cameras] image = [self.state[camera.name] for camera in self.scene.sensors]
image = np.vstack(image) image = np.vstack(image)
return image return image

10
rl_coach/presets/CARLA_CIL.py
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@@ -40,7 +40,7 @@ agent_params = CILAgentParameters()
# forward camera and measurements input # forward camera and measurements input
agent_params.network_wrappers['main'].input_embedders_parameters = { agent_params.network_wrappers['main'].input_embedders_parameters = {
'forward_camera': InputEmbedderParameters(scheme=[Conv2d([32, 5, 2]), 'CameraRGB': InputEmbedderParameters(scheme=[Conv2d([32, 5, 2]),
Conv2d([32, 3, 1]), Conv2d([32, 3, 1]),
Conv2d([64, 3, 2]), Conv2d([64, 3, 2]),
Conv2d([64, 3, 1]), Conv2d([64, 3, 1]),
@@ -80,13 +80,13 @@ agent_params.network_wrappers['main'].learning_rate = 0.0002
# crop and rescale the image + use only the forward speed measurement # crop and rescale the image + use only the forward speed measurement
agent_params.input_filter = InputFilter() agent_params.input_filter = InputFilter()
agent_params.input_filter.add_observation_filter('forward_camera', 'cropping', agent_params.input_filter.add_observation_filter('CameraRGB', 'cropping',
ObservationCropFilter(crop_low=np.array([115, 0, 0]), ObservationCropFilter(crop_low=np.array([115, 0, 0]),
crop_high=np.array([510, -1, -1]))) crop_high=np.array([510, -1, -1])))
agent_params.input_filter.add_observation_filter('forward_camera', 'rescale', agent_params.input_filter.add_observation_filter('CameraRGB', 'rescale',
ObservationRescaleToSizeFilter( ObservationRescaleToSizeFilter(
ImageObservationSpace(np.array([88, 200, 3]), high=255))) ImageObservationSpace(np.array([88, 200, 3]), high=255)))
agent_params.input_filter.add_observation_filter('forward_camera', 'to_uint8', ObservationToUInt8Filter(0, 255)) agent_params.input_filter.add_observation_filter('CameraRGB', 'to_uint8', ObservationToUInt8Filter(0, 255))
agent_params.input_filter.add_observation_filter( agent_params.input_filter.add_observation_filter(
'measurements', 'select_speed', 'measurements', 'select_speed',
ObservationReductionBySubPartsNameFilter( ObservationReductionBySubPartsNameFilter(
@@ -113,7 +113,7 @@ agent_params.memory.num_classes = 4
############### ###############
env_params = CarlaEnvironmentParameters() env_params = CarlaEnvironmentParameters()
env_params.level = 'town1' env_params.level = 'town1'
env_params.cameras = [CameraTypes.FRONT] env_params.cameras = ['CameraRGB']
env_params.camera_height = 600 env_params.camera_height = 600
env_params.camera_width = 800 env_params.camera_width = 800
env_params.allow_braking = False env_params.allow_braking = False

2
rl_coach/utilities/carla_dataset_to_replay_buffer.py
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@@ -58,7 +58,7 @@ if __name__ == "__main__":
for transition_idx in range(file_length): for transition_idx in range(file_length):
transition = Transition( transition = Transition(
state={ state={
'forward_camera': observations[transition_idx], 'CameraRGB': observations[transition_idx],
'measurements': measurements[transition_idx], 'measurements': measurements[transition_idx],
'high_level_command': high_level_commands[transition_idx] 'high_level_command': high_level_commands[transition_idx]
}, },