def get_observation(
self,
observations,
*args: Any,
episode: NavigationEpisode,
**kwargs: Any,
) -> Optional[int]:
if self.config.GOAL_SPEC == "TASK_CATEGORY_ID":
if len(episode.goals) == 0:
logger.error(
f"No goal specified for episode {episode.episode_id}."
)
return None
if not isinstance(episode.goals[0], ObjectGoal):
logger.error(
f"First goal should be ObjectGoal, episode {episode.episode_id}."
)
return None
category_name = episode.goals[0].object_category
return np.array(
[self._dataset.category_to_task_category_id[category_name]],
dtype=np.int64,
)
elif self.config.GOAL_SPEC == "OBJECT_ID":
return np.array([episode.goals[0].object_name_id], dtype=np.int64)
else:
raise RuntimeError(
"Wrong GOAL_SPEC specified for ObjectGoalSensor."
)
def update_metric(
self, episode: NavigationEpisode, *args: Any, **kwargs: Any
):
current_position = self._sim.get_agent_state().position
if self._previous_position is None or not np.allclose(
self._previous_position, current_position, atol=1e-4
):
if self._config.DISTANCE_TO == "POINT":
distance_to_target = self._sim.geodesic_distance(
current_position,
[goal.position for goal in episode.goals],
episode,
)
elif self._config.DISTANCE_TO == "VIEW_POINTS":
distance_to_target = self._sim.geodesic_distance(
current_position, self._episode_view_points, episode
)
else:
logger.error(
f"Non valid DISTANCE_TO parameter was provided: {self._config.DISTANCE_TO}"
)
self._previous_position = current_position
self._metric = distance_to_target
def update_metric(self, episode: Episode, task: EmbodiedTask, *args: Any,
**kwargs: Any):
current_position = self._sim.get_agent_state().position
if self.goal_idx == -1: self.goal_idx = 0
else:
self.goal_idx = task.measurements.measures[
GoalIndex.cls_uuid].get_metric()['curr_goal_index']
if self._previous_position is None or not np.allclose(
self._previous_position, current_position, atol=1e-4):
if self._config.DISTANCE_TO == "POINT":
distance_to_target = self._sim.geodesic_distance(
current_position,
episode.goals[self.goal_idx].position,
episode,
)
elif self._config.DISTANCE_TO == "VIEW_POINTS":
distance_to_target = self._sim.geodesic_distance(
current_position, self._episode_view_points, episode)
else:
logger.error(
f"Non valid DISTANCE_TO parameter was provided: {self._config.DISTANCE_TO}"
)
self._previous_position = current_position
self._metric = distance_to_target
def get_observation(
self,
observations,
*args: Any,
episode: ObjectGoalNavEpisode,
**kwargs: Any,
) -> Optional[int]:
if self.config.GOAL_SPEC == "TASK_CATEGORY_ID":
if len(episode.goals) == 0:
logger.error(
f"No goal specified for episode {episode.episode_id}.")
return None
if not isinstance(episode.goals[0], ObjectGoal):
logger.error(
f"First goal should be ObjectGoal, episode {episode.episode_id}."
)
return None
category_name = episode.object_category
return np.array(
[self._dataset.category_to_task_category_id[category_name]],
dtype=np.int64,
)
elif self.config.GOAL_SPEC == "OBJECT_ID":
return np.array([episode.goals[0].object_name_id], dtype=np.int64)
elif self.config.GOAL_SPEC == "OBJECT_IMG":
episode_id = episode.episode_id
scene_id = episode.scene_id
if (self.curr_episode_id != episode_id) and (self.curr_scene_id !=
scene_id):
closest = episode.info['closest_goal_object_id']
for goal in episode.goals:
if goal.object_id == int(closest):
viewpoint = goal.view_points[0].agent_state
break
obs = self._sim.get_observations_at(
episode.info['best_viewpoint_position'],
viewpoint.rotation)
rgb_array = obs['rgb'] / 255.0
depth_array = obs['depth']
category_array = np.ones_like(
depth_array) * self._dataset.category_to_task_category_id[
episode.object_category]
self.goal_obs = np.concatenate(
[rgb_array, depth_array, category_array], 2)
self.curr_episode_id = episode_id
self.curr_scene_id = scene_id
return self.goal_obs
else:
raise RuntimeError(
"Wrong GOAL_SPEC specified for ObjectGoalSensor.")
def update_metric(self, episode, *args: Any, **kwargs: Any):
current_position = self._sim.get_agent_state().position.tolist()
if self._config.DISTANCE_TO == "POINT":
distance_to_target = self._sim.geodesic_distance(
current_position, [goal.position for goal in episode.goals])
elif self._config.DISTANCE_TO == "VIEW_POINTS":
distance_to_target = self._sim.geodesic_distance(
current_position, self._episode_view_points)
else:
logger.error(
f"Non valid DISTANCE_TO parameter was provided: {self._config.DISTANCE_TO}"
)
self._agent_episode_distance += self._euclidean_distance(
current_position, self._previous_position)
self._previous_position = current_position
self._metric = distance_to_target
