def __deserialize_goal(serialized_goal: Dict[str, Any]) -> ObjectGoal:
g = ObjectGoal(**serialized_goal)
for vidx, view in enumerate(g.view_points):
view_location = ObjectViewLocation(**view)
view_location.agent_state = AgentState(**view_location.agent_state)
g.view_points[vidx] = view_location
return g
def from_json(self,
json_str: str,
scenes_dir: Optional[str] = None) -> None:
deserialized = json.loads(json_str)
self.__dict__.update(deserialized)
self.answer_vocab = VocabDict(word_list=self.answer_vocab["word_list"])
self.question_vocab = VocabDict(
word_list=self.question_vocab["word_list"])
for ep_index, episode in enumerate(deserialized["episodes"]):
episode = EQAEpisode(**episode)
if scenes_dir is not None:
if episode.scene_id.startswith(DEFAULT_SCENE_PATH_PREFIX):
episode.scene_id = episode.scene_id[
len(DEFAULT_SCENE_PATH_PREFIX):]
episode.scene_id = os.path.join(scenes_dir, episode.scene_id)
episode.question = QuestionData(**episode.question)
for g_index, goal in enumerate(episode.goals):
episode.goals[g_index] = ObjectGoal(**goal)
new_goal = episode.goals[g_index]
if new_goal.view_points is not None:
for p_index, agent_state in enumerate(
new_goal.view_points):
new_goal.view_points[p_index] = AgentState(
**agent_state)
if episode.shortest_paths is not None:
for path in episode.shortest_paths:
for p_index, point in enumerate(path):
path[p_index] = ShortestPathPoint(**point)
self.episodes[ep_index] = episode
def from_json(self,
json_str: str,
scenes_dir: Optional[str] = None) -> None:
deserialized = json.loads(json_str)
if CONTENT_SCENES_PATH_FIELD in deserialized:
self.content_scenes_path = deserialized[CONTENT_SCENES_PATH_FIELD]
if "category_to_task_category_id" in deserialized:
self.category_to_task_category_id = deserialized[
"category_to_task_category_id"]
if "category_to_scene_annotation_category_id" in deserialized:
self.category_to_scene_annotation_category_id = deserialized[
"category_to_scene_annotation_category_id"]
if "category_to_mp3d_category_id" in deserialized:
self.category_to_scene_annotation_category_id = deserialized[
"category_to_mp3d_category_id"]
assert len(self.category_to_task_category_id) == len(
self.category_to_scene_annotation_category_id)
assert set(self.category_to_task_category_id.keys()) == set(
self.category_to_scene_annotation_category_id.keys(
)), "category_to_task and category_to_mp3d must have the same keys"
for episode in deserialized["episodes"]:
episode = NavigationEpisode(**episode)
if scenes_dir is not None:
if episode.scene_id.startswith(DEFAULT_SCENE_PATH_PREFIX):
episode.scene_id = episode.scene_id[
len(DEFAULT_SCENE_PATH_PREFIX):]
episode.scene_id = os.path.join(scenes_dir, episode.scene_id)
for i in range(len(episode.goals)):
episode.goals[i] = ObjectGoal(**episode.goals[i])
for vidx, view in enumerate(episode.goals[i].view_points):
view_location = ObjectViewLocation(**view)
view_location.agent_state = AgentState(
**view_location.agent_state)
episode.goals[i].view_points[vidx] = view_location
if episode.shortest_paths is not None:
for path in episode.shortest_paths:
for p_index, point in enumerate(path):
point = {
"action": point,
"rotation": None,
"position": None,
}
path[p_index] = ShortestPathPoint(**point)
self.episodes.append(episode)
for i, ep in enumerate(self.episodes):
ep.episode_id = str(i)
def generate_objectnav_goals_by_category(sim: Simulator,
task_category) -> ObjectGoal:
scene = sim.semantic_annotations()
target = dict()
for obj in scene.objects:
if obj is not None:
# print(
# f"Object id:{obj.id}, category:{obj.category.name()}, Index:{obj.category.index()}"
# f" center:{obj.aabb.center}, dims:{obj.aabb.sizes}"
# )
if obj.category.name() in task_category.keys():
if obj.category.index() in target:
target[obj.category.index()].append(obj)
else:
target[obj.category.index()] = [obj]
for i in target:
# print("target episode len:", len(target[i]))
object_category = target[i][0].category.name()
# print("object_category :", object_category)
str_goal = f"{os.path.basename(sim.config.SCENE)}_{object_category}"
# print(str_goal)
goals_by = []
for j in range(len(target[i])):
object_view_list = []
for x in np.arange(
target[i][j].aabb.center[0] -
target[i][j].aabb.sizes[0] / 2.0,
target[i][j].aabb.center[0] +
target[i][j].aabb.sizes[0] / 2.0, 0.1):
for y in np.arange(
target[i][j].aabb.center[2] -
target[i][j].aabb.sizes[2] / 2.0,
target[i][j].aabb.center[2] +
target[i][j].aabb.sizes[2] / 2.0, 0.1):
# print("x, y: ", type(x)) # np.float6
# print("x, y: ", type(target[i][j].aabb.center[1])) # np.floa32 报错
object_view_list.append(
ObjectViewLocation(
agent_state=AgentState(position=[
x, target[i][j].aabb.center[1].astype(
np.float64), y
]),
iou=0.0,
))
# print(type(object_view_list))
goal_by_object = ObjectGoal(
position=target[i][j].aabb.center,
radius=0.5,
object_id=int(re.findall(r"\d+", target[i][j].id)[0]),
object_name=target[i][j].id,
object_category=object_category,
view_points=object_view_list,
)
goals_by.append(goal_by_object)
yield str_goal, goals_by