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# Copyright (c) Meta Platforms, Inc. and affiliates.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import csv
from dataclasses import dataclass
from typing import Any, Dict, List, Optional, Set

import numpy as np
from projectaria_tools.core.sensor_data import TimeDomain, TimeQueryOptions  # @manual
from projectaria_tools.core.sophus import SE3  # @manual

from .constants import POSE_DATA_CSV_COLUMNS
from .loader_poses_utils import check_csv_columns
from .pose_utils import lookup_timestamp


@dataclass
class ObjectPose3d:
    """
    Class to store pose of a single entity (object/headset/hand)
    """

    T_world_object: Optional[SE3] = None


@dataclass
class ObjectPose3dCollection:
    """
    Class to store the poses for a given timestamp
    """

    timestamp_ns: int
    poses: Dict[str, ObjectPose3d]

    @property
    def object_uid_list(self) -> Set[str]:
        return set(self.poses.keys())


ObjectPose3dTrajectory = Dict[int, ObjectPose3dCollection]


@dataclass
class ObjectPose3dCollectionWithDt:
    pose3d_collection: ObjectPose3dCollection
    time_delta_ns: int


class ObjectPose3dProvider(object):
    def __init__(self, pose3d_trajectory: ObjectPose3dTrajectory):
        self._pose3d_trajectory: ObjectPose3dTrajectory = pose3d_trajectory
        #排序时间戳
        self._sorted_timestamp_ns_list: List[int] = sorted(
            self._pose3d_trajectory.keys()
        )
        #所有出现过的物体ID
        self._object_uids_with_poses: Set = {
            x for v in self._pose3d_trajectory.values() for x in v.object_uid_list
        }

    #像属性一样访问，不用加括号
    @property
    def timestamp_ns_list(self) -> List[int]:
        return self._sorted_timestamp_ns_list

    @property
    def object_uids_with_poses(self) -> Set[str]:
        return set(self._object_uids_with_poses)

    def get_data_statistics(self) -> Dict[str, Any]:
        """
        Returns the stats of the trajectory
        """
        stats = {}
        stats["num_frames"] = len(self._sorted_timestamp_ns_list)
        stats["num_objects"] = len(self._object_uids_with_poses)
        stats["object_uids"] = [str(x) for x in self._object_uids_with_poses]
        return stats

    def get_pose_at_timestamp(
        self,
        timestamp_ns: int,
        time_query_options: TimeQueryOptions,
        time_domain: TimeDomain,
        acceptable_time_delta: Optional[int] = None,
    ) -> Optional[ObjectPose3dCollectionWithDt]:
        """
        Return the list of poses available at the given timestamp
        """
        if time_domain is not TimeDomain.TIME_CODE:
            raise ValueError("Value other than TimeDomain.TIME_CODE not yet supported.")

        pose3d_collection, time_delta_ns = lookup_timestamp(
            time_indexed_dict=self._pose3d_trajectory,
            sorted_timestamp_list=self._sorted_timestamp_ns_list,
            query_timestamp=timestamp_ns,
            time_query_options=time_query_options,
        )

        if (
            pose3d_collection is None
            or time_delta_ns is None
            or (
                acceptable_time_delta is not None
                and abs(time_delta_ns) > acceptable_time_delta
            )
        ):
            return None
        else:
            return ObjectPose3dCollectionWithDt(
                pose3d_collection=pose3d_collection, time_delta_ns=time_delta_ns
            )

#生成了一个pose3d_trajectory里面有物品在每个时间下的位置
def load_object_pose_trajectory_from_csv(filename: str) -> ObjectPose3dTrajectory:
    """Load Dynamic Objects meta data from a CSV file.
    Keyword arguments:
    filename -- the csv file i.e. sequence_folder + "/dynamic_objects.csv"
    """
    #空字典，后面逐行读 CSV 往里填数据
    pose3d_trajectory: ObjectPose3dTrajectory = {}
    # Open the CSV file for reading
    with open(filename, "r") as f:
        reader = csv.reader(f)

        # Read the header row
        #读表头
        header = next(reader)

        # Ensure we have the desired columns
        check_csv_columns(header, POSE_DATA_CSV_COLUMNS)

        # Read the rest of the rows in the CSV file
        for row in reader:
            #位置
            translation = [
                #"t_wo_x[m]" 这个字符串在 header 列表的第几位？ 然后读取
                row[header.index("t_wo_x[m]")],
                row[header.index("t_wo_y[m]")],
                row[header.index("t_wo_z[m]")],
            ]
            #朝向
            quaternion_xyz = [
                ##"q_wo_x 这个字符串在 header 列表的第几位？ 然后读取
                row[header.index("q_wo_x")],
                row[header.index("q_wo_y")],
                row[header.index("q_wo_z")],
            ]
            quaternion_w = row[header.index("q_wo_w")]
            timestamp_ns = int(row[header.index("timestamp[ns]")])
            object_uid = str(row[header.index("object_uid")])
            #把位置和朝向转换成 SE3 变换矩阵，se3 物品位置和朝向的信息    
            T_world_object = SE3.from_quat_and_translation(
                float(quaternion_w),
                np.array([float(o) for o in quaternion_xyz]),
                np.array([float(o) for o in translation]),
            )[0]

            pose3d = ObjectPose3d(T_world_object=T_world_object)
            #确保timestamp_ns有位置
            if timestamp_ns not in pose3d_trajectory:
                pose3d_trajectory[timestamp_ns] = ObjectPose3dCollection(
                    timestamp_ns=timestamp_ns, poses={}
                )

            pose3d_trajectory[timestamp_ns].poses[object_uid] = pose3d

    return pose3d_trajectory


def load_pose_provider_from_csv(filename: str) -> ObjectPose3dProvider:
    """
    Load the ObjectPose3dProvider from a csv file
    """
    return ObjectPose3dProvider(
        pose3d_trajectory=load_object_pose_trajectory_from_csv(filename)
    )

	# Copyright (c) Meta Platforms, Inc. and affiliates.
	#
	# Licensed under the Apache License, Version 2.0 (the "License");
	# you may not use this file except in compliance with the License.
	# You may obtain a copy of the License at
	#
	# http://www.apache.org/licenses/LICENSE-2.0
	#
	# Unless required by applicable law or agreed to in writing, software
	# distributed under the License is distributed on an "AS IS" BASIS,
	# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
	# See the License for the specific language governing permissions and
	# limitations under the License.

	import csv
	from dataclasses import dataclass
	from typing import Any, Dict, List, Optional, Set

	import numpy as np
	from projectaria_tools.core.sensor_data import TimeDomain, TimeQueryOptions # @manual
	from projectaria_tools.core.sophus import SE3 # @manual

	from .constants import POSE_DATA_CSV_COLUMNS
	from .loader_poses_utils import check_csv_columns
	from .pose_utils import lookup_timestamp


	@dataclass
	class ObjectPose3d:
	"""
	Class to store pose of a single entity (object/headset/hand)
	"""

	T_world_object: Optional[SE3] = None


	@dataclass
	class ObjectPose3dCollection:
	"""
	Class to store the poses for a given timestamp
	"""

	timestamp_ns: int
	poses: Dict[str, ObjectPose3d]

	@property
	def object_uid_list(self) -> Set[str]:
	return set(self.poses.keys())


	ObjectPose3dTrajectory = Dict[int, ObjectPose3dCollection]


	@dataclass
	class ObjectPose3dCollectionWithDt:
	pose3d_collection: ObjectPose3dCollection
	time_delta_ns: int


	class ObjectPose3dProvider(object):
	def __init__(self, pose3d_trajectory: ObjectPose3dTrajectory):
	self._pose3d_trajectory: ObjectPose3dTrajectory = pose3d_trajectory
	#排序时间戳
	self._sorted_timestamp_ns_list: List[int] = sorted(
	self._pose3d_trajectory.keys()
	)
	#所有出现过的物体ID
	self._object_uids_with_poses: Set = {
	x for v in self._pose3d_trajectory.values() for x in v.object_uid_list
	}

	#像属性一样访问，不用加括号
	@property
	def timestamp_ns_list(self) -> List[int]:
	return self._sorted_timestamp_ns_list

	@property
	def object_uids_with_poses(self) -> Set[str]:
	return set(self._object_uids_with_poses)

	def get_data_statistics(self) -> Dict[str, Any]:
	"""
	Returns the stats of the trajectory
	"""
	stats = {}
	stats["num_frames"] = len(self._sorted_timestamp_ns_list)
	stats["num_objects"] = len(self._object_uids_with_poses)
	stats["object_uids"] = [str(x) for x in self._object_uids_with_poses]
	return stats

	def get_pose_at_timestamp(
	self,
	timestamp_ns: int,
	time_query_options: TimeQueryOptions,
	time_domain: TimeDomain,
	acceptable_time_delta: Optional[int] = None,
	) -> Optional[ObjectPose3dCollectionWithDt]:
	"""
	Return the list of poses available at the given timestamp
	"""
	if time_domain is not TimeDomain.TIME_CODE:
	raise ValueError("Value other than TimeDomain.TIME_CODE not yet supported.")

	pose3d_collection, time_delta_ns = lookup_timestamp(
	time_indexed_dict=self._pose3d_trajectory,
	sorted_timestamp_list=self._sorted_timestamp_ns_list,
	query_timestamp=timestamp_ns,
	time_query_options=time_query_options,
	)

	if (
	pose3d_collection is None
	or time_delta_ns is None
	or (
	acceptable_time_delta is not None
	and abs(time_delta_ns) > acceptable_time_delta
	)
	):
	return None
	else:
	return ObjectPose3dCollectionWithDt(
	pose3d_collection=pose3d_collection, time_delta_ns=time_delta_ns
	)

	#生成了一个pose3d_trajectory里面有物品在每个时间下的位置
	def load_object_pose_trajectory_from_csv(filename: str) -> ObjectPose3dTrajectory:
	"""Load Dynamic Objects meta data from a CSV file.

	Keyword arguments:
	filename -- the csv file i.e. sequence_folder + "/dynamic_objects.csv"
	"""
	#空字典，后面逐行读 CSV 往里填数据
	pose3d_trajectory: ObjectPose3dTrajectory = {}
	# Open the CSV file for reading
	with open(filename, "r") as f:
	reader = csv.reader(f)

	# Read the header row
	#读表头
	header = next(reader)

	# Ensure we have the desired columns
	check_csv_columns(header, POSE_DATA_CSV_COLUMNS)

	# Read the rest of the rows in the CSV file
	for row in reader:
	#位置
	translation = [
	#"t_wo_x[m]" 这个字符串在 header 列表的第几位？然后读取
	row[header.index("t_wo_x[m]")],
	row[header.index("t_wo_y[m]")],
	row[header.index("t_wo_z[m]")],
	]
	#朝向
	quaternion_xyz = [
	##"q_wo_x 这个字符串在 header 列表的第几位？然后读取
	row[header.index("q_wo_x")],
	row[header.index("q_wo_y")],
	row[header.index("q_wo_z")],
	]
	quaternion_w = row[header.index("q_wo_w")]
	timestamp_ns = int(row[header.index("timestamp[ns]")])
	object_uid = str(row[header.index("object_uid")])
	#把位置和朝向转换成 SE3 变换矩阵，se3 物品位置和朝向的信息
	T_world_object = SE3.from_quat_and_translation(
	float(quaternion_w),
	np.array([float(o) for o in quaternion_xyz]),
	np.array([float(o) for o in translation]),
	)[0]

	pose3d = ObjectPose3d(T_world_object=T_world_object)
	#确保timestamp_ns有位置
	if timestamp_ns not in pose3d_trajectory:
	pose3d_trajectory[timestamp_ns] = ObjectPose3dCollection(
	timestamp_ns=timestamp_ns, poses={}
	)

	pose3d_trajectory[timestamp_ns].poses[object_uid] = pose3d

	return pose3d_trajectory


	def load_pose_provider_from_csv(filename: str) -> ObjectPose3dProvider:
	"""
	Load the ObjectPose3dProvider from a csv file
	"""
	return ObjectPose3dProvider(
	pose3d_trajectory=load_object_pose_trajectory_from_csv(filename)
	)