import os
import shutil
from datetime import timedelta
from dataclasses import dataclass
from typing import Dict, Tuple
import psutil
import pandas as pd
from pathlib import Path

from utils.directory_manager import DirectoryManager
from utils.gps_extractor import GPSExtractor
from utils.grid_divider import GridDivider
from utils.logger import setup_logger
from utils.visualizer import FilterVisualizer
from utils.docker_runner import DockerRunner
from filter.cluster_filter import GPSCluster
from post_pro.conv_obj import ConvertOBJ


@dataclass
class ProcessConfig:
    """配置类"""

    image_dir: str
    output_dir: str
    # 聚类过滤参数
    cluster_eps: float = 0.01
    cluster_min_samples: int = 5
    # 时间组重叠过滤参数
    time_group_overlap_threshold: float = 0.7
    time_group_interval: timedelta = timedelta(minutes=5)
    # 孤立点过滤参数
    filter_distance_threshold: float = 0.001  # 经纬度距离
    filter_min_neighbors: int = 6
    # 密集点过滤参数
    filter_grid_size: float = 0.001
    filter_dense_distance_threshold: float = 10  # 普通距离，单位：米
    filter_time_threshold: timedelta = timedelta(minutes=5)
    # 网格划分参数
    grid_overlap: float = 0.05
    grid_size: float = 500
    # 几个pipline过程是否开启
    mode: str = "快拼模式"
    accuracy: str = "medium"
    produce_dem: bool = False


class ODM_Plugin:
    def __init__(self, config: ProcessConfig):
        self.config = config

        # 初始化目录管理器
        self.dir_manager = DirectoryManager(config)
        # 清理并重建输出目录
        self.dir_manager.clean_output_dir()
        self.dir_manager.setup_output_dirs()
        # 检查磁盘空间
        self.dir_manager.check_disk_space()
        # 修改输入目录，符合ODM要求，从这里开始，image_dir就是project_path
        self.project_path = self.dir_manager.rename_input_dir()

        # 初始化其他组件
        self.logger = setup_logger(config.output_dir)
        self.gps_points = None
        self.grid_points = None
        self.visualizer = FilterVisualizer(config.output_dir)

    def extract_gps(self) -> pd.DataFrame:
        """提取GPS数据"""
        self.logger.info("开始提取GPS数据")
        extractor = GPSExtractor(self.project_path)
        self.gps_points = extractor.extract_all_gps()
        self.logger.info(f"成功提取 {len(self.gps_points)} 个GPS点")

    def cluster(self):
        """使用DBSCAN对GPS点进行聚类，只保留最大的类"""
        previous_points = self.gps_points.copy()
        clusterer = GPSCluster(
            self.gps_points,
            eps=self.config.cluster_eps,
            min_samples=self.config.cluster_min_samples
        )

        self.clustered_points = clusterer.fit()
        self.gps_points = clusterer.get_cluster_stats(self.clustered_points)

        self.visualizer.visualize_filter_step(
            self.gps_points, previous_points, "1-Clustering")

    def divide_grids(self):
        """划分网格
        Returns:
            tuple: (grid_points, translations)
                - grid_points: 网格点数据字典
                - translations: 网格平移量字典
        """
        grid_divider = GridDivider(
            overlap=self.config.grid_overlap,
            grid_size=self.config.grid_size,
            project_path=self.project_path,
            output_dir=self.config.output_dir
        )
        grids, self.grid_points = grid_divider.adjust_grid_size_and_overlap(
            self.gps_points
        )
        grid_divider.visualize_grids(self.gps_points, grids)
        grid_divider.save_image_groups(self.grid_points)
        if len(grids) >= 20:
            self.logger.warning("网格数量已超过20, 需要人工调整分区")

    def odm_docker_runner(self):
        """"运行OMD docker容器"""
        self.logger.info("开始运行Docker容器")
        # TODO：加一些容错处理
        docker_runner = DockerRunner(self.project_path, self.config)
        docker_runner.run_odm_container()

    def convert_obj(self):
        """转换OBJ模型"""
        self.logger.info("开始转换OBJ模型")
        converter = ConvertOBJ(self.config.output_dir)
        converter.convert_grid_obj(self.grid_points)

    def post_process(self):
        """后处理：合并或复制处理结果"""
        self.logger.info("开始后处理")

        self.logger.info("拷贝正射影像至输出目录")
        orthophoto_tif_path = os.path.join(
            self.project_path, "project", "odm_orthophoto", "odm_orthophoto.tif")
        shutil.copy(orthophoto_tif_path, self.config.output_dir)
        # if self.config.mode == "三维模式":
        #     self.convert_obj()
        # else:
        #     pass

    def process(self):
        """执行完整的预处理流程"""
        try:
            self.extract_gps()
            self.cluster()
            self.divide_grids()
            self.logger.info("==========预处理任务完成==========")
            self.odm_docker_runner()
            self.post_process()

        except Exception as e:
            self.logger.error(f"处理过程中发生错误: {str(e)}", exc_info=True)
            raise