UAV/utils/odm_monitor.py

import os
import time
import logging
from typing import Dict, Tuple
import pandas as pd
import numpy as np
from osgeo import gdal
import docker


class ODMProcessMonitor:
    """ODM处理监控器"""

    def __init__(self, output_dir: str, mode: str = "三维模式"):
        self.output_dir = output_dir
        self.logger = logging.getLogger('UAV_Preprocess.ODMMonitor')
        self.mode = mode

    def run_odm_with_monitor(self, grid_dir: str, grid_id: tuple) -> Tuple[bool, str]:
        """运行ODM命令"""
        self.logger.info(f"开始处理网格 ({grid_id[0]},{grid_id[1]})")
        success = False
        error_msg = ""
        max_retries = 3
        current_try = 0

        # 初始化 Docker 客户端
        client = docker.from_env()

        while current_try < max_retries:
            current_try += 1
            self.logger.info(
                f"第 {current_try} 次尝试处理网格 ({grid_id[0]},{grid_id[1]})")

            # 构建 Docker 容器运行参数
            grid_dir = grid_dir[0].lower(
            ) + grid_dir[1:].replace('\\', '/')
            volumes = {
                grid_dir: {'bind': '/datasets', 'mode': 'rw'}
            }
            command = (
                f"--project-path /datasets project "
                f"--max-concurrency 15 "
                f"--force-gps "
                f"--use-exif "
                f"--use-hybrid-bundle-adjustment "
                f"--optimize-disk-space "
                f"--orthophoto-cutline "
                f"--feature-type sift "
                f"--orthophoto-resolution 8 "
            )

            if self.mode == "快拼模式":
                command += (
                    f"--fast-orthophoto "
                    f"--skip-3dmodel "
                )
            else:  # 三维模式参数
                command += (
                    f"--dsm "
                    f"--dtm "
                )

            command += "--rerun-all"

            self.logger.info(f"Docker 命令: {command}")

            # 运行 Docker 容器
            container = client.containers.run(
                image="opendronemap/odm:gpu",
                command=command,
                volumes=volumes,
                detach=True,
                remove=False,
                runtime="nvidia",  # 使用 GPU
            )
            # 等待容器运行完成
            exit_status = container.wait()
            if exit_status["StatusCode"] != 0:
                self.logger.error(
                    f"容器运行失败，退出状态码: {exit_status['StatusCode']}")
                # 获取容器的错误日志
                error_msg = container.logs(
                    stderr=True).decode("utf-8").splitlines()
                self.logger.error("容器运行失败的详细错误日志：")
                for line in error_msg:
                    self.logger.error(line)
                container.remove()
                time.sleep(5)
            else:
                # 获取所有日志
                logs = container.logs().decode("utf-8").splitlines()
                # 输出最后 50 行日志
                self.logger.info("容器运行完成，以下是最后 50 行日志：")
                for line in logs[-50:]:
                    self.logger.info(line)
                success = True
                error_msg = ""
                container.remove()
                break


        return success, error_msg

    def process_all_grids(self, grid_points: Dict[tuple, pd.DataFrame]) -> list:
        """处理所有网格

        Returns:
            Dict[tuple, pd.DataFrame]: 成功处理的网格点数据字典
        """
        self.logger.info("开始执行网格处理")
        successful_grid_lt = []
        failed_grids = []

        for grid_id, points in grid_points.items():
            grid_dir = os.path.join(
                self.output_dir, f'grid_{grid_id[0]}_{grid_id[1]}'
            )

            try:
                success, error_msg = self.run_odm_with_monitor(
                    grid_dir=grid_dir,
                    grid_id=grid_id,
                )

                if success:
                    successful_grid_lt.append(grid_id)
                else:
                    self.logger.error(
                        f"网格 ({grid_id[0]},{grid_id[1]}) 处理失败: {error_msg}")
                    failed_grids.append((grid_id, error_msg))

            except Exception as e:
                error_msg = str(e)
                self.logger.error(
                    f"处理网格 ({grid_id[0]},{grid_id[1]}) 时发生异常: {error_msg}")
                failed_grids.append((grid_id, error_msg))

        # 汇总处理结果
        total_grids = len(grid_points)
        failed_count = len(failed_grids)
        success_count = len(successful_grid_lt)

        self.logger.info(
            f"网格处理完成。总计: {total_grids}, 成功: {success_count}, 失败: {failed_count}")
        if failed_grids:
            self.logger.error("失败的网格:")
            for grid_id, error_msg in failed_grids:
                self.logger.error(
                    f"网格 ({grid_id[0]},{grid_id[1]}): {error_msg}")

        if len(successful_grid_lt) == 0:
            raise Exception("所有网格处理都失败，无法继续处理")

        return successful_grid_lt