89 lines
3.2 KiB
Python
89 lines
3.2 KiB
Python
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import os
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import logging
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import subprocess
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from typing import Dict
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import pandas as pd
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class CommandRunner:
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"""执行网格处理命令的类"""
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def __init__(self, output_dir: str):
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"""
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初始化命令执行器
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Args:
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output_dir: 输出目录路径
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"""
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self.output_dir = output_dir
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self.logger = logging.getLogger('UAV_Preprocess.CommandRunner')
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def run_grid_commands(self, grid_points: Dict[int, pd.DataFrame], enable_grid_division: bool = True):
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"""
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为每个网格顺序运行指定命令
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Args:
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grid_points: 网格点数据字典，键为网格索引，值为该网格的点数据
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enable_grid_division: 是否启用网格划分
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"""
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if not enable_grid_division:
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self._run_command(0)
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return
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self.logger.info("开始执行网格处理命令")
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# 顺序执行每个网格的命令
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for grid_idx in grid_points.keys():
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try:
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self._run_command(grid_idx)
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except Exception as e:
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self.logger.error(f"网格 {grid_idx + 1} 处理命令执行失败: {str(e)}")
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raise # 如果一个网格失败，停止后续执行
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def _run_command(self, grid_idx: int):
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"""
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执行单个网格的命令
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Args:
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grid_idx: 网格索引
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Raises:
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Exception: 当命令执行失败时抛出异常
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"""
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try:
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# 确定网格目录和命令
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grid_dir = os.path.join(self.output_dir, f'grid_{grid_idx + 1}')
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command = f"docker run -ti --rm -v {grid_dir}:/datasets opendronemap/odm --project-path /datasets project --feature-quality lowest --force-gps"
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self.logger.info(f"执行命令: {command} 在目录: {grid_dir}")
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# 在指定目录下执行命令
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process = subprocess.Popen(
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command,
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shell=True,
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cwd=grid_dir,
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stdout=subprocess.PIPE,
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stderr=subprocess.PIPE,
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text=True
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)
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# 获取命令输出
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stdout, stderr = process.communicate()
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# 检查命令执行结果
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if process.returncode == 0:
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self.logger.info(f"网格 {grid_idx + 1} 命令执行成功")
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self.logger.debug(f"命令输出至日志文件")
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with open(os.path.join(grid_dir, 'odm_success.log'), 'a', encoding='utf-8') as f:
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f.write(f"{stdout}")
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else:
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self.logger.error(f"网格 {grid_idx + 1} 命令执行失败")
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self.logger.error(f"错误信息输出至日志文件")
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with open(os.path.join(grid_dir, 'odm_error.log'), 'a', encoding='utf-8') as f:
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f.write(f"{stdout}")
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f.write(f"\n错误日志：\n")
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f.write(f"{stderr}")
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raise Exception(f"命令执行失败: {stderr}")
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except Exception as e:
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self.logger.error(f"网格 {grid_idx + 1} 命令执行出错: {str(e)}")
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raise
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