155 lines
5.2 KiB
Python
155 lines
5.2 KiB
Python
import os
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import time
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import logging
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from typing import Dict, Tuple
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import pandas as pd
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import docker
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class ODMProcessMonitor:
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"""ODM处理监控器"""
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def __init__(self, output_dir: str, mode: str = "三维模式"):
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self.output_dir = output_dir
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self.logger = logging.getLogger('UAV_Preprocess.ODMMonitor')
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self.mode = mode
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def run_odm_with_monitor(self, grid_dir: str, grid_id: tuple) -> Tuple[bool, str]:
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"""运行ODM命令"""
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self.logger.info(f"开始处理网格 ({grid_id[0]},{grid_id[1]})")
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success = False
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error_msg = ""
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max_retries = 3
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current_try = 0
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cpu_cores = os.cpu_count()
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# 初始化 Docker 客户端
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client = docker.from_env()
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while current_try < max_retries:
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current_try += 1
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self.logger.info(
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f"第 {current_try} 次尝试处理网格 ({grid_id[0]},{grid_id[1]})")
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# 构建 Docker 容器运行参数
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grid_dir = grid_dir[0].lower(
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) + grid_dir[1:].replace('\\', '/')
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volumes = {
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grid_dir: {'bind': '/datasets', 'mode': 'rw'}
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}
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command = (
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f"--project-path /datasets project "
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f"--max-concurrency {cpu_cores} "
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f"--force-gps "
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f"--use-exif "
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f"--use-hybrid-bundle-adjustment "
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f"--optimize-disk-space "
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f"--orthophoto-cutline "
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f"--feature-type sift "
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f"--orthophoto-resolution 8 "
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# f"--mesh-size 5000000 "
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# f"--mesh-octree-depth 13 "
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)
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if self.mode == "快拼模式":
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command += (
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f"--fast-orthophoto "
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f"--skip-3dmodel "
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)
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else: # 三维模式参数
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command += (
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f"--dsm "
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f"--dtm "
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)
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if current_try == 1:
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command += (
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f"--feature-quality low "
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)
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command += "--rerun-all"
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self.logger.info(f"Docker 命令: {command}")
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# 运行 Docker 容器
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container = client.containers.run(
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image="opendronemap/odm:gpu",
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command=command,
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volumes=volumes,
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detach=True,
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remove=False,
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runtime="nvidia", # 使用 GPU
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)
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# 等待容器运行完成
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exit_status = container.wait()
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if exit_status["StatusCode"] != 0:
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self.logger.error(
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f"容器运行失败，退出状态码: {exit_status['StatusCode']}")
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# 获取容器的错误日志
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error_msg = container.logs(
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stderr=True).decode("utf-8").splitlines()
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self.logger.error("容器运行失败的最后 50 行错误日志：")
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for line in error_msg[-50:]:
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self.logger.error(line)
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container.remove()
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time.sleep(5)
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else:
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# 获取所有日志
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logs = container.logs().decode("utf-8").splitlines()
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# 输出最后 50 行日志
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self.logger.info("容器运行完成，以下是最后 50 行日志：")
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for line in logs[-50:]:
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self.logger.info(line)
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success = True
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error_msg = ""
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container.remove()
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break
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return success, error_msg
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def process_all_grids(self, grid_points: Dict[tuple, pd.DataFrame]) -> list:
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"""处理所有网格
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Returns:
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Dict[tuple, pd.DataFrame]: 成功处理的网格点数据字典
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"""
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self.logger.info("开始执行网格处理")
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successful_grid_lt = []
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failed_grids = []
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for grid_id, points in grid_points.items():
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grid_dir = os.path.join(
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self.output_dir, f'grid_{grid_id[0]}_{grid_id[1]}'
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)
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try:
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success, error_msg = self.run_odm_with_monitor(
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grid_dir=grid_dir,
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grid_id=grid_id,
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)
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if success:
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successful_grid_lt.append(grid_id)
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else:
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self.logger.error(
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f"网格 ({grid_id[0]},{grid_id[1]})")
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failed_grids.append(grid_id)
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except Exception as e:
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error_msg = str(e)
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self.logger.error(
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f"处理网格 ({grid_id[0]},{grid_id[1]}) 时发生异常: {error_msg}")
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failed_grids.append((grid_id, error_msg))
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# 汇总处理结果
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total_grids = len(grid_points)
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failed_count = len(failed_grids)
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success_count = len(successful_grid_lt)
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self.logger.info(
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f"网格处理完成。总计: {total_grids}, 成功: {success_count}, 失败: {failed_count}")
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if len(successful_grid_lt) == 0:
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raise Exception("所有网格处理都失败，无法继续处理")
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return successful_grid_lt
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