diff --git a/odm_preprocess.py b/odm_preprocess.py index 9bad923..949c063 100644 --- a/odm_preprocess.py +++ b/odm_preprocess.py @@ -248,6 +248,17 @@ class ImagePreprocessor: self.logger.info("开始合并OBJ模型") merger = MergeObj(self.config.output_dir) merger.merge_grid_obj(grid_points, translations) + + def post_process(self, successful_grid_points: Dict[tuple, pd.DataFrame], grid_points: Dict[tuple, pd.DataFrame], translations: Dict[tuple, tuple]): + if len(successful_grid_points) < len(grid_points): + self.logger.warning( + f"有 {len(grid_points) - len(successful_grid_points)} 个网格处理失败，" + f"将只合并成功处理的 {len(successful_grid_points)} 个网格" + ) + self.merge_tif(successful_grid_points, self.config.produce_dem) + if self.config.mode != "快拼模式": + self.merge_ply(successful_grid_points) + self.merge_obj(successful_grid_points, translations) def process(self): """执行完整的预处理流程""" @@ -260,10 +271,10 @@ class ImagePreprocessor: self.copy_images(grid_points) self.logger.info("预处理任务完成") - self.odm_monitor.process_all_grids(grid_points, self.config.produce_dem) - self.merge_tif(grid_points, self.config.produce_dem) - self.merge_ply(grid_points) - self.merge_obj(grid_points, translations) + successful_grid_points = self.odm_monitor.process_all_grids(grid_points, self.config.produce_dem) + + self.post_process(successful_grid_points, grid_points, translations) + except Exception as e: self.logger.error(f"处理过程中发生错误: {str(e)}", exc_info=True) raise diff --git a/utils/odm_monitor.py b/utils/odm_monitor.py index d053f5d..59d13b2 100644 --- a/utils/odm_monitor.py +++ b/utils/odm_monitor.py @@ -3,8 +3,22 @@ import logging import subprocess from typing import Dict, Tuple import pandas as pd +import numpy as np +from osgeo import gdal +class NotOverlapError(Exception): + """图像重叠度不足异常""" + pass + +class DockerNotRunError(Exception): + """Docker未启动异常""" + pass + +class DockerShareError(Exception): + """Docker目录共享异常""" + pass + class ODMProcessMonitor: """ODM处理监控器""" @@ -14,11 +28,76 @@ class ODMProcessMonitor: self.mode = mode def _check_success(self, grid_dir: str) -> bool: - """检查ODM是否执行成功""" - success_markers = ['odm_orthophoto', 'odm_georeferencing'] + """检查ODM是否执行成功 + + 检查项目: + 1. 必要的文件夹是否存在 + 2. 正射影像是否生成且有效 + 3. 正射影像文件大小是否正常 + """ + # 检查必要文件夹 + success_markers = ['odm_orthophoto'] if self.mode != "快拼模式": - success_markers.append('odm_texturing') - return all(os.path.exists(os.path.join(grid_dir, 'project', marker)) for marker in success_markers) + success_markers.extend(['odm_texturing', 'odm_georeferencing']) + + if not all(os.path.exists(os.path.join(grid_dir, 'project', marker)) for marker in success_markers): + self.logger.error("必要的文件夹未生成") + return False + + # 检查正射影像文件 + ortho_path = os.path.join(grid_dir, 'project', 'odm_orthophoto', 'odm_orthophoto.original.tif') + if not os.path.exists(ortho_path): + self.logger.error("正射影像文件未生成") + return False + + # 检查文件大小 + file_size_mb = os.path.getsize(ortho_path) / (1024 * 1024) # 转换为MB + if file_size_mb < 1: + self.logger.error(f"正射影像文件过小: {file_size_mb:.2f}MB") + return False + + try: + # 打开影像文件 + ds = gdal.Open(ortho_path) + if ds is None: + self.logger.error("无法打开正射影像文件") + return False + + # 读取第一个波段 + band = ds.GetRasterBand(1) + + # 获取统计信息 + stats = band.GetStatistics(False, True) + if stats is None: + self.logger.error("无法获取影像统计信息") + return False + + min_val, max_val, mean, std = stats + + # 计算空值比例 + no_data_value = band.GetNoDataValue() + array = band.ReadAsArray() + if no_data_value is not None: + no_data_ratio = np.sum(array == no_data_value) / array.size + else: + no_data_ratio = 0 + + # 检查空值比例是否过高（超过50%） + if no_data_ratio > 0.5: + self.logger.error(f"正射影像空值比例过高: {no_data_ratio:.2%}") + return False + + # 检查影像是否全黑或全白 + if max_val - min_val < 1: + self.logger.error("正射影像可能无效：像素值范围过小") + return False + + ds = None # 关闭数据集 + return True + + except Exception as e: + self.logger.error(f"检查正射影像时发生错误: {str(e)}") + return False def run_odm_with_monitor(self, grid_dir: str, grid_id: tuple, fast_mode: bool = True, produce_dem: bool = False) -> Tuple[bool, str]: """运行ODM命令""" @@ -27,63 +106,151 @@ class ODMProcessMonitor: return False, "快拼模式下无法生成DEM，请调整生产参数" self.logger.info(f"开始处理网格 ({grid_id[0]},{grid_id[1]})") + max_retries = 3 + current_try = 0 + use_lowest_quality = True # 初始使用lowest quality - # 构建Docker命令 - grid_dir = grid_dir[0].lower()+grid_dir[1:].replace('\\', '/') - docker_command = ( - f"docker run --gpus all -ti --rm " - f"-v {grid_dir}:/datasets " - f"opendronemap/odm:gpu " - f"--project-path /datasets project " - f"--max-concurrency 15 " - f"--force-gps " - f"--feature-quality lowest " - f"--orthophoto-resolution 10 " - ) + 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]})") - if produce_dem: - docker_command += ( - f"--dsm " - f"--dtm " - ) + try: + # 构建Docker命令 + grid_dir = grid_dir[0].lower()+grid_dir[1:].replace('\\', '/') + docker_command = ( + f"docker run --gpus all -ti --rm " + f"-v {grid_dir}:/datasets " + f"opendronemap/odm:gpu " + f"--project-path /datasets project " + f"--max-concurrency 15 " + f"--force-gps " + ) - if fast_mode: - docker_command += ( - f"--fast-orthophoto " - f"--skip-3dmodel " - ) + # 根据是否使用lowest quality添加参数 + if use_lowest_quality: + docker_command += f"--feature-quality lowest " - docker_command += "--rerun-all" - self.logger.info(docker_command) - result = subprocess.run( - docker_command, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE) - stdout, stderr = result.stdout.decode( - 'utf-8'), result.stderr.decode('utf-8') + docker_command += f"--orthophoto-resolution 10 " - self.logger.info(f"==========stdout==========: {stdout}") - self.logger.error(f"==========stderr==========: {stderr}") - # 检查执行结果 - if self._check_success(grid_dir): - self.logger.info(f"网格 ({grid_id[0]},{grid_id[1]}) 处理成功") - return True, "" - else: - self.logger.error(f"网格 ({grid_id[0]},{grid_id[1]}) 处理失败") - return False, f"网格 ({grid_id[0]},{grid_id[1]}) 处理失败" + if produce_dem: + docker_command += ( + f"--dsm " + f"--dtm " + ) - def process_all_grids(self, grid_points: Dict[tuple, pd.DataFrame], produce_dem: bool): - """处理所有网格""" + if fast_mode: + docker_command += ( + f"--fast-orthophoto " + f"--skip-3dmodel " + ) + + docker_command += "--rerun-all" + self.logger.info(docker_command) + + result = subprocess.run( + docker_command, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE) + stdout, stderr = result.stdout.decode( + 'utf-8'), result.stderr.decode('utf-8') + + self.logger.error(f"==========stderr==========: {stderr}") + + # 检查是否有错误 + stdout_lines = stdout.strip().split('\n') + last_lines = stdout_lines[-10:] if len(stdout_lines) > 10 else stdout_lines + + # 检查Docker是否未运行 + if any("docker not run" in line.lower() for line in last_lines) or \ + any("docker daemon" in line.lower() for line in last_lines) or \ + any("cannot connect to the docker daemon" in line.lower() for line in last_lines): + raise DockerNotRunError("Docker服务未启动") + + # 检查目录共享问题 + if any("not share" in line.lower() for line in last_lines) or \ + any("permission denied" in line.lower() for line in last_lines) or \ + any("access is denied" in line.lower() for line in last_lines): + raise DockerShareError("Docker无法访问目录") + + # 检查是否有重叠度不足错误 + if any("not overlap" in line.lower() for line in last_lines): + raise NotOverlapError("检测到图像重叠度不足错误") + + # 检查执行结果 + if self._check_success(grid_dir): + self.logger.info(f"网格 ({grid_id[0]},{grid_id[1]}) 处理成功") + return True, "" + + if current_try < max_retries: + self.logger.warning(f"网格处理失败，准备第 {current_try + 1} 次重试") + else: + self.logger.error(f"网格 ({grid_id[0]},{grid_id[1]}) 处理失败，已达到最大重试次数") + return False, f"网格 ({grid_id[0]},{grid_id[1]}) 处理失败，已重试{max_retries}次" + + except NotOverlapError: + if use_lowest_quality: + self.logger.warning("检测到'not overlap'错误，移除lowest quality参数后重试") + use_lowest_quality = False + continue + else: + self.logger.error("即使移除lowest quality参数后仍然出现'not overlap'错误") + return False, "图像重叠度不足" + + except DockerNotRunError: + self.logger.error("Docker服务未启动") + return False, "Docker没有启动，请启动Docker" + + except DockerShareError: + self.logger.error("Docker无法访问目录") + return False, "Docker无法访问数据目录或输出目录，请检查目录权限和共享设置" + + return False, f"网格 ({grid_id[0]},{grid_id[1]}) 处理失败" + + def process_all_grids(self, grid_points: Dict[tuple, pd.DataFrame], produce_dem: bool) -> Dict[tuple, pd.DataFrame]: + """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") - for grid_id in grid_points.keys(): + successful_grid_points = {} + 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]}' ) - success, error_msg = self.run_odm_with_monitor( - grid_dir=grid_dir, - grid_id=grid_id, - fast_mode=(self.mode == "快拼模式"), - produce_dem=produce_dem - ) + try: + success, error_msg = self.run_odm_with_monitor( + grid_dir=grid_dir, + grid_id=grid_id, + fast_mode=(self.mode == "快拼模式"), + produce_dem=produce_dem + ) - if not success: - raise Exception(f"网格 ({grid_id[0]},{grid_id[1]}) 处理失败: {error_msg}") + if success: + successful_grid_points[grid_id] = points + 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_points) + + 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_points) == 0: + raise Exception("所有网格处理都失败，无法继续处理") + + + return successful_grid_points