along/UAV
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

小修bug

Browse Source
This commit is contained in:
龙澳 2025-01-02 20:11:47 +08:00
parent 076282780f
commit 38db33b2c0
5 changed files with 195 additions and 77 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

16
odm_preprocess.py
View File

@ -46,6 +46,7 @@ class PreprocessConfig:
grid_size: float = 500
# 几个pipline过程是否开启
mode: str = "快拼模式"
produce_dem: bool = False
class ImagePreprocessor:
@ -237,11 +238,11 @@ class ImagePreprocessor:
shutil.copy(src, dst)
self.logger.info(f"网格 ({grid_id[0]},{grid_id[1]}) 包含 {len(points)} 张图像")
def merge_tif(self, grid_points: Dict[tuple, pd.DataFrame]):
def merge_tif(self, grid_points: Dict[tuple, pd.DataFrame], produce_dem: bool):
"""合并所有网格的影像产品"""
self.logger.info("开始合并所有影像产品")
merger = MergeTif(self.config.output_dir)
merger.merge_all_tifs(grid_points)
merger.merge_all_tifs(grid_points, produce_dem)
def merge_ply(self, grid_points: Dict[tuple, pd.DataFrame]):
"""合并所有网格的PLY点云"""
@ -266,8 +267,8 @@ 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.merge_tif(grid_points)
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)
except Exception as e:
@ -278,8 +279,8 @@ class ImagePreprocessor:
if __name__ == "__main__":
# 创建配置
config = PreprocessConfig(
image_dir=r"E:\datasets\UAV\1815\project\images",
output_dir=r"G:\ODM_output\1815",
image_dir=r"E:\datasets\UAV\283\project\images",
output_dir=r"G:\ODM_output\283",
cluster_eps=0.01,
cluster_min_samples=5,
@ -295,11 +296,12 @@ if __name__ == "__main__":
filter_dense_distance_threshold=10,
filter_time_threshold=timedelta(minutes=5),
grid_size=500,
grid_size=400,
grid_overlap=0.1,
mode="重建模式",
produce_dem=False,
)
# 创建处理器并执行

59
post_pro/merge_obj.py
View File

@ -4,6 +4,7 @@ import numpy as np
from typing import Dict
import pandas as pd
import shutil
import time
class MergeObj:
@ -124,8 +125,23 @@ class MergeObj:
materials2 = self.read_mtl(mtl2_path)
# 创建材质名称映射（使用与MTL文件相同的命名格式）
material_map1 = {old_name: f"material_{grid_id1[0]}_{grid_id1[1]}_{old_name}" for old_name in materials1.keys()}
material_map2 = {old_name: f"material_{grid_id2[0]}_{grid_id2[1]}_{old_name}" for old_name in materials2.keys()}
material_map1 = {}
material_map2 = {}
# 处理第一个模型的材质映射
for old_name in materials1.keys():
# 如果材质名称已经包含了网格ID前缀，就不再添加
if old_name.startswith(f"material_{grid_id1[0]}_{grid_id1[1]}_"):
material_map1[old_name] = old_name
else:
material_map1[old_name] = f"material_{grid_id1[0]}_{grid_id1[1]}_{old_name}"
# 处理第二个模型的材质映射
for old_name in materials2.keys():
if old_name.startswith(f"material_{grid_id2[0]}_{grid_id2[1]}_"):
material_map2[old_name] = old_name
else:
material_map2[old_name] = f"material_{grid_id2[0]}_{grid_id2[1]}_{old_name}"
# 平移第二个模型的顶点
vertices2_translated = self.translate_vertices(vertices2, translation)
@ -315,24 +331,51 @@ class MergeObj:
# 合并OBJ文件
reference_id = list(grid_files.keys())[0]
merged_obj = grid_files[reference_id]['obj']
temp_files = [] # 记录所有中间文件
for grid_id, files in list(grid_files.items())[1:]:
translation = translations[grid_id]
translation = (translation[0], translation[1], 0)
output_obj = os.path.join(
# 生成临时输出文件名
temp_output = os.path.join(
output_model_dir,
f"merged_model_{reference_id[0]}_{reference_id[1]}_{grid_id[0]}_{grid_id[1]}.obj"
f"temp_merged_{int(time.time())}.obj"
)
temp_files.append(temp_output) # 添加到临时文件列表
self.merge_two_objs(merged_obj, files['obj'], output_obj, translation, reference_id, grid_id)
merged_obj = output_obj
self.merge_two_objs(merged_obj, files['obj'], temp_output, translation, reference_id, grid_id)
# 如果上一个merged_obj是临时文件，则删除它
if merged_obj != grid_files[reference_id]['obj'] and os.path.exists(merged_obj):
try:
os.remove(merged_obj)
except Exception as e:
self.logger.warning(f"删除临时文件失败: {merged_obj}, 错误: {str(e)}")
merged_obj = temp_output
# 最终结果
final_obj = os.path.join(output_model_dir, "merged_model.obj")
if os.path.exists(merged_obj) and merged_obj != final_obj:
try:
if os.path.exists(final_obj):
os.remove(final_obj)
os.rename(merged_obj, final_obj)
except Exception as e:
self.logger.warning(f"重命名最终文件失败: {str(e)}")
shutil.copy2(merged_obj, final_obj)
os.remove(merged_obj)
try:
os.remove(merged_obj)
except:
pass
# 清理所有临时文件
for temp_file in temp_files:
if os.path.exists(temp_file):
try:
os.remove(temp_file)
except Exception as e:
self.logger.warning(f"删除临时文件失败: {temp_file}, 错误: {str(e)}")
self.logger.info(
f"模型合并完成，输出目录: {output_model_dir}\n"

174
post_pro/merge_tif.py
View File

@ -3,6 +3,8 @@ import logging
import os
from typing import Dict
import pandas as pd
import time
import shutil
class MergeTif:
@ -25,49 +27,72 @@ class MergeTif:
raise FileNotFoundError(error_msg)
# 打开影像，检查投影是否一致
datasets = [gdal.Open(tif) for tif in [input_tif1, input_tif2]]
if None in datasets:
error_msg = "无法打开输入影像文件"
self.logger.error(error_msg)
raise ValueError(error_msg)
datasets = []
try:
for tif in [input_tif1, input_tif2]:
ds = gdal.Open(tif)
if ds is None:
error_msg = f"无法打开影像文件: {tif}"
self.logger.error(error_msg)
raise ValueError(error_msg)
datasets.append(ds)
projections = [dataset.GetProjection() for dataset in datasets]
self.logger.debug(f"影像1投影: {projections[0]}")
self.logger.debug(f"影像2投影: {projections[1]}")
projections = [ds.GetProjection() for ds in datasets]
self.logger.debug(f"影像1投影: {projections[0]}")
self.logger.debug(f"影像2投影: {projections[1]}")
# 检查投影是否一致
if len(set(projections)) != 1:
error_msg = "影像的投影不一致，请先进行重投影！"
self.logger.error(error_msg)
raise ValueError(error_msg)
# 检查投影是否一致
if len(set(projections)) != 1:
error_msg = "影像的投影不一致，请先进行重投影！"
self.logger.error(error_msg)
raise ValueError(error_msg)
# 创建 GDAL Warp 选项
warp_options = gdal.WarpOptions(
format="GTiff",
resampleAlg="average",
srcNodata=0,
dstNodata=0,
multithread=True
)
# 如果输出文件已存在，先删除
if os.path.exists(output_tif):
try:
os.remove(output_tif)
except Exception as e:
self.logger.warning(f"删除已存在的输出文件失败: {str(e)}")
# 生成一个新的输出文件名
base, ext = os.path.splitext(output_tif)
output_tif = f"{base}_{int(time.time())}{ext}"
self.logger.info(f"使用新的输出文件名: {output_tif}")
self.logger.info("开始执行影像拼接...")
result = gdal.Warp(
output_tif, [input_tif1, input_tif2], options=warp_options)
# 创建 GDAL Warp 选项
warp_options = gdal.WarpOptions(
format="GTiff",
resampleAlg="average",
srcNodata=0,
dstNodata=0,
multithread=True
)
if result is None:
error_msg = "影像拼接失败"
self.logger.error(error_msg)
raise RuntimeError(error_msg)
self.logger.info("开始执行影像拼接...")
result = gdal.Warp(output_tif, datasets, options=warp_options)
# 获取输出影像的基本信息
output_dataset = gdal.Open(output_tif)
if output_dataset:
width = output_dataset.RasterXSize
height = output_dataset.RasterYSize
bands = output_dataset.RasterCount
self.logger.info(f"拼接完成，输出影像大小: {width}x{height}，波段数: {bands}")
if result is None:
error_msg = "影像拼接失败"
self.logger.error(error_msg)
raise RuntimeError(error_msg)
self.logger.info(f"影像拼接成功，输出文件保存至: {output_tif}")
# 获取输出影像的基本信息
output_dataset = gdal.Open(output_tif)
if output_dataset:
width = output_dataset.RasterXSize
height = output_dataset.RasterYSize
bands = output_dataset.RasterCount
self.logger.info(
f"拼接完成，输出影像大小: {width}x{height}，波段数: {bands}")
output_dataset = None # 显式关闭数据集
self.logger.info(f"影像拼接成功，输出文件保存至: {output_tif}")
finally:
# 确保所有数据集都被正确关闭
for ds in datasets:
if ds:
ds = None
result = None
except Exception as e:
self.logger.error(f"影像拼接过程中发生错误: {str(e)}", exc_info=True)
@ -108,25 +133,58 @@ class MergeTif:
self.logger.info(f"设置第一个输入{product_name}: {input_tif1}")
else:
input_tif2 = grid_tif
output_tif = os.path.join(
self.output_dir, f"merged_{product_info['output']}")
# 生成带时间戳的临时输出文件名
temp_output = os.path.join(
self.output_dir,
f"temp_merged_{int(time.time())}_{product_info['output']}"
)
self.logger.info(
f"开始合并{product_name}第 {merge_count + 1} 次:\n"
f"输入1: {input_tif1}\n"
f"输入2: {input_tif2}\n"
f"输出: {output_tif}"
f"输出: {temp_output}"
)
self.merge_two_tifs(input_tif1, input_tif2, output_tif)
self.merge_two_tifs(input_tif1, input_tif2, temp_output)
merge_count += 1
input_tif1 = output_tif
# 如果之前的输入文件是临时文件，则删除它
if 'temp_merged_' in input_tif1:
try:
os.remove(input_tif1)
except Exception as e:
self.logger.warning(f"删除临时文件失败: {str(e)}")
input_tif1 = temp_output
input_tif2 = None
# 重命名最终的临时文件为目标文件名
final_output = os.path.join(
self.output_dir, product_info['output'])
if os.path.exists(final_output):
try:
os.remove(final_output)
except Exception as e:
self.logger.warning(f"删除已存在的最终输出文件失败: {str(e)}")
final_output = os.path.join(
self.output_dir,
f"merged_{int(time.time())}_{product_info['output']}"
)
try:
os.rename(input_tif1, final_output)
except Exception as e:
self.logger.warning(f"重命名最终文件失败: {str(e)}")
shutil.copy2(input_tif1, final_output)
try:
os.remove(input_tif1)
except:
pass
self.logger.info(
f"{product_name}合并完成，共执行 {merge_count} 次合并，"
f"最终输出文件: {input_tif1}"
f"最终输出文件: {final_output}"
)
except Exception as e:
@ -134,7 +192,7 @@ class MergeTif:
f"{product_name}合并过程中发生错误: {str(e)}", exc_info=True)
raise
def merge_all_tifs(self, grid_points: Dict[tuple, pd.DataFrame]):
def merge_all_tifs(self, grid_points: Dict[tuple, pd.DataFrame], produce_dem: bool):
"""合并所有产品（正射影像、DSM和DTM）"""
try:
products = [
@ -144,19 +202,23 @@ class MergeTif:
'filename': 'odm_orthophoto.original.tif',
'output': 'orthophoto.tif'
},
{
'name': 'DSM',
'path': 'odm_dem',
'filename': 'dsm.original.tif',
'output': 'dsm.tif'
},
{
'name': 'DTM',
'path': 'odm_dem',
'filename': 'dtm.original.tif',
'output': 'dtm.tif'
}
]
if produce_dem:
products.append(
{
'name': 'DSM',
'path': 'odm_dem',
'filename': 'dsm.original.tif',
'output': 'dsm.tif'
},
{
'name': 'DTM',
'path': 'odm_dem',
'filename': 'dtm.original.tif',
'output': 'dtm.tif'
}
)
for product in products:
self.merge_grid_tif(grid_points, product)
@ -173,7 +235,7 @@ if __name__ == "__main__":
os.path.dirname(os.path.abspath(__file__))))
from utils.logger import setup_logger
import pandas as pd
# 设置输出目录和日志
output_dir = r"G:\ODM_output\1009"
setup_logger(output_dir)

6
utils/grid_divider.py
View File

@ -149,9 +149,9 @@ class GridDivider:
plt.text(center_lon, center_lat, f"({i},{j})", # 显示(i,j)
horizontalalignment='center', verticalalignment='center')
plt.title('网格划分与GPS点分布图')
plt.xlabel('经度')
plt.ylabel('纬度')
plt.title('Grid Division and GPS Point Distribution')
plt.xlabel('Longitude')
plt.ylabel('Latitude')
plt.legend()
plt.grid(True)

17
utils/odm_monitor.py
View File

@ -20,8 +20,12 @@ class ODMProcessMonitor:
success_markers.append('odm_texturing')
return all(os.path.exists(os.path.join(grid_dir, 'project', marker)) for marker in success_markers)
def run_odm_with_monitor(self, grid_dir: str, grid_id: tuple, fast_mode: bool = True) -> Tuple[bool, str]:
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"""
if produce_dem and fast_mode:
self.logger.error("快拼模式下无法生成DEM，请调整生产参数")
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]})")
# 构建Docker命令
@ -37,6 +41,12 @@ class ODMProcessMonitor:
f"--orthophoto-resolution 10 "
)
if produce_dem:
docker_command += (
f"--dsm "
f"--dtm "
)
if fast_mode:
docker_command += (
f"--fast-orthophoto "
@ -60,7 +70,7 @@ class ODMProcessMonitor:
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"
def process_all_grids(self, grid_points: Dict[tuple, pd.DataFrame]):
def process_all_grids(self, grid_points: Dict[tuple, pd.DataFrame], produce_dem: bool):
"""处理所有网格"""
self.logger.info("开始执行网格处理")
for grid_id in grid_points.keys():
@ -71,7 +81,8 @@ class ODMProcessMonitor:
success, error_msg = self.run_odm_with_monitor(
grid_dir=grid_dir,
grid_id=grid_id,
fast_mode=(self.mode == "快拼模式")
fast_mode=(self.mode == "快拼模式"),
produce_dem=produce_dem
)
if not success: