灾害数据输出：综合明细表.xlsx

predict/predict_yolo11seg.py

@@ -899,7 +899,8 @@ def predict_images_share_dir(task_id, pt_name, zip_url, user_name, pwd, output_d
     found_paths = scanner.find_folders_by_name(
         share_path=config['share'],
         folder_name='图像类',
-        start_dir=config['dir']
+        start_dir=config['dir'],
+        max_depth=2
     )
 
     target_path = ""    # 识别图片目录
@@ -911,7 +912,8 @@ def predict_images_share_dir(task_id, pt_name, zip_url, user_name, pwd, output_d
         found_paths = scanner.find_folders_by_name(
             share_path=config['share'],
             folder_name='Images',
-            start_dir=tmpConfig['dir']
+            start_dir=tmpConfig['dir'],
+            max_depth=3
         )
         if len(found_paths) > 0:
             target_path = found_paths[0]

util/smb.py

@@ -758,7 +758,8 @@ def get_road_dict(dir,user_name,pwd) :
     found_paths = scanner.find_files_by_name(
             share_path=config['share'],
             file_name='每公里指标明细表*.xls',
-            start_dir=config['dir']
+            start_dir=config['dir'],
+            max_depth=1
         )
     print(f"\n找到 {len(found_paths)} 个 'fileindex.txt' 文件:")
     for i, path in enumerate(found_paths, 1):
@@ -789,7 +790,8 @@ def get_pile_dict(dir,user_name,pwd) :
     found_paths = scanner.find_files_by_name(
             share_path=config['share'],
             file_name='fileindex.txt',
-            start_dir=config['dir']
+            start_dir=config['dir'],
+            max_depth=8
         )
     print(f"\n找到 {len(found_paths)} 个 'fileindex.txt' 文件:")
     for i, path in enumerate(found_paths, 1):

util/yolo2pix_new.py

@@ -6,6 +6,9 @@ import numpy as np
 from collections import defaultdict
 import smb
 import pandas as pd
+from openpyxl import Workbook
+from openpyxl.styles import Font, Alignment
+from openpyxl.utils import get_column_letter
 import glob
 from datetime import datetime
 
@@ -169,7 +172,8 @@ def yoloseg_to_grid_share_dir(road_dict,pile_dict,image_path,label_file,cover_ra
 
             cname = class_names[cls_id] if cls_id<len(class_names) else str(cls_id)
             ids_str = '-'.join(map(str,sorted(covered_cells)))+'-'
-            result_lines.append(f"{cname}   {f"桩号:K000{pile_no}"}   {ROAD_TYPE_EN_TO_CN.get(road_type, 'xx')}   {ids_str}")
+            pile_no_tmp = f"桩号:K000{pile_no}"
+            result_lines.append(f"{cname} {pile_no_tmp} {ROAD_TYPE_EN_TO_CN.get(road_type, 'xx')} {ids_str}")
             if cname not in all_class_cells: all_class_cells[cname]=set()
             cell_info.append(covered_cells)
             cell_info.append([max_x - min_x, max_y - min_y])
@@ -272,7 +276,164 @@ def in_interval(increment, cur_pile_no, tmp_start, tmp_end) :
             return True
         else :
             return False
+        
+# 指定间隔区间，输出基本信息+灾害数据
+def process_info(road_dict,pile_dict,summary_data,image_path,current_time,interval=10,dir="output",cell_area=CELL_AREA,grid_width=GRID_WIDTH,grid_height=GRID_HEIGHT) :
+    process_info_data = []
+    if summary_data:
+        img_file_name = os.path.basename(image_path)
+        road_data = get_road_info(road_dict, pile_dict, img_file_name)
+        identify_width = road_data.get('识别宽度（米）', '3.6')
+        up_or_down = road_data.get('方向(上行/下行)', '上行')
+        road_code = pile_dict.get(img_file_name)[0]
+        road_level = road_data.get('技术等级', '')
+        road_type_cn = road_data.get('路面类型（沥青/水泥/砂石）', '沥青')
 
+        group_list = summary_data
+        increment = float(0.001 * interval)
+        pile_no_start = float(0.000)
+        pile_no_end = float(0.000) + increment
+        # 上行/下行
+        if up_or_down == '下行' :
+            group_list = list(summary_data)[::-1]
+            increment = float(-0.001 * interval)
+            tmp_pile_no = convert_special_format(group_list[len(group_list)-1][1])
+            pile_no_start = tmp_pile_no
+            if tmp_pile_no % increment != 0 :
+                pile_no_end = tmp_pile_no + (tmp_pile_no % increment)
+            else :
+                pile_no_end = tmp_pile_no + increment
+
+        
+        index = 0
+        tmp_start = pile_no_start
+        tmp_end = pile_no_end
+        while True :
+            # 每10m一个区间，在区间内进行灾害计算
+            pile_no, DR, counts, road_type = group_list[index]
+            cur_pile_no = convert_special_format(pile_no)
+            pile_no_s = f"{tmp_start:0.3f}"
+            pile_no_e = f"{tmp_end:0.3f}"
+            up_or_down_code = "B" if up_or_down == '下行' else "A"
+            if not in_interval(increment, cur_pile_no, tmp_start, tmp_end) :
+                # 没在刻度内直接输出无病害数据
+                row = [road_code, pile_no_s,pile_no_e,up_or_down_code,up_or_down,road_level,f"{road_type_cn}路面",'','',f"{0:.2f}",'','','','','','','','','','','','','','','']
+                if road_type=="asphalt":
+                    keys = list(CLASS_MAP_ASPHALT.keys())
+                elif road_type=="cement":
+                    keys = list(CLASS_MAP_CEMENT.keys())
+                else:
+                    keys = list(CLASS_MAP_GRAVEL.keys())
+                # for k in keys:
+                #     row.append(f"{0:.2f}")
+                process_info_data.append(row)
+                # f.write(','.join(row)+'\n')
+            else :
+                row = [road_code, pile_no_s,pile_no_e,up_or_down_code,up_or_down,road_level,f"{road_type_cn}路面",'','']
+                subRows = []
+                while index < len(group_list):
+                    pile_no, DR, counts, road_type = group_list[index]
+                    cur_pile_no = convert_special_format(pile_no)
+                    
+                    tmp_row = []
+                    if in_interval(increment, cur_pile_no, tmp_start, tmp_end) :
+                        pile_no = f"{tmp_start:0.3f}"
+                        tmp_row = [DR]
+                        if road_type=="asphalt":
+                            keys = list(CLASS_MAP_ASPHALT.keys())
+                        elif road_type=="cement":
+                            keys = list(CLASS_MAP_CEMENT.keys())
+                        else:
+                            keys = list(CLASS_MAP_GRAVEL.keys())
+                        # for k in keys:
+                        #     tmp_row.append(counts.get(k, [0,0,0])[0])
+                        subRows.append(tmp_row)
+                        index = index + 1
+                    else :
+                        break
+                
+                # 同列汇总 10m一个区间--对应5张图
+                column_sums = [f"{(sum(column)/(interval / 2)):0.2f}" for column in zip(*subRows)]
+                row += column_sums
+                # f.write(','.join(row)+'\n')
+                row += ['','','','','','','','','','','','','','','']
+                process_info_data.append(row)
+
+            tmp_start = tmp_end
+            tmp_end = tmp_start + increment
+
+            print(f"tmp_start={tmp_start}, tmp_end={tmp_end}, index={index}, len(group_list)={len(group_list)}")
+            if index >= len(group_list) :
+                break
+    return process_info_data
+
+def adjust_column_width(worksheet):
+    """
+    调整列宽函数
+    """
+    for col_idx in range(1, worksheet.max_column + 1):
+        max_length = 0
+        column_letter = get_column_letter(col_idx)
+        
+        for row_idx in range(1, worksheet.max_row + 1):
+            try:
+                cell = worksheet.cell(row=row_idx, column=col_idx)
+                # 检查单元格是否在合并单元格范围内
+                if any(cell.coordinate in merged_range for merged_range in worksheet.merged_cells.ranges):
+                    continue  # 跳过合并单元格
+                
+                if cell.value is not None:
+                    cell_length = len(str(cell.value))
+                    if cell_length > max_length:
+                        max_length = cell_length
+            except:
+                continue
+        
+        if max_length > 0:
+            worksheet.column_dimensions[column_letter].width = max_length + 2
+
+def create_multiple_sheets_with_multiple_headers(file_path, excel_data):
+    # 创建工作簿
+    wb = Workbook()
+    
+    # 删除默认创建的sheet
+    wb.remove(wb.active)
+    
+    for sheet_data in excel_data:
+        # 创建工作表
+        ws = wb.create_sheet(title=sheet_data['name'])
+        
+        # 设置多表头
+        current_row = 1
+        
+        # 多级表头
+        for heads in sheet_data['headers'] :
+            for head in heads :
+                ws.merge_cells(f'{head[1]}{current_row}:{head[2]}{current_row}')
+                ws[f'{head[1]}{current_row}'] = head[0]
+                ws[f'{head[1]}{current_row}'].font = Font(bold=True, size=14)
+                ws[f'{head[1]}{current_row}'].alignment = Alignment(horizontal='center')
+                current_row += 1
+        
+        # 列标题
+        for col_idx, column_name in enumerate(sheet_data['columns'], 1):
+            cell = ws.cell(row=current_row, column=col_idx, value=column_name)
+            cell.font = Font(bold=True)
+        
+        current_row += 1
+        
+        # 写入数据
+        for row_data in sheet_data['data']:
+            for col_idx, value in enumerate(row_data, 1):
+                ws.cell(row=current_row, column=col_idx, value=value)
+            current_row += 1
+        
+        # 自动调整列宽
+        adjust_column_width(ws)
+    
+    # 保存文件
+    wb.save(file_path)
+    print(f"文件已保存为 {file_path}")
 
 # ---------------- 主函数-共享目录 ----------------
 def process_dir(road_dict,pile_dict,dir="output",cell_area=CELL_AREA,grid_width=GRID_WIDTH,grid_height=GRID_HEIGHT):
@@ -367,7 +528,7 @@ def process_dir(road_dict,pile_dict,dir="output",cell_area=CELL_AREA,grid_width=
             if up_or_down == '下行' :
                 group_list = list(group)[::-1]
                 increment = float(-0.010)
-                tmp_pile_no = convert_special_format(group[len(group)-1][1])
+                tmp_pile_no = convert_special_format(group_list[len(group_list)-1][1])
                 pile_no_start = tmp_pile_no
                 if tmp_pile_no % increment != 0 :
                     pile_no_end = tmp_pile_no + (tmp_pile_no % increment)
@@ -381,7 +542,7 @@ def process_dir(road_dict,pile_dict,dir="output",cell_area=CELL_AREA,grid_width=
                 tmp_end = pile_no_end
                 while True :
                     # 每10m一个区间，在区间内进行灾害计算
-                    pile_no, DR, counts, road_type = summary_data[index]
+                    pile_no, DR, counts, road_type = group_list[index]
                     cur_pile_no = convert_special_format(pile_no)
                     if not in_interval(increment, cur_pile_no, tmp_start, tmp_end) :
                         # 没在刻度内直接输出无病害数据
@@ -400,7 +561,7 @@ def process_dir(road_dict,pile_dict,dir="output",cell_area=CELL_AREA,grid_width=
                         row = [f"{tmp_start:0.3f}", identify_width]
                         subRows = []
                         while index < len(group_list):
-                            pile_no, DR, counts, road_type = summary_data[index]
+                            pile_no, DR, counts, road_type = group_list[index]
                             cur_pile_no = convert_special_format(pile_no)
                             
                             tmp_row = []
@@ -452,7 +613,37 @@ def process_dir(road_dict,pile_dict,dir="output",cell_area=CELL_AREA,grid_width=
                 data_list.append(excel_data)
 
     all_data = [headers] + data_list
-    smb.write_to_excel_pandas(all_data, img_file_path + '/病害明显列表.xlsx')
+    smb.write_to_excel_pandas(all_data, img_file_path + '/病害明细列表.xlsx')
+
+    # 综合明细表.xlsx
+    heads = ['路线编码','起点','终点','车道编码','上下行','公路等级','路面类型','PQI','PQI等级','DR(%)','PCI','PCI等级','IRI','RQI','RQI等级','RD','RDI','RDI等级','SMTD','PBI','PBI等级','WR','PWI','PWI等级','备注']
+    data1 = process_info(road_dict,pile_dict,summary_data,image_path,current_time,10)
+    data2 = process_info(road_dict,pile_dict,summary_data,image_path,current_time,100)
+    data3 = process_info(road_dict,pile_dict,summary_data,image_path,current_time,1000)
+
+    excel_data = [
+        {
+            'name': '综合明细十米',
+            'headers': [[['综合明细十米','A','Y']]],
+            'columns': heads,
+            'data': data1
+        },
+        {
+            'name': '综合明细百米',
+            'headers': [[['综合明细百米','A','Y']]],
+            'columns': heads,
+            'data': data2
+        },
+        {
+            'name': '综合明细千米',
+            'headers': [[['综合明细千米','A','Y']]],
+            'columns': heads,
+            'data': data3
+        }
+    ]
+    create_multiple_sheets_with_multiple_headers(img_file_path + '/综合明细表.xlsx', excel_data)
+
+
 
 # ---------------- 主函数 ----------------
 def process_zip(zip_path,pile_map_file,output_dir="output",cell_area=CELL_AREA,grid_width=GRID_WIDTH,grid_height=GRID_HEIGHT):