91d0262300
- 完成多版本测试（22.2, 23.6, 24.12, 25.3） - 发现API设计问题：无法访问CAD特定功能 - 提供5个解决方案，推荐使用ezdxf替代方案 - 创建完整的测试脚本和分析报告 - 包含详细的README文档
447 lines
18 KiB
Python
447 lines
18 KiB
Python
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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正确的DWG线条提取脚本
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基于调试结果，使用正确的API提取线条数据
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"""
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import os
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import sys
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import csv
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import json
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from pathlib import Path
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import math
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def print_separator(title=""):
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"""打印分隔线"""
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print("=" * 60)
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if title:
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print(f" {title} ")
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print("=" * 60)
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def extract_lines_correctly(dwg_path):
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"""正确提取DWG文件中的线条"""
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print_separator("正确提取DWG文件中的线条")
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if not os.path.exists(dwg_path):
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print(f"文件不存在: {dwg_path}")
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return None
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try:
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import aspose.cad as cad
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from aspose.cad.fileformats.cad import CadImage
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from aspose.cad.fileformats.cad.cadobjects import CadLine
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# 获取文件基本信息
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file_size = os.path.getsize(dwg_path)
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print(f"文件路径: {dwg_path}")
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print(f"文件大小: {file_size:,} 字节 ({file_size/1024/1024:.2f} MB)")
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# 使用CadImage.load加载文件
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print("正在使用CadImage.load加载DWG文件...")
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cad_image = CadImage.load(dwg_path)
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print(f"成功加载DWG文件")
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print(f"图像类型: {type(cad_image).__name__}")
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print(f"图像尺寸: {cad_image.width} x {cad_image.height}")
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lines_data = []
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total_lines = 0
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# 方法1：尝试从cad_image的blocks获取
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print("\n方法1：尝试从blocks获取实体")
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try:
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if hasattr(cad_image, 'blocks'):
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blocks = cad_image.blocks
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print(f"找到blocks属性: {type(blocks).__name__}")
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if hasattr(blocks, '__len__'):
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print(f"块数量: {len(blocks)}")
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for block_index, block in enumerate(blocks):
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print(f" 分析块 {block_index}: {type(block).__name__}")
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if hasattr(block, 'entities'):
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block_entities = block.entities
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if hasattr(block_entities, '__len__'):
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print(f" 块中实体数量: {len(block_entities)}")
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for entity_index, entity in enumerate(block_entities):
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entity_type = type(entity).__name__
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print(f" 实体 {entity_index}: {entity_type}")
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if entity_type == 'CadLine':
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line_info = extract_cad_line_info(entity, total_lines, block_index, entity_index)
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if line_info:
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lines_data.append(line_info)
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total_lines += 1
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else:
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print("cad_image没有blocks属性")
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except Exception as e:
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print(f"从blocks获取实体失败: {e}")
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# 方法2：尝试从cad_image的entities获取
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print("\n方法2：尝试从entities获取实体")
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try:
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if hasattr(cad_image, 'entities'):
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entities = cad_image.entities
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print(f"找到entities属性: {type(entities).__name__}")
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if hasattr(entities, '__len__'):
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print(f"实体数量: {len(entities)}")
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for entity_index, entity in enumerate(entities):
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entity_type = type(entity).__name__
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print(f" 实体 {entity_index}: {entity_type}")
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if entity_type == 'CadLine':
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line_info = extract_cad_line_info(entity, total_lines, -1, entity_index)
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if line_info:
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lines_data.append(line_info)
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total_lines += 1
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else:
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print("cad_image没有entities属性")
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except Exception as e:
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print(f"从entities获取实体失败: {e}")
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# 方法3：尝试从cad_image的layers获取
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print("\n方法3：尝试从layers获取实体")
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try:
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if hasattr(cad_image, 'layers'):
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layers = cad_image.layers
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print(f"找到layers属性: {type(layers).__name__}")
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if hasattr(layers, '__len__'):
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print(f"图层数量: {len(layers)}")
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for layer_index, layer in enumerate(layers):
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print(f" 分析图层 {layer_index}: {type(layer).__name__}")
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if hasattr(layer, 'entities'):
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layer_entities = layer.entities
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if hasattr(layer_entities, '__len__'):
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print(f" 图层中实体数量: {len(layer_entities)}")
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for entity_index, entity in enumerate(layer_entities):
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entity_type = type(entity).__name__
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print(f" 实体 {entity_index}: {entity_type}")
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if entity_type == 'CadLine':
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line_info = extract_cad_line_info(entity, total_lines, layer_index, entity_index)
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if line_info:
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lines_data.append(line_info)
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total_lines += 1
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else:
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print("cad_image没有layers属性")
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except Exception as e:
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print(f"从layers获取实体失败: {e}")
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# 方法4：尝试遍历cad_image的所有属性
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print("\n方法4：遍历cad_image的所有属性")
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try:
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all_attrs = [attr for attr in dir(cad_image) if not attr.startswith('_')]
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print(f"cad_image共有 {len(all_attrs)} 个属性")
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# 查找可能包含实体的属性
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entity_attrs = [attr for attr in all_attrs if 'entit' in attr.lower() or 'object' in attr.lower() or 'item' in attr.lower()]
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print(f"可能的实体属性: {entity_attrs}")
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for attr_name in entity_attrs:
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try:
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attr_value = getattr(cad_image, attr_name)
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if attr_value and hasattr(attr_value, '__len__') and len(attr_value) > 0:
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print(f" 找到属性 {attr_name}: {type(attr_value).__name__} (长度: {len(attr_value)})")
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# 尝试遍历这个属性
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for i, item in enumerate(attr_value):
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item_type = type(item).__name__
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print(f" {attr_name}[{i}]: {item_type}")
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if item_type == 'CadLine':
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line_info = extract_cad_line_info(item, total_lines, -1, i)
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if line_info:
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lines_data.append(line_info)
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total_lines += 1
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if i >= 4: # 只显示前5个
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break
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except Exception as e:
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print(f" 访问属性 {attr_name} 失败: {e}")
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except Exception as e:
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print(f"遍历属性失败: {e}")
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print(f"\n成功提取 {total_lines} 条线条")
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return lines_data
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except Exception as e:
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print(f"提取线条失败: {e}")
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import traceback
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traceback.print_exc()
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return None
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def extract_cad_line_info(entity, line_index, parent_index, entity_index):
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"""提取CadLine实体的详细信息"""
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try:
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line_info = {
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'line_index': line_index,
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'parent_index': parent_index,
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'entity_index': entity_index,
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'entity_type': 'CadLine',
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'layer_name': 'Unknown',
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'color': 'Unknown',
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'line_type': 'Unknown',
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'thickness': 0,
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'visible': True,
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}
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# 尝试获取基本属性
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try:
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if hasattr(entity, 'layer_name'):
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line_info['layer_name'] = str(getattr(entity, 'layer_name', 'Unknown'))
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if hasattr(entity, 'color_name'):
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line_info['color'] = str(getattr(entity, 'color_name', 'Unknown'))
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if hasattr(entity, 'line_type_name'):
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line_info['line_type'] = str(getattr(entity, 'line_type_name', 'Unknown'))
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if hasattr(entity, 'thickness'):
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line_info['thickness'] = float(getattr(entity, 'thickness', 0))
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if hasattr(entity, 'visible'):
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line_info['visible'] = bool(getattr(entity, 'visible', True))
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except Exception as e:
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print(f" 获取基本属性失败: {e}")
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# 尝试获取坐标信息
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try:
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if hasattr(entity, 'first_point'):
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first_point = entity.first_point
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line_info['start_x'] = float(getattr(first_point, 'x', 0))
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line_info['start_y'] = float(getattr(first_point, 'y', 0))
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line_info['start_z'] = float(getattr(first_point, 'z', 0))
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if hasattr(entity, 'second_point'):
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second_point = entity.second_point
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line_info['end_x'] = float(getattr(second_point, 'x', 0))
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line_info['end_y'] = float(getattr(second_point, 'y', 0))
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line_info['end_z'] = float(getattr(second_point, 'z', 0))
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# 计算线条长度
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if 'start_x' in line_info and 'end_x' in line_info:
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dx = line_info['end_x'] - line_info['start_x']
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dy = line_info['end_y'] - line_info['start_y']
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dz = line_info['end_z'] - line_info['start_z']
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length = math.sqrt(dx*dx + dy*dy + dz*dz)
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line_info['length'] = round(length, 4)
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# 计算角度
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if 'start_x' in line_info and 'end_x' in line_info:
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dx = line_info['end_x'] - line_info['start_x']
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dy = line_info['end_y'] - line_info['start_y']
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if dx != 0 or dy != 0:
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angle = math.atan2(dy, dx) * 180 / math.pi
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line_info['angle_degrees'] = round(angle, 2)
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except Exception as e:
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print(f" 获取坐标信息失败: {e}")
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# 尝试获取其他属性
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try:
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if hasattr(entity, 'object_handle'):
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line_info['handle'] = str(getattr(entity, 'object_handle', ''))
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if hasattr(entity, 'id'):
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line_info['id'] = str(getattr(entity, 'id', ''))
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if hasattr(entity, 'length'):
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line_info['cad_length'] = float(getattr(entity, 'length', 0))
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except Exception as e:
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print(f" 获取其他属性失败: {e}")
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return line_info
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except Exception as e:
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print(f"提取线条 {line_index} 信息时出错: {e}")
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return None
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def save_lines_to_csv(lines_data, output_path):
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"""将线条数据保存为CSV文件"""
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if not lines_data:
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print("没有线条数据可保存")
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return False
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try:
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with open(output_path, 'w', newline='', encoding='utf-8-sig') as csvfile:
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# 获取所有可能的字段名
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all_fields = set()
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for line in lines_data:
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all_fields.update(line.keys())
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fieldnames = sorted(list(all_fields))
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writer = csv.DictWriter(csvfile, fieldnames=fieldnames)
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writer.writeheader()
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for line in lines_data:
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# 确保所有字段都有值
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row = {}
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for field in fieldnames:
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row[field] = line.get(field, '')
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writer.writerow(row)
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print(f"线条数据已保存到: {output_path}")
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return True
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except Exception as e:
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print(f"保存CSV文件失败: {e}")
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return False
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def save_lines_to_json(lines_data, output_path):
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"""将线条数据保存为JSON文件"""
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if not lines_data:
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print("没有线条数据可保存")
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return False
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try:
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with open(output_path, 'w', encoding='utf-8') as jsonfile:
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json.dump(lines_data, jsonfile, ensure_ascii=False, indent=2)
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print(f"线条数据已保存到: {output_path}")
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return True
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except Exception as e:
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print(f"保存JSON文件失败: {e}")
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return False
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def create_summary_report(lines_data, output_path):
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"""创建线条统计报告"""
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if not lines_data:
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return False
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try:
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with open(output_path, 'w', encoding='utf-8') as report:
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report.write("DWG文件线条提取报告\n")
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report.write("=" * 50 + "\n\n")
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# 基本统计
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total_lines = len(lines_data)
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report.write(f"总线条数量: {total_lines}\n\n")
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# 按类型统计
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type_count = {}
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layer_count = {}
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color_count = {}
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for line in lines_data:
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# 类型统计
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entity_type = line.get('entity_type', 'Unknown')
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type_count[entity_type] = type_count.get(entity_type, 0) + 1
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# 图层统计
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layer = line.get('layer_name', 'Unknown')
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layer_count[layer] = layer_count.get(layer, 0) + 1
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# 颜色统计
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color = line.get('color', 'Unknown')
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color_count[color] = color_count.get(color, 0) + 1
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# 写入统计信息
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report.write("按类型统计:\n")
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for entity_type, count in sorted(type_count.items()):
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report.write(f" {entity_type}: {count}\n")
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report.write("\n按图层统计:\n")
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for layer, count in sorted(layer_count.items()):
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report.write(f" {layer}: {count}\n")
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report.write("\n按颜色统计:\n")
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for color, count in sorted(color_count.items()):
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report.write(f" {color}: {count}\n")
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# 长度统计
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lengths = [line.get('length', 0) for line in lines_data if 'length' in line and line['length'] > 0]
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if lengths:
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report.write(f"\n长度统计:\n")
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report.write(f" 最短线条: {min(lengths):.4f}\n")
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report.write(f" 最长线条: {max(lengths):.4f}\n")
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report.write(f" 平均长度: {sum(lengths)/len(lengths):.4f}\n")
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# 详细数据
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report.write(f"\n详细线条数据:\n")
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for i, line in enumerate(lines_data):
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report.write(f"\n线条 {i+1}:\n")
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for key, value in line.items():
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report.write(f" {key}: {value}\n")
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print(f"统计报告已保存到: {output_path}")
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return True
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except Exception as e:
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print(f"创建统计报告失败: {e}")
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return False
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def main():
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"""主函数"""
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print_separator("正确的DWG线条提取工具")
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print("基于调试结果，使用正确的API提取线条数据")
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print()
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# 查找DWG文件
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dwg_files = list(Path('.').glob('*.dwg'))
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if not dwg_files:
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print("当前目录下未找到DWG文件")
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print("请确保DWG文件在当前目录中")
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return
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print(f"找到 {len(dwg_files)} 个DWG文件:")
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for i, dwg_file in enumerate(dwg_files, 1):
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print(f" {i}. {dwg_file}")
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# 使用第一个DWG文件进行测试
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test_file = str(dwg_files[0])
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print(f"\n使用文件进行提取: {test_file}")
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# 提取线条数据
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lines_data = extract_lines_correctly(test_file)
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if lines_data is None:
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print("线条提取失败")
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return
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# 保存数据
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base_name = test_file.replace('.dwg', '')
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# 保存为CSV
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csv_path = f"{base_name}_lines_correct.csv"
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csv_success = save_lines_to_csv(lines_data, csv_path)
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# 保存为JSON
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json_path = f"{base_name}_lines_correct.json"
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json_success = save_lines_to_json(lines_data, json_path)
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# 创建统计报告
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report_path = f"{base_name}_lines_correct_report.txt"
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report_success = create_summary_report(lines_data, report_path)
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# 总结
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print_separator("提取总结")
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print(f"提取的线条数量: {len(lines_data)}")
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print(f"CSV文件保存: {'成功' if csv_success else '失败'}")
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print(f"JSON文件保存: {'成功' if json_success else '失败'}")
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print(f"统计报告生成: {'成功' if report_success else '失败'}")
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if csv_success or json_success:
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print(f"\n线条提取完成！文件已保存到当前目录")
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print(f" - CSV文件: {csv_path}")
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print(f" - JSON文件: {json_path}")
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print(f" - 统计报告: {report_path}")
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else:
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print("\n所有保存操作都失败了")
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if __name__ == "__main__":
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try:
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main()
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except KeyboardInterrupt:
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print("\n\n用户中断了程序执行")
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except Exception as e:
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print(f"\n\n程序执行出错: {e}")
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import traceback
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traceback.print_exc()
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