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drawing-analyzer绘图分析仪

Agent Skill

drawing-analyzer 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

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OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

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请帮我安装这个 Agent Skill:drawing-analyzer(绘图分析仪)
来源仓库:https://github.com/datadrivenconstruction/drawing-analyzer
安装命令:
openclaw skills install drawing-analyzer
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

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openclaw skills install drawing-analyzer

简介

分析施工图以提取尺寸、注释、符号和元数据。 Support quantity takeoff and design review automation.

SKILL.md

name
drawing-analyzer
description
Analyze construction drawings to extract dimensions, annotations, symbols, and metadata. Support quantity takeoff and design review automation.
homepage
https://datadrivenconstruction.io
metadata
{"openclaw": {"emoji": "📑", "os": ["darwin", "linux", "win32"], "homepage": "https://datadrivenconstruction.io", "requires": {"bins": ["python3"]}}}

Drawing Analyzer for Construction

Overview

Analyze construction drawings (PDF, DWG) to extract dimensions, annotations, symbols, title block data, and support automated quantity takeoff and design review.

Business Case

Drawing analysis automation enables:

  • Faster Takeoffs: Extract quantities from drawings
  • Quality Control: Verify drawing completeness
  • Data Extraction: Pull metadata for project systems
  • Design Review: Automated checking against standards

Technical Implementation

from dataclasses import dataclass, field
from typing import List, Dict, Any, Optional, Tuple
import re
import pdfplumber
from pathlib import Path

@dataclass
class TitleBlockData:
    project_name: str
    project_number: str
    sheet_number: str
    sheet_title: str
    discipline: str
    scale: str
    date: str
    revision: str
    drawn_by: str
    checked_by: str
    approved_by: str

@dataclass
class Dimension:
    value: float
    unit: str
    dimension_type: str  # linear, angular, radial
    location: Tuple[float, float]
    associated_text: str

@dataclass
class Annotation:
    text: str
    annotation_type: str  # note, callout, tag, keynote
    location: Tuple[float, float]
    references: List[str]

@dataclass
class Symbol:
    symbol_type: str  # door, window, equipment, etc.
    tag: str
    location: Tuple[float, float]
    properties: Dict[str, Any]

@dataclass
class DrawingAnalysisResult:
    file_name: str
    title_block: Optional[TitleBlockData]
    dimensions: List[Dimension]
    annotations: List[Annotation]
    symbols: List[Symbol]
    scale_factor: float
    drawing_area: Tuple[float, float]
    quality_issues: List[str]

class DrawingAnalyzer:
    """Analyze construction drawings for data extraction."""

    # Common dimension patterns
    DIMENSION_PATTERNS = [
        r"(\d+'-\s*\d+(?:\s*\d+/\d+)?\"?)",  # Feet-inches: 10'-6", 10' - 6 1/2"
        r"(\d+(?:\.\d+)?)\s*(?:mm|cm|m|ft|in)",  # Metric/imperial with unit
        r"(\d+'-\d+\")",  # Compact feet-inches
        r"(\d+)\s*(?:SF|LF|CY|EA)",  # Quantity dimensions
    ]

    # Common annotation patterns
    ANNOTATION_PATTERNS = {
        'keynote': r'^\d{1,2}[A-Z]?$',  # 1A, 12, 5B
        'room_tag': r'^(?:RM|ROOM)\s*\d+',
        'door_tag': r'^[A-Z]?\d{2,3}[A-Z]?$',
        'grid_line': r'^[A-Z]$|^\d+$',
        'elevation': r'^(?:EL|ELEV)\.?\s*\d+',
        'detail_ref': r'^\d+/[A-Z]\d+',
    }

    # Scale patterns
    SCALE_PATTERNS = [
        r"SCALE:\s*(\d+(?:/\d+)?)\s*[\"']\s*=\s*(\d+)\s*['\-]",  # 1/4" = 1'-0"
        r"(\d+):(\d+)",  # 1:100
        r"NTS|NOT TO SCALE",
    ]

    def __init__(self):
        self.results: Dict[str, DrawingAnalysisResult] = {}

    def analyze_pdf_drawing(self, pdf_path: str) -> DrawingAnalysisResult:
        """Analyze a PDF drawing."""
        path = Path(pdf_path)

        all_text = ""
        dimensions = []
        annotations = []
        symbols = []
        quality_issues = []

        with pdfplumber.open(pdf_path) as pdf:
            for page in pdf.pages:
                # Extract text
                text = page.extract_text() or ""
                all_text += text + "\
"

                # Extract dimensions
                page_dims = self._extract_dimensions(text)
                dimensions.extend(page_dims)

                # Extract annotations
                page_annots = self._extract_annotations(text)
                annotations.extend(page_annots)

                # Extract from tables (often contain schedules)
                tables = page.extract_tables()
                for table in tables:
                    symbols.extend(self._parse_schedule_table(table))

        # Parse title block
        title_block = self._extract_title_block(all_text)

        # Determine scale
        scale_factor = self._determine_scale(all_text)

        # Quality checks
        quality_issues = self._check_drawing_quality(
            title_block, dimensions, annotations
        )

        result = DrawingAnalysisResult(
            file_name=path.name,
            title_block=title_block,
            dimensions=dimensions,
            annotations=annotations,
            symbols=symbols,
            scale_factor=scale_factor,
            drawing_area=(0, 0),  # Would need image analysis
            quality_issues=quality_issues
        )

        self.results[path.name] = result
        return result

    def _extract_dimensions(self, text: str) -> List[Dimension]:
        """Extract dimensions from text."""
        dimensions = []

        for pattern in self.DIMENSION_PATTERNS:
            matches = re.findall(pattern, text)
            for match in matches:
                value, unit = self._parse_dimension_value(match)
                if value > 0:
                    dimensions.append(Dimension(
                        value=value,
                        unit=unit,
                        dimension_type='linear',
                        location=(0, 0),
                        associated_text=match
                    ))

        return dimensions

    def _parse_dimension_value(self, dim_text: str) -> Tuple[float, str]:
        """Parse dimension text to value and unit."""
        dim_text = dim_text.strip()

        # Feet and inches: 10'-6"
        ft_in_match = re.match(r"(\d+)'[-\s]*(\d+)?(?:\s*(\d+)/(\d+))?\"?", dim_text)
        if ft_in_match:
            feet = int(ft_in_match.group(1))
            inches = int(ft_in_match.group(2) or 0)
            if ft_in_match.group(3) and ft_in_match.group(4):
                inches += int(ft_in_match.group(3)) / int(ft_in_match.group(4))
            return feet * 12 + inches, 'in'

        # Metric with unit
        metric_match = re.match(r"(\d+(?:\.\d+)?)\s*(mm|cm|m)", dim_text)
        if metric_match:
            return float(metric_match.group(1)), metric_match.group(2)

        # Just a number
        num_match = re.match(r"(\d+(?:\.\d+)?)", dim_text)
        if num_match:
            return float(num_match.group(1)), ''

        return 0, ''

    def _extract_annotations(self, text: str) -> List[Annotation]:
        """Extract annotations from text."""
        annotations = []
        lines = text.split('\
')

        for line in lines:
            line = line.strip()
            if not line:
                continue

            for annot_type, pattern in self.ANNOTATION_PATTERNS.items():
                if re.match(pattern, line, re.IGNORECASE):
                    annotations.append(Annotation(
                        text=line,
                        annotation_type=annot_type,
                        location=(0, 0),
                        references=[]
                    ))
                    break

            # General notes
            if line.startswith(('NOTE:', 'SEE ', 'REFER TO', 'TYP', 'U.N.O.')):
                annotations.append(Annotation(
                    text=line,
                    annotation_type='note',
                    location=(0, 0),
                    references=[]
                ))

        return annotations

    def _extract_title_block(self, text: str) -> Optional[TitleBlockData]:
        """Extract title block information."""
        # Common title block patterns
        patterns = {
            'project_name': r'PROJECT(?:\s*NAME)?:\s*(.+?)(?:\
|$)',
            'project_number': r'(?:PROJECT\s*)?(?:NO|NUMBER|#)\.?:\s*(\S+)',
            'sheet_number': r'SHEET(?:\s*NO)?\.?:\s*([A-Z]?\d+(?:\.\d+)?)',
            'sheet_title': r'SHEET\s*TITLE:\s*(.+?)(?:\
|$)',
            'scale': r'SCALE:\s*(.+?)(?:\
|$)',
            'date': r'DATE:\s*(\d{1,2}[/-]\d{1,2}[/-]\d{2,4})',
            'revision': r'REV(?:ISION)?\.?:\s*(\S+)',
            'drawn_by': r'(?:DRAWN|DRN)\s*(?:BY)?:\s*(\S+)',
            'checked_by': r'(?:CHECKED|CHK)\s*(?:BY)?:\s*(\S+)',
        }

        extracted = {}
        for field, pattern in patterns.items():
            match = re.search(pattern, text, re.IGNORECASE)
            extracted[field] = match.group(1).strip() if match else ''

        # Determine discipline from sheet number
        sheet_num = extracted.get('sheet_number', '')
        discipline = ''
        if sheet_num:
            prefix = sheet_num[0].upper() if sheet_num[0].isalpha() else ''
            discipline_map = {
                'A': 'Architectural', 'S': 'Structural', 'M': 'Mechanical',
                'E': 'Electrical', 'P': 'Plumbing', 'C': 'Civil',
                'L': 'Landscape', 'I': 'Interior', 'F': 'Fire Protection'
            }
            discipline = discipline_map.get(prefix, '')

        return TitleBlockData(
            project_name=extracted.get('project_name', ''),
            project_number=extracted.get('project_number', ''),
            sheet_number=sheet_num,
            sheet_title=extracted.get('sheet_title', ''),
            discipline=discipline,
            scale=extracted.get('scale', ''),
            date=extracted.get('date', ''),
            revision=extracted.get('revision', ''),
            drawn_by=extracted.get('drawn_by', ''),
            checked_by=extracted.get('checked_by', ''),
            approved_by=''
        )

    def _parse_schedule_table(self, table: List[List]) -> List[Symbol]:
        """Parse schedule table to extract symbols/elements."""
        symbols = []

        if not table or len(table) < 2:
            return symbols

        # First row is usually headers
        headers = [str(cell).lower() if cell else '' for cell in table[0]]

        # Find key columns
        tag_col = next((i for i, h in enumerate(headers) if 'tag' in h or 'mark' in h or 'no' in h), 0)
        type_col = next((i for i, h in enumerate(headers) if 'type' in h or 'size' in h), -1)

        for row in table[1:]:
            if len(row) > tag_col and row[tag_col]:
                tag = str(row[tag_col]).strip()
                symbol_type = str(row[type_col]).strip() if type_col >= 0 and len(row) > type_col else ''

                if tag:
                    props = {}
                    for i, header in enumerate(headers):
                        if i < len(row) and row[i]:
                            props[header] = str(row[i])

                    symbols.append(Symbol(
                        symbol_type=symbol_type or 'unknown',
                        tag=tag,
                        location=(0, 0),
                        properties=props
                    ))

        return symbols

    def _determine_scale(self, text: str) -> float:
        """Determine drawing scale factor."""
        for pattern in self.SCALE_PATTERNS:
            match = re.search(pattern, text, re.IGNORECASE)
            if match:
                if 'NTS' in match.group(0).upper():
                    return 0  # Not to scale

                if '=' in match.group(0):
                    # Imperial: 1/4" = 1'-0"
                    return self._parse_imperial_scale(match.group(0))
                else:
                    # Metric: 1:100
                    return 1 / float(match.group(2))

        return 1.0  # Default

    def _parse_imperial_scale(self, scale_text: str) -> float:
        """Parse imperial scale to factor."""
        match = re.search(r'(\d+)(?:/(\d+))?\s*["\']?\s*=\s*(\d+)', scale_text)
        if match:
            numerator = float(match.group(1))
            denominator = float(match.group(2)) if match.group(2) else 1
            feet = float(match.group(3))
            inches_per_foot = (numerator / denominator)
            return inches_per_foot / (feet * 12)
        return 1.0

    def _check_drawing_quality(self, title_block: TitleBlockData,
                                dimensions: List, annotations: List) -> List[str]:
        """Check drawing for quality issues."""
        issues = []

        if title_block:
            if not title_block.project_number:
                issues.append("Missing project number in title block")
            if not title_block.sheet_number:
                issues.append("Missing sheet number")
            if not title_block.scale:
                issues.append("Missing scale indication")
            if not title_block.date:
                issues.append("Missing date")

        if len(dimensions) == 0:
            issues.append("No dimensions found - verify drawing content")

        # Check for typical construction notes
        note_types = [a.annotation_type for a in annotations]
        if 'note' not in note_types:
            issues.append("No general notes found")

        return issues

    def generate_drawing_index(self, results: List[DrawingAnalysisResult]) -> str:
        """Generate drawing index from multiple analyzed drawings."""
        lines = ["# Drawing Index", ""]
        lines.append("| Sheet | Title | Discipline | Scale | Rev |")
        lines.append("|-------|-------|------------|-------|-----|")

        for result in sorted(results, key=lambda r: r.title_block.sheet_number if r.title_block else ''):
            if result.title_block:
                tb = result.title_block
                lines.append(f"| {tb.sheet_number} | {tb.sheet_title} | {tb.discipline} | {tb.scale} | {tb.revision} |")

        return "\
".join(lines)

    def generate_report(self, result: DrawingAnalysisResult) -> str:
        """Generate analysis report for a drawing."""
        lines = ["# Drawing Analysis Report", ""]
        lines.append(f"**File:** {result.file_name}")

        if result.title_block:
            tb = result.title_block
            lines.append("")
            lines.append("## Title Block")
            lines.append(f"- **Project:** {tb.project_name}")
            lines.append(f"- **Project No:** {tb.project_number}")
            lines.append(f"- **Sheet:** {tb.sheet_number}")
            lines.append(f"- **Title:** {tb.sheet_title}")
            lines.append(f"- **Discipline:** {tb.discipline}")
            lines.append(f"- **Scale:** {tb.scale}")
            lines.append(f"- **Date:** {tb.date}")
            lines.append(f"- **Revision:** {tb.revision}")

        lines.append("")
        lines.append("## Content Summary")
        lines.append(f"- **Dimensions Found:** {len(result.dimensions)}")
        lines.append(f"- **Annotations Found:** {len(result.annotations)}")
        lines.append(f"- **Symbols/Elements:** {len(result.symbols)}")

        if result.quality_issues:
            lines.append("")
            lines.append("## Quality Issues")
            for issue in result.quality_issues:
                lines.append(f"- ⚠️ {issue}")

        if result.symbols:
            lines.append("")
            lines.append("## Elements Found")
            for symbol in result.symbols[:20]:
                lines.append(f"- {symbol.tag}: {symbol.symbol_type}")

        return "\
".join(lines)

Quick Start

# Initialize analyzer
analyzer = DrawingAnalyzer()

# Analyze a drawing
result = analyzer.analyze_pdf_drawing("A101_Floor_Plan.pdf")

# Check title block
if result.title_block:
    print(f"Sheet: {result.title_block.sheet_number}")
    print(f"Title: {result.title_block.sheet_title}")
    print(f"Scale: {result.title_block.scale}")

# Review extracted data
print(f"Dimensions: {len(result.dimensions)}")
print(f"Annotations: {len(result.annotations)}")
print(f"Symbols: {len(result.symbols)}")

# Check quality
for issue in result.quality_issues:
    print(f"Issue: {issue}")

# Generate report
report = analyzer.generate_report(result)
print(report)

Dependencies

pip install pdfplumber

适合场景

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能力 4

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