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ClaudeWave
Skill254 estrellas del repoactualizado 5mo ago

ifc-qto-extraction

This skill automates quantity takeoff extraction from BIM models (IFC, Revit, DWG), using DDC converters to rapidly generate structured data on element counts, areas, volumes, lengths, and weights organized by type and location. Use it to replace manual quantity counting for cost estimation, material procurement, and project tracking when fast, accurate, and updatable takeoffs are needed.

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git clone --depth 1 https://github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction /tmp/ifc-qto-extraction && cp -r /tmp/ifc-qto-extraction/1_DDC_Toolkit/BIM-Analysis/ifc-qto-extraction ~/.claude/skills/ifc-qto-extraction
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SKILL.md

# IFC Quantity Takeoff Extraction

Extract structured quantity data from BIM models (IFC, Revit) for cost estimation, material ordering, and progress tracking.

## Business Case

**Problem**: Manual quantity takeoff is:
- Time-consuming (40-80 hours for medium project)
- Error-prone (human counting mistakes)
- Not repeatable (changes require full rework)
- Disconnected from design (no live updates)

**Solution**: Automated QTO from BIM that:
- Extracts all quantities in minutes
- Groups by type, level, zone
- Updates instantly with model changes
- Exports to Excel for pricing

**ROI**: 90% reduction in QTO time, near-zero counting errors

## DDC Tools Used

```
┌──────────────────────────────────────────────────────────────────────┐
│                      QTO EXTRACTION PIPELINE                          │
├──────────────────────────────────────────────────────────────────────┤
│                                                                       │
│   INPUT                 CONVERT                 ANALYZE               │
│   ┌─────────┐          ┌─────────┐            ┌─────────┐            │
│   │ .rvt    │          │ DDC     │            │ Python  │            │
│   │ .ifc    │─────────►│Converter│───────────►│ pandas  │            │
│   │ .dwg    │          │         │            │         │            │
│   └─────────┘          └─────────┘            └─────────┘            │
│                              │                      │                 │
│                              ▼                      ▼                 │
│                        ┌─────────┐            ┌─────────┐            │
│                        │ .xlsx   │            │ Grouped │            │
│                        │ raw data│            │ QTO     │            │
│                        └─────────┘            └─────────┘            │
│                                                    │                  │
│   OUTPUT                                           ▼                  │
│   ┌─────────────────────────────────────────────────────────────┐   │
│   │  QTO Report                                                  │   │
│   │  • Element counts by type                                    │   │
│   │  • Areas (m², ft²)                                           │   │
│   │  • Volumes (m³, ft³)                                         │   │
│   │  • Lengths (m, ft)                                           │   │
│   │  • Weights (kg, tons)                                        │   │
│   │  • Grouped by level/zone/system                              │   │
│   └─────────────────────────────────────────────────────────────┘   │
│                                                                       │
└──────────────────────────────────────────────────────────────────────┘
```

## CLI Commands

### Revit to Excel (with BBox for volumes)

```bash
# Basic extraction
RvtExporter.exe "C:\Models\Building.rvt"

# Full extraction with bounding boxes (for volume calculations)
RvtExporter.exe "C:\Models\Building.rvt" complete bbox

# Include schedules (Revit's built-in QTO)
RvtExporter.exe "C:\Models\Building.rvt" complete bbox schedule
```

### IFC to Excel

```bash
# Extract IFC data
IfcExporter.exe "C:\Models\Building.ifc"

# Output: Building.xlsx with all IFC entities
```

### DWG to Excel (2D areas)

```bash
# Extract DWG blocks and areas
DwgExporter.exe "C:\Drawings\FloorPlan.dwg"
```

## Python Implementation

```python
import pandas as pd
import numpy as np
from pathlib import Path
import subprocess
from typing import List, Dict, Optional
from dataclasses import dataclass

@dataclass
class QuantityItem:
    """Single quantity line item"""
    category: str
    type_name: str
    count: int
    area: float = 0.0
    volume: float = 0.0
    length: float = 0.0
    weight: float = 0.0
    unit_area: str = "m²"
    unit_volume: str = "m³"
    unit_length: str = "m"
    level: str = ""
    zone: str = ""


class BIMQuantityExtractor:
    """Extract quantities from BIM models using DDC converters"""

    def __init__(self, converter_path: str):
        self.converter_path = Path(converter_path)

    def convert_model(self, model_path: str, options: List[str] = None) -> Path:
        """Convert BIM model to Excel"""

        model = Path(model_path)
        options = options or ["complete", "bbox"]

        # Determine converter
        ext = model.suffix.lower()
        converters = {
            '.rvt': 'RvtExporter.exe',
            '.rfa': 'RvtExporter.exe',
            '.ifc': 'IfcExporter.exe',
            '.dwg': 'DwgExporter.exe',
            '.dgn': 'DgnExporter.exe'
        }

        converter = self.converter_path / converters.get(ext, 'RvtExporter.exe')

        # Build command
        cmd = [str(converter), str(model)] + options

        # Execute
        result = subprocess.run(cmd, capture_output=True, text=True)

        if result.returncode != 0:
            raise RuntimeError(f"Conversion failed: {result.stderr}")

        # Return path to generated Excel
        xlsx_path = model.with_suffix('.xlsx')
        return xlsx_path

    def load_bim_data(self, xlsx_path: str) -> pd.DataFrame:
        """Load converted BIM data from Excel"""

        xlsx = Path(xlsx_path)
        if not xlsx.exists():
            raise FileNotFoundError(f"Excel file not found: {xlsx}")

        # Read main data sheet
        df = pd.read_excel(xlsx, sheet_name=0)

        # Clean column names
        df.columns = df.columns.str.strip()

        return df

    def extract_quantities(
        self,
        df: pd.DataFrame,
        group_by: str = "Type Name",
        include_categories: List[str] = None
    ) -> List[QuantityItem]:
        """Extract quantities grouped by type"""

        # Filter categories if specified
        if include_categories and 'Category' in df.columns:
            df = df[df['Category'].isin(include_categories)]

        # Group and aggregate
        quantities = []

        for (category, type_name),