10-of-my-most-popular-text-to-image-series-prompts-78b0897e
generate a bunch of images, then you curate the results to handpick the best ones
Extract quantities from BIM/CAD data for cost estimation. Group by type, level, zone. Generate QTO reports.
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Quantity Takeoff (QTO) extracts measurable quantities from BIM models. This skill processes BIM exports to generate grouped quantity reports for cost estimation.
import pandas as pd
import numpy as np
from typing import Dict, Any, List, Optional, Tuple
from dataclasses import dataclass, field
from enum import Enum
class QTOUnit(Enum):
"""Quantity takeoff measurement units."""
COUNT = "ea"
LENGTH = "m"
AREA = "m2"
VOLUME = "m3"
WEIGHT = "kg"
LINEAR_FOOT = "lf"
SQUARE_FOOT = "sf"
CUBIC_YARD = "cy"
@dataclass
class QTOItem:
"""Single QTO line item."""
category: str
type_name: str
description: str
quantity: float
unit: str
level: Optional[str] = None
material: Optional[str] = None
element_count: int = 0
@dataclass
class QTOReport:
"""Complete QTO report."""
project_name: str
items: List[QTOItem]
total_elements: int
categories: int
generated_date: str
class BIMQuantityTakeoff:
"""Extract quantities from BIM data."""
# Column mappings for different BIM exports
COLUMN_MAPPINGS = {
'type': ['Type Name', 'TypeName', 'type_name', 'Family and Type', 'IfcType'],
'category': ['Category', 'category', 'IfcClass', 'Element Category'],
'level': ['Level', 'level', 'Building Storey', 'BuildingStorey', 'Floor'],
'volume': ['Volume', 'volume', 'Volume (m³)', 'Qty_Volume'],
'area': ['Area', 'area', 'Surface Area', 'Area (m²)', 'Qty_Area'],
'length': ['Length', 'length', 'Length (m)', 'Qty_Length'],
'count': ['Count', 'count', 'Quantity', 'ElementCount'],
'material': ['Material', 'material', 'Structural Material', 'MaterialName']
}
def __init__(self, df: pd.DataFrame):
"""Initialize with BIM data DataFrame."""
self.df = df
self.column_map =...
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# BIM Quantity Takeoff
## Overview
Quantity Takeoff (QTO) extracts measurable quantities from BIM models. This skill processes BIM exports to generate grouped quantity reports for cost estimation.
## Python Implementation
```python
import pandas as pd
import numpy as np
from typing import Dict, Any, List, Optional, Tuple
from dataclasses import dataclass, field
from enum import Enum
class QTOUnit(Enum):
"""Quantity takeoff measurement units."""
COUNT = "ea"
LENGTH = "m"
AREA = "m2"
VOLUME = "m3"
WEIGHT = "kg"
LINEAR_FOOT = "lf"
SQUARE_FOOT = "sf"
CUBIC_YARD = "cy"
@dataclass
class QTOItem:
"""Single QTO line item."""
category: str
type_name: str
description: str
quantity: float
unit: str
level: Optional[str] = None
material: Optional[str] = None
element_count: int = 0
@dataclass
class QTOReport:
"""Complete QTO report."""
project_name: str
items: List[QTOItem]
total_elements: int
categories: int
generated_date: str
class BIMQuantityTakeoff:
"""Extract quantities from BIM data."""
# Column mappings for different BIM exports
COLUMN_MAPPINGS = {
'type': ['Type Name', 'TypeName', 'type_name', 'Family and Type', 'IfcType'],
'category': ['Category', 'category', 'IfcClass', 'Element Category'],
'level': ['Level', 'level', 'Building Storey', 'BuildingStorey', 'Floor'],
'volume': ['Volume', 'volume', 'Volume (m³)', 'Qty_Volume'],
'area': ['Area', 'area', 'Surface Area', 'Area (m²)', 'Qty_Area'],
'length': ['Length', 'length', 'Length (m)', 'Qty_Length'],
'count': ['Count', 'count', 'Quantity', 'ElementCount'],
'material': ['Material', 'material', 'Structural Material', 'MaterialName']
}
def __init__(self, df: pd.DataFrame):
"""Initialize with BIM data DataFrame."""
self.df = df
self.column_map =...generate a bunch of images, then you curate the results to handpick the best ones
generate a bunch of images, then you curate the results to handpick the best ones
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