stock-data-skill
OpenClaw Skill for stock data analysis
Extract data from construction images using AI Vision. Analyze site photos, scanned documents, drawings.
请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求,再添加到工作流。
SkillHub CLI
skillhub install datadrivenconstruction/image-to-data打开来源仓库,查看说明和兼容环境后,按来源提供的命令或步骤安装。
将来源链接提供给你的 Agent,让它先读取说明、核对依赖,并向你说明将执行的安装步骤。
Based on DDC methodology (Chapter 2.4), this skill extracts structured data from construction images using computer vision, OCR, and AI models to analyze site photos, scanned documents, and drawings.
Book Reference: "Преобразование данных в структурированную форму" / "Data Transformation to Structured Form"
from dataclasses import dataclass, field
from enum import Enum
from typing import List, Dict, Optional, Any, Tuple
from datetime import datetime
import json
import base64
class ImageType(Enum):
"""Types of construction images"""
SITE_PHOTO = "site_photo"
SCANNED_DOCUMENT = "scanned_document"
FLOOR_PLAN = "floor_plan"
ELEVATION = "elevation"
DETAIL_DRAWING = "detail_drawing"
PROGRESS_PHOTO = "progress_photo"
SAFETY_PHOTO = "safety_photo"
DEFECT_PHOTO = "defect_photo"
MATERIAL_PHOTO = "material_photo"
EQUIPMENT_PHOTO = "equipment_photo"
class ExtractionType(Enum):
"""Types of data extraction"""
OCR_TEXT = "ocr_text"
TABLE = "table"
OBJECT_DETECTION = "object_detection"
MEASUREMENT = "measurement"
CLASSIFICATION = "classification"
PROGRESS = "progress"
@dataclass
class BoundingBox:
"""Bounding box for detected region"""
x: int
y: int
width: int
height: int
confidence: float = 1.0
@dataclass
class TextRegion:
"""Extracted text region from image"""
text: str
bbox: BoundingBox
confidence: float
language: str = "en"
@dataclass
class DetectedObject:
"""Detected object in image"""
label: str
bbox: BoundingBox
confidence: float
attributes: Dict[str, Any] = field(default_factory=dict)
@dataclass
class ExtractedTable:
"""Extracted table from image"""
headers: List[str]
rows: List[List[str]]
bbox: BoundingBox
confidence: float
@dataclass
class ProgressMeasurement:
"""Progress m...
这些信息来自收录时的来源分析,可能滞后;使用前请核对最新来源文件。
# Image To Data
## Overview
Based on DDC methodology (Chapter 2.4), this skill extracts structured data from construction images using computer vision, OCR, and AI models to analyze site photos, scanned documents, and drawings.
**Book Reference:** "Преобразование данных в структурированную форму" / "Data Transformation to Structured Form"
## Quick Start
```python
from dataclasses import dataclass, field
from enum import Enum
from typing import List, Dict, Optional, Any, Tuple
from datetime import datetime
import json
import base64
class ImageType(Enum):
"""Types of construction images"""
SITE_PHOTO = "site_photo"
SCANNED_DOCUMENT = "scanned_document"
FLOOR_PLAN = "floor_plan"
ELEVATION = "elevation"
DETAIL_DRAWING = "detail_drawing"
PROGRESS_PHOTO = "progress_photo"
SAFETY_PHOTO = "safety_photo"
DEFECT_PHOTO = "defect_photo"
MATERIAL_PHOTO = "material_photo"
EQUIPMENT_PHOTO = "equipment_photo"
class ExtractionType(Enum):
"""Types of data extraction"""
OCR_TEXT = "ocr_text"
TABLE = "table"
OBJECT_DETECTION = "object_detection"
MEASUREMENT = "measurement"
CLASSIFICATION = "classification"
PROGRESS = "progress"
@dataclass
class BoundingBox:
"""Bounding box for detected region"""
x: int
y: int
width: int
height: int
confidence: float = 1.0
@dataclass
class TextRegion:
"""Extracted text region from image"""
text: str
bbox: BoundingBox
confidence: float
language: str = "en"
@dataclass
class DetectedObject:
"""Detected object in image"""
label: str
bbox: BoundingBox
confidence: float
attributes: Dict[str, Any] = field(default_factory=dict)
@dataclass
class ExtractedTable:
"""Extracted table from image"""
headers: List[str]
rows: List[List[str]]
bbox: BoundingBox
confidence: float
@dataclass
class ProgressMeasurement:
"""Progress m...OpenClaw Skill for stock data analysis
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