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OpenClaw

image-to-data

Extract data from construction images using AI Vision. Analyze site photos, scanned documents, drawings.

datadrivenconstruction0 来源安装数☆ 0 仓库 Stars

安装与使用

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。

查看来源 ↗使用指南

技能说明

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

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...

来源信息

Source
github
Repository
openclaw/skills
Path
skills/datadrivenconstruction/image-to-data
Version
—
Commit
ee612319881c9306a664db29f0bf3372b36f1d92
分类来源
rules
状态
active
可见性
public

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。

来源内容

SKILL.md
# 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...

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