paddleocr-doc-parsing
Parse documents using PaddleOCR's API.
Datos de origen
- Repositorio
- Kernel8901/ai-agent-skills-classification
- Última actividad en el origen
- 4 de abril de 2026 a las 15:26
- Idioma detectado de SKILL.md
- inglés
- Estrellas
- 5
- Forks
- 1
Opciones de instalación
De forma predeterminada está seleccionado el prompt que primero revisa el origen. Puedes cambiar a un comando directo o descargar una copia local.
Revisa los archivos de origen
Lee SKILL.md y los archivos complementarios que muestra SkillsMP antes de decidir si quieres instalarlo.
Explorador de archivos
3 archivosMostrando SKILL.md
SKILL.md
Instrucciones de origen · Vista previa de solo lectura- name
- paddleocr-doc-parsing
- description
- Parse documents using PaddleOCR's API.
- homepage
- https://www.paddleocr.com
- metadata
- {"openclaw":{"emoji":"📄","os":["darwin","linux"],"requires":{"bins":"[Truncated]","env":"[Truncated]"}}}
# PaddleOCR Document Parsing
Parse images and PDF files using PaddleOCR's API. Supports multiple document parsing algorithms with structured output.
## Key Features
- **Multi-format support**: PDF and image files (JPG, PNG, BMP, TIFF)
- **Layout analysis**: Automatic detection of text blocks, tables, formulas
- **Multi-language**: Support for 110+ languages
- **Structured output**: Markdown format with preserved document structure
## Setup
1. Obtain credentials from the [PaddleOCR official website](https://www.paddleocr.com). Click the “API” button, choose the desired algorithm (e.g., PP-Structure, PaddleOCR-VL-1.5), and copy the API URL and the access token.
2. Set environment variables:
```bash
export PADDLEOCR_API_URL="https://your-endpoint-here"
export PADDLEOCR_ACCESS_TOKEN="your_access_token"
```
## Usage Examples
### Run Script
```bash
# Parse local image
{baseDir}/paddleocr_parse.sh document.jpg
# Parse local PDF file
{baseDir}/paddleocr_parse.sh -t pdf document.pdf
# Parse document from URL
{baseDir}/paddleocr_parse.sh -t pdf https://example.com/document.pdf
# Output to stdout (default)
{baseDir}/paddleocr_parse.sh document.jpg
# Save output to file
{baseDir}/paddleocr_parse.sh -o result.json document.jpg
```
### Response Structure
```json
{
"logId": "unique_request_id",
"errorCode": 0,
"errorMsg": "Success",
"result": {
"layoutParsingResults": [
{
"prunedResult": [...],
"markdown": {
"text": "# Document Title\n\nParagraph content...",
"images": {}
},
"outputImages": [...],
"inputImage": "http://input-image"
}
],
"dataInfo": {...}
}
}
```
**Important Fields:**
- **`prunedResult`** - Contains detailed layout element information including positions, categories, etc.
- **`markdown`** - Stores the document content converted to Markdown format with preserved structure and formatting.
## Quota Information
See official documentation: https://ai.baidu.com/ai-doc/AISTUDIO/Xmjclapam
Ver en GitHub