A high-performance OCR tool powered by RapidOCR to extract structured Chinese and English text from any image file.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install rapid-ocr-reader
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install rapid-ocr-reader using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Rapid OCR Reader?
Rapid OCR Reader is a specialized tool within the Openclaw Skills ecosystem designed for high-accuracy Optical Character Recognition. By leveraging the PP-OCRv4 models and the ONNX Runtime backend, it enables developers and AI agents to programmatically read text from screenshots, documents, and photos without requiring a GPU.
This skill bridges the gap between visual data and actionable text, making it an essential component for automated data extraction, document processing, and visual context understanding. It is optimized for speed and efficiency, ensuring that text extraction occurs in seconds even on standard CPU hardware.
Rapid OCR Reader Use Cases
- Extracting text from UI screenshots for automated software testing or analysis.
- Processing photographed documents, receipts, and invoices into machine-readable formats.
- Identifying labels, annotations, and legends within complex technical diagrams.
- Automating content extraction from web-based images or social media captures for data archiving.
How Rapid OCR Reader Works
- The user or AI agent provides a local path to an image file (JPG, PNG, etc.) as input.
- The system invokes the RapidOCR engine to perform localized text detection across the image.
- The PP-OCRv4 model identifies characters and recognizes text in Chinese, English, or mixed-language formats.
- The skill generates a structured JSON response containing the full text string, individual line metadata, and spatial bounding boxes.
Rapid OCR Reader Setup
Install the required dependencies via pip to start using this Openclaw Skills utility:
pip install rapidocr onnxruntime pillow
To perform OCR on an image, execute the provided script:
python scripts/read_image.py /path/to/image.jpg
Note: On the first execution, the system will automatically download the necessary OCR models (~50MB).
Rapid OCR Reader Data Schema & Taxonomy
| Field | Type | Description |
|---|---|---|
| success | boolean | Indicates if the OCR process completed successfully. |
| text | string | The full block of extracted text as a single string. |
| lines | array | A detailed list of objects containing specific text lines, confidence scores, and bounding box coordinates. |
| line_count | integer | The total number of distinct text lines detected in the image. |
| image_info | object | Metadata including image format, dimensions, and color mode. |
Rapid OCR Reader Advanced Features
- Support for multi-language detection including Simplified/Traditional Chinese and English.
- High-precision spatial mapping using bounding box coordinates for every detected text line.
- CPU-optimized execution utilizing ONNX Runtime for fast processing without expensive GPU overhead.
- Seamless integration for AI agents within the Openclaw Skills framework to handle visual inputs autonomously.
SKILL.md
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