Silicon Paddle OCR
OCR skill using PaddleOCR model via SiliconFlow API. This skill should be used when the user asks to "recognize text from an image", "extract text from a photo", "OCR this image", "read text from screenshot", or mentions "PaddleOCR", "image text recognition", "text extraction from images".
- Skill ID
- aotenjou/silicon-paddleocr/silicon-paddle-ocr
- Publisher
- aotenjou
- Repository
- silicon-paddleocr
- Installs
- 0
- Files
- 5
- License
- MIT
- Synced
- Sep 23, 2026
Open any RiverX project, open the Skills panel in the chat, and search for this identifier. The files are fetched from the source repository at install time.
aotenjou/silicon-paddleocr/silicon-paddle-ocrInstalls these files- SKILL.md
- examples/sample-usage.sh
- metadata.json
- references/api-configuration.md
- scripts/ocr_skill.py
What this skill tells the agent
OCR - Image Text Recognition
Use PaddleOCR to extract text content from images. Supports single image or batch processing.
Overview
This skill provides optical character recognition (OCR) capabilities using the PaddlePaddle/PaddleOCR-VL-1.5 model via the SiliconFlow API. Extract text from JPG, PNG, WebP, BMP, and GIF images.
When to Use
Invoke this skill when:
- User wants to extract text from an image
- User asks to OCR a screenshot or photo
- User needs to read text from an image file
- User mentions text recognition from images
How to Use
Prerequisites
Ensure the SILICONFLOW_API_KEY environment variable is set:
export SILICONFLOW_API_KEY="your_api_key"Basic Usage
Execute the OCR script:
python3 scripts/ocr_skill.py [options] image_pathArguments
| Argument | Description |
|---|---|
images | Image file path(s) or glob pattern (required) |
-k, --api-key | API key (default: from SILICONFLOW_API_KEY env) |
-m, --model | OCR model name (default: PaddlePaddle/PaddleOCR-VL-1.5) |
-p, --prompt | Recognition prompt for custom behavior |
-j, --json | Output results in JSON format |
-o, --output | Save results to specified file |
--max-tokens | Maximum tokens in response (default: 2000) |
Examples
Single image:
python3 scripts/ocr_skill.py /path/to/image.jpgMultiple images with glob:
python3 scripts/ocr_skill.py /path/to/images/*.pngJSON output format:
python3 scripts/ocr_skill.py --json /path/to/image.jpgCustom prompt for table extraction:
python3 scripts/ocr_skill.py -p "Please identify and format table content as Markdown" /path/to/table.jpgSave to file:
python3 scripts/ocr_skill.py --json --output results.json /path/to/images/*.jpgOutput Format
Text output (default):
--- image.jpg ---
识别到的文字内容
识别到 X 处文字区域JSON output:
{
"image.jpg": {
"image_path": "/path/to/image.jpg",
"image_size": [width, height],
"texts": [
{
"text": "识别的文字",
"box": [[x1, y1], [x2, y2], [x3, y3], [x4, y4]]
}
],
"full_text": "所有文本的组合"
},
"image2.png": { ... }
}Coordinates Explanation:
- LOC values are normalized coordinates converted to pixel coordinates
- Conversion: pixel = LOC × (image_size / LOC_max_value)
- LOC max_value is approximately 972 (may vary by model/image)
- The
boxfield provides the four corner coordinates of each text region in pixel format
Supported Image Formats
- JPG/JPEG
- PNG
- WebP
- BMP
- GIF
Error Handling
If processing fails:
- Check that the image file exists
- Verify the SILICONFLOW_API_KEY is valid
- Ensure the API endpoint is reachable
Images that fail to process will show an error message, and other images will continue processing.
Additional Resources
Reference Files
- `references/api-configuration.md` - API configuration details
Example Files
- `examples/sample-usage.sh` - Example usage script
Scripts
- `scripts/ocr_skill.py` - The main OCR implementation
Use this skill in a project
Open any RiverX project, search the Skills panel for aotenjou/silicon-paddleocr/silicon-paddle-ocr, and install it in one click.
