aotenjou/silicon-paddleocrMIT5 files

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".

Specification
Skill ID
aotenjou/silicon-paddleocr/silicon-paddle-ocr
Publisher
aotenjou
Repository
silicon-paddleocr
Installs
0
Files
5
License
MIT
Synced
Sep 23, 2026
How to use it

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_path

Arguments

ArgumentDescription
imagesImage file path(s) or glob pattern (required)
-k, --api-keyAPI key (default: from SILICONFLOW_API_KEY env)
-m, --modelOCR model name (default: PaddlePaddle/PaddleOCR-VL-1.5)
-p, --promptRecognition prompt for custom behavior
-j, --jsonOutput results in JSON format
-o, --outputSave results to specified file
--max-tokensMaximum tokens in response (default: 2000)

Examples

Single image:

python3 scripts/ocr_skill.py /path/to/image.jpg

Multiple images with glob:

python3 scripts/ocr_skill.py /path/to/images/*.png

JSON output format:

python3 scripts/ocr_skill.py --json /path/to/image.jpg

Custom prompt for table extraction:

python3 scripts/ocr_skill.py -p "Please identify and format table content as Markdown" /path/to/table.jpg

Save to file:

python3 scripts/ocr_skill.py --json --output results.json /path/to/images/*.jpg

Output 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 box field 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.

Use this skill