aotenjou/silicon-paddleocr

silicon-paddle-ocr

OCR skill using PaddleOCR model via SiliconFlow API.

Voir la source

Mode d’emploi

  1. Copiez la commande et examinez le paquet avant de l’installer dans votre environnement agent.
  2. Consultez le document original pour les outils, identifiants et environnements requis.
  3. Décrivez les entrées et le livrable souhaité ; comparez la sortie aux sources.
npx skills add https://github.com/aotenjou/silicon-paddleocr --skill silicon-paddle-ocr

Avant de commencer

  • L’installation n’inclut ni abonnement au modèle, ni quota API, ni accès aux fichiers.
  • Étoiles et installations reflètent l’activité, pas un test indépendant de qualité ou de sécurité.
Document Skill original

Rendu depuis le dépôt source en conservant titres, exemples, code, tableaux, liens et images.

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:

bash
export SILICONFLOW_API_KEY="your_api_key"

Basic Usage

Execute the OCR script:

bash
python3 scripts/ocr_skill.py [options] image_path

Arguments

ArgumentDescription
imagesImage file path(s) or glob pattern (required)
-k, --api-keyAPI key (default: from SILICONFLOWAPIKEY 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:

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

Multiple images with glob:

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

JSON output format:

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

Custom prompt for table extraction:

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

Save to file:

bash
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:

json
{
  "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 × (imagesize / LOCmax_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 SILICONFLOWAPIKEY 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

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