Image OCR

Source: https://github.com/aipoch/medical-research-skills

When to Use

• You need to extract text from an image file (PNG/JPEG/TIFF/BMP) for downstream processing or review.
• You want to run OCR with a specific Tesseract language model (e.g., eng, chi_sim).
• You prefer providing a natural-language request that contains an image path (e.g., "Interpret the image at ...") instead of manually setting image_path.
• You need a quick local OCR verification workflow from the command line.
• You want a simple JSON-configured OCR runner that can be integrated into scripts or automation.

Key Features

• OCR text extraction using Tesseract via pytesseract.
• Supports common image formats: PNG, JPEG, TIFF, BMP (via Pillow).
• Multi-language OCR through the lang configuration option.
• Natural-language request parsing to automatically locate the image path.
• Config-driven execution through scripts/ocr_config.json.

Dependencies

• Python packages:
  • pytesseract (version not specified)
  • Pillow (version not specified)
• System dependency:
  • Tesseract OCR (installed separately; ensure tesseract_cmd points to the executable)

Example Usage

1. Install dependencies (example):

pip install pytesseract Pillow

2. Install Tesseract OCR (system-level) and ensure it is accessible.

   • If it is not on PATH, set tesseract_cmd to the full executable path in the config.

3. Create or edit scripts/ocr_config.json:

Option A: Direct image path

{
  "image_path": "C:\\Users\\xuw\\Desktop\\test_image.png",
  "request": "",
  "lang": "chi_sim",
  "tesseract_cmd": "tesseract"
}

Option B: Natural-language request (image path embedded)

{
  "request": "Interpret the image at C:\\Users\\xuw\\Desktop\\test_image.png",
  "lang": "chi_sim",
  "tesseract_cmd": "tesseract"
}

4. Run:

python scripts/image_ocr.py

Implementation Details

• Configuration inputs

  • image_path: Explicit path to the image file to OCR.
  • request: Natural-language instruction that includes an image path; when provided, the script extracts the path from this text and uses it as the OCR target.
  • lang: Tesseract language model code (e.g., eng, chi_sim). This is passed to Tesseract to control recognition language.
  • tesseract_cmd: The Tesseract executable name or full path; used to configure pytesseract to locate Tesseract.

• Execution flow (high level)

  1. Load scripts/ocr_config.json.
  2. Determine the target image path:
     • Use image_path if present and non-empty; otherwise parse the path from request.
  3. Load the image via Pillow.
  4. Run OCR via pytesseract with the configured lang.
  5. Output the extracted text (script-defined output behavior).

• Language model requirement

  • The selected lang must be installed in your local Tesseract language data; otherwise OCR may fail or fall back depending on your Tesseract setup.

When Not to Use

• Do not use this skill when the required source data, identifiers, files, or credentials are missing.
• Do not use this skill when the user asks for fabricated results, unsupported claims, or out-of-scope conclusions.
• Do not use this skill when a simpler direct answer is more appropriate than the documented workflow.

Required Inputs

• A clearly specified task goal aligned with the documented scope.
• All required files, identifiers, parameters, or environment variables before execution.
• Any domain constraints, formatting requirements, and expected output destination if applicable.

Recommended Workflow

1. Validate the request against the skill boundary and confirm all required inputs are present.
2. Select the documented execution path and prefer the simplest supported command or procedure.
3. Produce the expected output using the documented file format, schema, or narrative structure.
4. Run a final validation pass for completeness, consistency, and safety before returning the result.