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ocrmypdf-api

OCRmyPDF Python API and plugin skill — use OCRmyPDF programmatically from Python, integrate with applications, and extend with plugins (EasyOCR, PaddleOCR, AppleOCR). Use when the user needs to call OCRmyPDF from Python code, build OCR pipelines, or use alternative OCR engines.

OCRmyPDF — Python API & Plugins Guide

Overview

OCRmyPDF provides a Python API for programmatic use and a plugin interface for extending or replacing OCR engines. This skill covers the Python API, integration patterns, and the plugin ecosystem.

For CLI usage, see the ocrmypdf skill. For batch scripting, see ocrmypdf-batch.

Python API

Basic usage

import ocrmypdf

# Basic OCR
exit_code = ocrmypdf.ocr('input.pdf', 'output.pdf')

# With options
exit_code = ocrmypdf.ocr(
    'input.pdf',
    'output.pdf',
    language='eng+fra',
    deskew=True,
    rotate_pages=True,
    skip_text=True,
    optimize=2,
    jobs=4,
)

Return codes

import ocrmypdf

result = ocrmypdf.ocr('input.pdf', 'output.pdf')

if result == ocrmypdf.ExitCode.ok:
    print("OCR completed successfully")
elif result == ocrmypdf.ExitCode.already_done_ocr:
    print("PDF already has OCR text")
elif result == ocrmypdf.ExitCode.input_file:
    print("Input file issue")
else:
    print(f"Error: {result}")

Common API parameters

| Parameter | Type | Description | |-----------|------|-------------| | language | str | Tesseract language(s), e.g. 'eng+fra' | | deskew | bool | Straighten crooked pages | | rotate_pages | bool | Auto-rotate pages | | skip_text | bool | Skip pages that already have text | | force_ocr | bool | Force OCR on all pages | | redo_ocr | bool | Replace existing OCR | | optimize | int | Optimization level (0-3) | | output_type | str | 'pdfa', 'pdf', 'auto', 'none' | | jobs | int | Number of parallel workers | | sidecar | str | Path for sidecar text file | | image_dpi | int | DPI for image inputs | | clean | bool | Clean pages with unpaper (OCR only) | | clean_final | bool | Clean pages and use in output | | remove_background | bool | Remove noisy backgrounds | | oversample | int | Oversample DPI for low-res images | | pages | str | Page range, e.g. '1,3,5-10' | | title | str | Output PDF title | | author | str | Output PDF author |

Integration example: Flask web service

from flask import Flask, request, send_file
import ocrmypdf
import tempfile
import os

app = Flask(__name__)

@app.route('/ocr', methods=['POST'])
def ocr_endpoint():
    """OCR a PDF via HTTP POST."""
    if 'file' not in request.files:
        return {'error': 'No file uploaded'}, 400

    uploaded = request.files['file']
    with tempfile.NamedTemporaryFile(suffix='.pdf', delete=False) as inp:
        uploaded.save(inp.name)
        out_path = inp.name.replace('.pdf', '_ocr.pdf')

    try:
        result = ocrmypdf.ocr(
            inp.name, out_path,
            language='eng',
            skip_text=True,
            optimize=2,
        )
        if result == ocrmypdf.ExitCode.ok:
            return send_file(out_path, as_attachment=True,
                             download_name='ocr_output.pdf')
        return {'error': f'OCR failed: {result}'}, 500
    finally:
        os.unlink(inp.name)
        if os.path.exists(out_path):
            os.unlink(out_path)

if __name__ == '__main__':
    app.run(port=5000)

Streamlit web UI

OCRmyPDF provides an optional Streamlit-based web UI:

pip install ocrmypdf[webservice]
# See OCRmyPDF docs for launching the web service

Plugin Ecosystem

OCRmyPDF's plugin interface allows replacing the OCR engine. Available plugins:

OCRmyPDF-EasyOCR

Replaces Tesseract with EasyOCR (PyTorch-based). GPU strongly recommended.

pip install ocrmypdf-easyocr

# Usage
ocrmypdf --plugin ocrmypdf_easyocr -l en input.pdf output.pdf

OCRmyPDF-PaddleOCR

Replaces Tesseract with PaddleOCR. Powerful GPU-accelerated engine.

pip install ocrmypdf-paddleocr

# Usage
ocrmypdf --plugin ocrmypdf_paddleocr input.pdf output.pdf

OCRmyPDF-AppleOCR

Replaces Tesseract with Apple Vision Framework. macOS only.

pip install ocrmypdf-appleocr

# Usage
ocrmypdf --plugin ocrmypdf_appleocr input.pdf output.pdf

paperless-ngx Integration

paperless-ngx uses OCRmyPDF internally for searchable document management. See paperless-ngx docs for configuration.

Custom Plugins

Create a custom OCR plugin by implementing the OCRmyPDF plugin interface:

# my_ocr_plugin.py
from ocrmypdf import OcrEngine, hookimpl

class MyOcrEngine(OcrEngine):
    """Custom OCR engine implementation."""

    @staticmethod
    def version():
        return "1.0.0"

    @staticmethod
    def creator_tag(options):
        return "MyOCR"

    def recognize(self, input_file, output_file, output_text, options):
        # Implement OCR logic here
        pass

@hookimpl
def get_ocr_engine():
    return MyOcrEngine()
# Use custom plugin
ocrmypdf --plugin my_ocr_plugin input.pdf output.pdf

Quick Reference

| Task | Code / Command | |------|----------------| | Python API basic | ocrmypdf.ocr('in.pdf', 'out.pdf') | | With options | ocrmypdf.ocr('in.pdf', 'out.pdf', language='eng', deskew=True) | | Check result | if result == ocrmypdf.ExitCode.ok: ... | | EasyOCR plugin | ocrmypdf --plugin ocrmypdf_easyocr in.pdf out.pdf | | PaddleOCR plugin | ocrmypdf --plugin ocrmypdf_paddleocr in.pdf out.pdf | | AppleOCR plugin | ocrmypdf --plugin ocrmypdf_appleocr in.pdf out.pdf |

Troubleshooting

  • Import error: Ensure pip install ocrmypdf in your Python environment.
  • Plugin not found: Check plugin is installed (pip install ocrmypdf-easyocr).
  • GPU not used (EasyOCR/PaddleOCR): Ensure CUDA/GPU drivers are installed.
  • Memory issues: Use jobs=1 for large files; process in batches.

References

  • OCRmyPDF API Reference
  • OCRmyPDF Plugin Interface
  • OCRmyPDF-EasyOCR
  • OCRmyPDF-PaddleOCR
  • OCRmyPDF-AppleOCR
  • paperless-ngx

国内适配

  • 支持中文文档和中文注释
  • 示例代码兼容国内开发环境
  • 提供中文 FAQ 和常见问题解答

能力边界

✅ 适用场景

  • 当你需要使用此技能对应的技术栈时
  • 当项目需要遵循最佳实践时
  • 当需要快速上手或深入理解核心概念时

⚠️ 需要注意

  • 复杂业务逻辑需要结合具体场景调整
  • 性能优化需要根据实际数据量评估

❌ 不适用场景

  • 不相关的技术栈或框架
  • 需要完全自定义的特殊场景

使用流程

Step 1: 环境准备

确保开发环境已安装必要的依赖和工具。

Step 2: 配置初始化

根据项目需求进行基础配置。

Step 3: 核心功能使用

按照示例代码实现核心功能。

Step 4: 测试验证

运行测试确保功能正常。

Step 5: 部署上线

完成开发后进行部署和监控。