ocrmypdf-batch

OCRmyPDF batch processing skill — process multiple PDFs, Docker automation, shell scripting, and CI/CD integration. Use when the user needs to OCR many PDFs, set up automated OCR pipelines, or integrate OCR into workflows.

261 stars

Best use case

ocrmypdf-batch is best used when you need a repeatable AI agent workflow instead of a one-off prompt. It is especially useful for teams working in multi. OCRmyPDF batch processing skill — process multiple PDFs, Docker automation, shell scripting, and CI/CD integration. Use when the user needs to OCR many PDFs, set up automated OCR pipelines, or integrate OCR into workflows.

OCRmyPDF batch processing skill — process multiple PDFs, Docker automation, shell scripting, and CI/CD integration. Use when the user needs to OCR many PDFs, set up automated OCR pipelines, or integrate OCR into workflows.

Users should expect a more consistent workflow output, faster repeated execution, and less time spent rewriting prompts from scratch.

Practical example

Example input

Use the "ocrmypdf-batch" skill to help with this workflow task. Context: OCRmyPDF batch processing skill — process multiple PDFs, Docker automation, shell scripting, and CI/CD integration. Use when the user needs to OCR many PDFs, set up automated OCR pipelines, or integrate OCR into workflows.

Example output

A structured workflow result with clearer steps, more consistent formatting, and an output that is easier to reuse in the next run.

When to use this skill

  • Use this skill when you want a reusable workflow rather than writing the same prompt again and again.

When not to use this skill

  • Do not use this when you only need a one-off answer and do not need a reusable workflow.
  • Do not use it if you cannot install or maintain the related files, repository context, or supporting tools.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/ocrmypdf-batch/SKILL.md --create-dirs "https://raw.githubusercontent.com/partme-ai/full-stack-skills/main/skills/ocrmypdf-skills/ocrmypdf-batch/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/ocrmypdf-batch/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How ocrmypdf-batch Compares

Feature / Agentocrmypdf-batchStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

OCRmyPDF batch processing skill — process multiple PDFs, Docker automation, shell scripting, and CI/CD integration. Use when the user needs to OCR many PDFs, set up automated OCR pipelines, or integrate OCR into workflows.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

SKILL.md Source

# OCRmyPDF — Batch Processing Guide

## Overview

[OCRmyPDF](https://github.com/ocrmypdf/OCRmyPDF) supports batch processing through shell scripting, Docker, and CI/CD integration for automated OCR pipelines.

For core OCR functionality, see the **ocrmypdf** skill. For image processing, see **ocrmypdf-image**. For optimization, see **ocrmypdf-optimize**.

## Shell Loop

### Basic batch

```bash
# Process all PDFs in directory
for f in *.pdf; do
    ocrmypdf "$f" "output/$f"
done
```

### Parallel processing

```bash
# Use GNU parallel for faster processing
parallel ocrmypdf {} output/{/} ::: *.pdf

# Limit to 4 concurrent jobs
parallel -j 4 ocrmypdf {} output/{/} ::: *.pdf
```

### Recursive batch

```bash
# Process all PDFs in directory tree
find . -name "*.pdf" -exec ocrmypdf {} output/{/} \;
```

## Docker

### Official image

```bash
# Pull image
docker pull jbarlow83/ocrmypdf

# Basic usage
docker run --rm \
    -v $(pwd):/data \
    jbarlow83/ocrmypdf \
    input.pdf output.pdf
```

### Batch with Docker

```bash
# Process all PDFs
docker run --rm \
    -v $(pwd):/data \
    jbar65t83/ocrmypdf \
    ocrmypdf /data/input/*.pdf /data/output/
```

### Docker Compose

```yaml
version: '3'
services:
  ocrmypdf:
    image: jbarlow83/ocrmypdf
    volumes:
      - ./input:/data/input
      - ./output:/data/output
    command: sh -c "for f in /data/input/*.pdf; do ocrmypdf \"$f\" \"/data/output/$(basename $f)\"; done"
```

## GitHub Actions

```yaml
name: OCR PDFs
on: [push]
jobs:
  ocr:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - name: Run OCR
        run: |
          docker run --rm \
            -v ${{ github.workspace }}:/data \
            jbarlow83/ocrmypdf \
            sh -c "for f in /data/*.pdf; do ocrmypdf \"$f\" \"/data/output/$(basename $f)\"; done"
```

## CI/CD Examples

### GitLab CI

```yaml
ocr:
  image: jbarlow83/ocrmypdf
  script:
    - mkdir -p output
    - for f in *.pdf; do ocrmypdf "$f" "output/$f"; done
  artifacts:
    paths:
      - output/
```

### Shell script template

```bash
#!/bin/bash
INPUT_DIR="input"
OUTPUT_DIR="output"
LANG="eng+chi_sim"

mkdir -p "$OUTPUT_DIR"

for pdf in "$INPUT_DIR"/*.pdf; do
    filename=$(basename "$pdf")
    echo "Processing: $filename"
    ocrmypdf -l "$LANG" --deskew --remove-bordering "$pdf" "$OUTPUT_DIR/$filename"
    echo "Done: $filename"
done

echo "Batch OCR complete!"
```

## Error Handling

```bash
# Continue on error, log failures
for f in *.pdf; do
    if ! ocrmypdf "$f" "output/$f" 2>&1; then
        echo "FAILED: $f" >> failed.log
    fi
done
```

## Performance Tips

- Use `--jobs N` for multi-core processing
- Use `--output-type pdf` (not pdfa) for faster processing when archival not needed
- Pre-process images with `--deskew` and `--clean` to reduce file size
- Use Docker layer caching in CI/CD for faster rebuilds

## Quick Reference

| Task | Command |
|------|---------|
| Sequential batch | `for f in *.pdf; do ocrmypdf "$f" out/"$f"; done` |
| Parallel batch | `parallel ocrmypdf {} out/{/} ::: *.pdf` |
| Docker basic | `docker run -v $(pwd):/data jbarlow83/ocrmypdf in.pdf out.pdf` |
| Recursive | `find . -name "*.pdf" -exec ocrmypdf {} out/{/} \;` |

## Troubleshooting

- **Permission denied**: Ensure output directory is writable.
- **Memory issues**: Process in smaller batches or use `--jobs 1`.
- **Docker path issues**: Use absolute paths with `-v`.

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