Xournal++ Searchable PDF OCR Export Plugin

A high-performance Xournal++ plugin that exports .xopp documents to searchable PDFs with embedded OCR text layers. Combines Windows Digital Ink handwriting recognition and WinRT Neural OCR for printed images/screenshots.

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✨ Features

• Dual-Engine Recognition:
  • Windows Digital Ink Analyzer: Extracts exact vector strokes from .xopp to recognize handwritten notes and mathematical/code symbols accurately.
  • WinRT Neural OCR: Scans embedded screenshots, diagrams, and inserted images across all pages.
• Fast Multi-Core Processing: Runs parallel OCR workers across available CPU cores via ThreadPoolExecutor.
• Non-Blocking UI: Exports run in a detached process, keeping Xournal++ responsive with no freezing.
• Real-Time Terminal Dashboard: Visual ASCII progress bar and execution metrics.
• Searchable PDF Output: Embeds an invisible text layer (render_mode=3) so you can search notes using Ctrl + F in Adobe Acrobat, PDF-XChange, Edge, or Chrome.

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🖥️ Terminal Preview

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  ─────────────────────────────────────────────────────────────────────────────
  DOCUMENT: Lecture_Notes.xopp
  ENGINE  : Windows Digital Ink + WinRT Neural OCR + PyMuPDF
  ─────────────────────────────────────────────────────────────────────────────

  [1/4] Exporting base vector PDF from Xournal++...  DONE
  [2/4] Extracting handwriting stroke coordinates... DONE
  [3/4] Rasterizing 12 page(s) for visual OCR...     DONE
  [4/4] Executing parallel neural OCR (4 threads)...

  › OCR Processing ████████████████████░░░░░░░░  66.7% [8/12] page 7 ready

  › Embedding invisible searchable text layer...

  ┌───────────────────────────────────────────────────────────────────────────┐
  │  EXPORT COMPLETE                                                          │
  ├───────────────────────────────────────────────────────────────────────────┤
  │  Pages Processed : 12                                                     │
  │  Text Embedded   : 342                                                    │
  │  Time Elapsed    : 4.82s                                                  │
  │  Saved Location  : C:\Users\User\Documents\Lecture_Notes.pdf              │
  └───────────────────────────────────────────────────────────────────────────┘

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📋 Prerequisites

1. Windows 10 / 11 (64-bit)
2. Xournal++ (v1.1.0 or higher)
3. Python 3.8+ added to your system PATH
4. PyMuPDF:

   pip install pymupdf

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🚀 Installation

Option 1: Automatic (One-Click)

1. Clone or download this repository.
2. Double-click install.bat.
3. The installer will automatically verify dependencies and copy the plugin to %LOCALAPPDATA%\xournalpp\plugins\ExportOCR.

Option 2: Manual Installation

1. Clone this repository:

   git clone https://github.com/your-username/xournalpp-export-ocr.git

2. Copy the ExportOCR folder into your local Xournal++ plugins directory:

   C:\Users\<YourUsername>\AppData\Local\xournalpp\plugins\ExportOCR
   

3. Install Python dependencies:

   pip install -r requirements.txt

4. Restart Xournal++.

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🎯 How to Use

1. Open Xournal++ and write your notes or open any .xopp file.
2. Save your document (Ctrl + S).
3. Export with OCR by:
   • Pressing Shift + Alt + O
   • Or selecting Plugin → Export with OCR (Searchable PDF) from the top menu bar.
4. The terminal window will open and display live progress.
5. Once finished, open the exported .pdf and press Ctrl + F to search your handwritten notes!

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🛠️ Project Structure

xournalpp-export-ocr/
├── ExportOCR/
│   ├── plugin.ini                     # Plugin manifest
│   ├── main.lua                       # Lua menu entry & hotkey handler
│   └── helper/
│       ├── super_ocr.py               # Parallel OCR orchestrator & ASCII UI
│       ├── ocr_helper.ps1             # WinRT Optical Character Recognition
│       ├── inkanalyzer_helper.ps1     # Windows Ink handwriting stroke analysis
│       ├── process_pdf.py             # Standalone PDF processor
│       └── watch_folder.ps1           # Auto-OCR watcher utility
├── install.bat                        # Automated Windows installer
├── requirements.txt                   # Python requirements
├── LICENSE                            # MIT License
└── README.md                          # Documentation

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📄 License

This project is licensed under the MIT License.