scanlayer

Scanned image or photographed document → searchable PDF, or raw OCR text/JSON/TSV/hOCR.

Turn a scanned image or photographed document into a searchable PDF, or export the raw OCR result as plain text, JSON, TSV, or hOCR. Use it as a command-line tool or as a Python library; both are the same engine underneath.

What it does

A scanned invoice, a phone photo of a letter, a stack of photographed pages: scanlayer runs it through Tesseract OCR and gives you back either:

• a searchable PDF: the original page image, with an invisible, precisely positioned text layer over it, so you can select and search text exactly where it visually appears, or
• the raw OCR result as txt, json, tsv, or hocr: text, per-word confidence, and bounding boxes, no PDF built at all.

Along the way it automatically straightens rotated/skewed pages, corrects uneven lighting, denoises and sharpens for OCR accuracy without touching what you actually see in the output, reconstructs correct reading order on genuine multi-column pages, and races several OCR configurations against each other to pick the most confident result.

See the feature catalog for the complete list, and Roadmap & Limitations for what's deliberately out of scope or not built yet.

Requirements

• Python 3.9+
• Tesseract OCR (a separate, system-level install, see below)
• poppler only if you feed scanlayer a native .pdf file directly

# Debian / Ubuntu
sudo apt install tesseract-ocr poppler-utils

# macOS (Homebrew)
brew install tesseract poppler

# Windows: Tesseract -> https://github.com/tesseract-ocr/tesseract/wiki
#          poppler    -> download a release, add its bin/ to PATH

Full detail, including how scanlayer locates the Tesseract binary automatically and how to bundle your own, is in Installation and Bundling Tesseract.

Install

pip install scanlayer

This installs the scanlayer console command and makes import scanlayer available anywhere on the machine.

Working on scanlayer itself, or want to run it straight from a checkout with no install at all?

git clone https://github.com/Hyacinthe-primus/scanlayer.git
cd scanlayer                        # the repo root, which contains requirements.txt
pip install -r requirements.txt
python -m scanlayer invoice.jpg -o invoice.pdf   # works with no install at all

See CONTRIBUTING.md for the full contributor setup (editable install and running the test suite).

Quick start

As a CLI:

scanlayer invoice.jpg -o invoice.pdf --lang fra+eng --dpi 300

As a library:

import scanlayer

result = scanlayer.convert("invoice.jpg", "invoice.pdf", lang="fra+eng", dpi=300)
print(f"{result.words_count} words, {result.mean_confidence:.1f}% confidence")

Every CLI flag and library keyword argument in this project are named to match each other (--lang ↔ lang=, --dpi ↔ dpi=, and so on), see Examples for every feature shown both ways, side by side, and CLI Reference / Library API for the complete details of each.

A few more common cases:

# Batch-convert a folder
scanlayer *.jpg -o ./converted/

# Merge several photographed pages into one searchable PDF
scanlayer page1.jpg page2.jpg page3.jpg -o report.pdf --merge

# Export raw OCR text/JSON instead of a PDF
scanlayer invoice.jpg -o invoice.json --format json

# See what OCR actually detected, color-coded by confidence
scanlayer invoice.jpg --debug-image

# Validate a batch before spending time on OCR: files exist,
# Tesseract reachable, output paths writable
scanlayer *.jpg -o ./converted/ --dry-run

import scanlayer

# Batch
result = scanlayer.convert_batch(["*.jpg"], "./converted/")

# Merge
scanlayer.convert_merge(["page1.jpg", "page2.jpg", "page3.jpg"], "report.pdf")

# Raw export
scanlayer.convert("invoice.jpg", "invoice.json", output_format="json")

Documentation

The site is published from the gh-pages branch at https://Hyacinthe-primus.github.io/scanlayer/. To browse it locally, open index.html in a gh-pages worktree (e.g. git worktree add <path> gh-pages); it has no build step or server-side dependency.

Repository layout

.
├── .github/           # FUNDING.yml
├── scanlayer/         # library source
│   ├── __init__.py
│   ├── __main__.py    # enables `python -m scanlayer`
│   ├── main.py        # public API: convert()/convert_batch()/convert_merge()
│   ├── config.py
│   ├── cli/           # argparse CLI: parser.py, run.py, dry_run.py
│   ├── fonts/         # bundled DejaVu Sans for the PDF text layer
│   ├── preprocessing/
│   ├── ocr/
│   ├── layout/
│   ├── pdf/
│   └── utils/
├── tests/             # pytest suite
├── pyproject.toml
├── requirements.txt
├── README.md
├── CONTRIBUTING.md
├── SECURITY.md
└── LICENSE.md

Contributing

Bug reports, fixes, and feature discussions are welcome: see CONTRIBUTING.md for how to set up a development environment and what to include in a pull request. There is a tests/ directory (now including utils/validators.py and the --dry-run flag, with cross-platform coverage for Tesseract discovery on Windows/macOS/Linux) and it runs with pytest, but no CI yet; see Roadmap & Limitations and the Adding tests section of the contributing guide for where coverage is thinnest.

License

MIT.