tess-pdfseq

Configurable OCR for documents in any language. Built with Tesseract and optimized for PDF processing.

Features

• Process PDFs with high accuracy
• Support for any language Tesseract supports
• Memory efficient processing
• Optional GPU acceleration via OpenCV
• Graceful fallback to CPU processing
• Docker-based deployment
• 7z archive support for batch processing

Quick Start

# Build with default language (English)
docker build -t tess-pdfseq .

# Process a 7z archive (CPU mode)
./bin/pdfseq input.7z

# Process with GPU acceleration
GPU=1 ./bin/pdfseq input.7z

# Process with custom settings
LANGS="eng+ara" DPI=300 WIDTH=2400 GPU=1 ./bin/pdfseq docs.7z

Configuration

Shell Script Options

Environment variables for bin/pdfseq:

• LANGS: OCR languages (default: eng)
• DPI: PDF scan resolution (default: 500)
• WIDTH: Target width in pixels (default: 1800)
• MAX_PAGES: Max pages per PDF (default: 3)
• WORKDIR: Working directory (default: current directory)
• GPU: Enable GPU acceleration (default: 0)
• TAG: Docker image tag (default: latest)

Languages

First, install languages during Docker build (plus-separated):

# Build with multiple languages available
docker build -t tess-pdfseq --build-arg TESS_LANGS="eng+fas+ara" .

Then use any of the installed languages at runtime:

# Use English (default)
./bin/pdfseq docs.7z

# Use Persian/Farsi
LANGS=fas ./bin/pdfseq docs.7z

# Use multiple languages together
LANGS="eng+fas" ./bin/pdfseq docs.7z

Note: You can only use languages at runtime that were installed during build.

List available languages:

# On Arch Linux
pacman -Ss tesseract-data | grep -Po 'tesseract-data-\K[^/\s]*(?=\s)'

# Using Docker
docker run --rm python:3.12-alpine sh -c \
  "apk add --no-cache tesseract-ocr && tesseract --list-langs"

Common languages:

• eng - English
• heb - Hebrew
• jpn - Japanese
• kor - Korean
• rus - Russian
• fas - Persian/Farsi
• chi_sim - Chinese Simplified

Processing

• Optimizes images for OCR (1800px width)
• GPU acceleration with OpenCV UMat when enabled
• Automatic fallback to CPU if GPU fails
• Outputs plain text files

Requirements

• Docker (GPU support optional)
• NVIDIA Container Toolkit for GPU support
• ~1GB disk space for Docker image
• p7zip for archive handling

Development

git clone /~https://github.com/metaory/tess-pdfseq
cd tess-pdfseq

# Build with custom languages
docker build -t tess-pdfseq --build-arg TESS_LANGS="eng+ara" .

License

MIT