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OCRmyPDF adds an OCR text layer to scanned PDF files, allowing them to be searched

Project description

OCRmyPDF adds an OCR text layer to scanned PDF files, allowing them to be searched.

Main features

  • Generates a searchable PDF/A file from a regular PDF only containing images
  • Places OCRed text accurately below the image to ease copy / paste
  • Keeps the exact resolution of the original embedded images
    • or if requested oversamples the images before OCRing so as to get better results
  • When possible, copies input images directly to output without transcoding them, to preserve image quality
  • Keeps file size about the same
  • If requested deskews and/or cleans the image before performing OCR
  • Validates input and output files
  • Provides debug mode to enable easy verification of the OCR results
  • Processes several pages in parallel when more than one CPU core is available
  • Uses Tesseract OCR engine

For details: please consult the release notes

Motivation

I searched the web for a free command line tool to OCR PDF files on Linux/UNIX: I found many, but none of them were really satisfying.

  • Either they produced PDF files with misplaced text under the image (making copy/paste impossible)
  • Or they did not display correctly some escaped HTML characters located in the hOCR file produced by the OCR engine
  • Or they changed the resolution of the embedded images
  • Or they generated PDF files having a ridiculous big size
  • Or they crashed when trying to OCR some of my PDF files
  • Or they did not produce valid PDF files (even though they were readable with my current PDF reader)
  • On top of that none of them produced PDF/A files (format dedicated for long time storage)

… so I decided to develop my own tool (using various existing scripts as an inspiration)

Installation

Download OCRmyPDF here: https://github.com/fritz-hh/OCRmyPDF/releases

You can install it to a Python virtual environment or system-wide.

Installing the Docker container

For many users, installing the Docker container will be easier than installing all of OCRmyPDF’s dependencies. For Windows, it is the only option.

If you have Docker installed on your system, you can install a Docker container of the latest release.

Follow the Docker installation instructions for your platform. If you can run this command successfully, your system is ready to download and execute the image:

docker run hello-world

OCRmyPDF will use all available CPU cores. By default, the VirtualBox machine instance on Windows and OS X has only a single CPU core enabled. Use the VirtualBox Manager to determine the name of your Docker container host, and then follow these optional steps to enable multiple CPUs:

# Optional
docker-machine stop "yourVM"
VBoxManage modifyvm "yourVM" --cpus 2  # or whatever number of core is desired
docker-machine start "yourVM"
eval $(docker-machine env "yourVM")

Assuming you have a Docker engine running somewhere, you can run these commands to download the image:

docker pull jbarlow83/ocrmypdf

Then tag it to give a more convenient name, just ocrmypdf:

docker tag jbarlow83/ocrmypdf ocrmypdf

You can then run using the command:

docker run ocrmypdf --help

To execute the OCRmyPDF on a local file, you must provide a writable volume to the Docker image, such as this in this template:

docker run -v "$(pwd):/home/docker" <other docker arguments>   ocrmypdf <your arguments to ocrmypdf>

In this worked example, the current working directory contains an input file called test.pdf and the output will go to output.pdf:

docker run -v "$(pwd):/home/docker"   ocrmypdf --skip-text test.pdf output.pdf

Note that ocrmypdf has its own separate -v argument to control debug verbosity. All Docker arguments should before the ocrmypdf container name and all arguments to ocrmypdf should be listed after.

Installing on Mac OS X Yosemite

If it’s not already present, install Homebrew

Update Homebrew:

brew update

Install or upgrade the required Homebrew packages, if any are missing:

brew install libpng openjpeg jbig2dec     # image libraries
brew install qpdf
brew install ghostscript
brew install python3
brew install libxml2
brew install leptonica
brew install tesseract

It is also recommended that install Pillow and confirm it can read and write JPEG and PNG files:

pip3 install --upgrade pip
pip3 install --upgrade pillow

To test that your Python imaging library (Pillow) can access JPEG and PNG files, try this command:

python3 -c "from PIL import Image; im = Image.new('1', (1, 1)); im.save('test.png'); im.save('test.jpg')"

If you have trouble getting Pillow to access JPEG and PNG files, review the installation instructions.

You can then install OCRmyPDF from PyPI:

pip3 install ocrmypdf

The command line program should now be available:

ocrmypdf --help

Installing on Ubuntu 14.04 LTS

Installing on Ubuntu 14.04 LTS (trusty) is more difficult than other options, because of certain bugs in package installation.

Update apt-get:

sudo apt-get update
sudo apt-get upgrade

Install system dependencies:

sudo apt-get install \
   zlib1g-dev \
   libjpeg-dev \
   ghostscript \
   tesseract-ocr \
   qpdf \
   unpaper \
   python3-pip \
   python3-pil \
   python3-pytest \
   python3-reportlab

If you wish install OCRmyPDF to the system Python, then install as follows (note this installs new packages into your system Python, which could interfere with other programs):

sudo pip3 install ocrmypdf

If you wish to install OCRmyPDF to a virtual environment to isolate system Python from modified, you can follow these steps. This includes a workaround for a known, unresolved issue in Ubuntu 14.04’s ensurepip package:

sudo apt-get install python3-venv
python3 -m venv venv-ocrmypdf --without-pip
source venv-ocrmypdf/bin/activate
wget -O - -o /dev/null https://bootstrap.pypa.io/get-pip.py | python
deactivate
pyvenv --system-site-packages venv-ocrmypdf
source venv-ocrmypdf/bin/activate
pip install ocrmypdf

Ubuntu 14.04 only installs unpaper version 0.4.2, which is not supported by OCRmyPDF because it is produces invalid output. This program is an optional dependency, and provides page deskewing and cleaning. See Dockerfile for an example of how to building unpaper 6.1 from source. If you choose to install unpaper later, OCRmyPDF will use the foremost version on the system PATH.

Installing HEAD revision from sources

To install the HEAD revision from sources in development mode:

git clone -b master https://github.com/fritz-hh/OCRmyPDF.git
cd OCRmyPDF
pip3 install -e .

On certain Linux/UNIX platforms such as Ubuntu, you may need to use run the install command as superuser:

sudo pip3 install -e .

Note that this will alter your system’s Python distribution. If you prefer to not install as superuser, you can install the package in a Python virtual environment:

git clone -b master https://github.com/fritz-hh/OCRmyPDF.git
pyvenv venv
source venv/bin/activate
cd OCRmyPDF
pip3 install -e .

If your platform does not have pip3, make sure that Python 3.4+ and the pip package are installed.

To run the program:

ocrmypdf --help

If not yet installed, the script will notify you about dependencies that need to be installed. The script requires specific versions of the dependencies. Older version than the ones mentioned in the release notes are likely not to be compatible to OCRmyPDF.

Support

In case you detect an issue, please:

  • Check if your issue is already known
  • If no problem report exists on github, please create one here: https://github.com/fritz-hh/OCRmyPDF/issues
  • Describe your problem thoroughly
  • Append the console output of the script when running the debug mode (-v 1 option)
  • If possible provide your input PDF file as well as the content of the temporary folder (using a file sharing service like www.file-upload.net)

Press & Media

Disclaimer

The software is distributed on an “AS IS” BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.

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