Skip to main content

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

  • Places OCR text accurately below the image to ease copy / paste

  • Keeps the exact resolution of the original embedded images

  • When possible, inserts OCR information as a “lossless” operation without rendering vector information

  • 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 pages in parallel when more than one CPU core is available

  • Uses Tesseract OCR engine

  • Supports the 39 languages recognized by Tesseract

  • Battle-tested on thousands of PDFs, a test suite and continuous integration

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/jbarlow83/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 VERBOSITYLEVEL 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

These instructions probably work on all Mac OS X versions later than 10.7 (Lion). OCRmyPDF is known to work on Yosemite and El Capitan, and regularly tested on El Capitan.

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

Sometimes, the Python imaging library (Pillow) can end up being compiled and installed without support for JPEG and PNG files. (Arguably, this is an unfixed bug in Pillow’s installer.) To confirm that Pillow is compiled correctly and 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 Python 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 on Windows

Direct installation on Windows is not possible. Install the Docker container as described above.

Installing HEAD revision from sources

If you have git and python3.4 or python3.5 installed, you can install from source. When the pip installer runs, it will alert you if dependencies are missing.

First, clone the HEAD revision:

git clone -b master https://github.com/jbarlow83/OCRmyPDF.git
cd OCRmyPDF

To install the HEAD revision from sources:

pip3 install .

Or, to install in development mode, allowing customization of OCRmyPDF, use the -e flag:

pip3 install -e .

On certain Linux distributions 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/jbarlow83/OCRmyPDF.git
pyvenv venv
source venv/bin/activate
cd OCRmyPDF
pip3 install .

However, ocrmypdf will only be accessible on the system PATH after you activate the virtual environment.

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/jbarlow83/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 Dropbox)

Press & Media

Disclaimer

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

Project details


Release history Release notifications | RSS feed

This version

3.2

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

ocrmypdf-3.2.tar.gz (19.6 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

ocrmypdf-3.2-py34-none-any.whl (27.6 kB view details)

Uploaded Python 3.4

File details

Details for the file ocrmypdf-3.2.tar.gz.

File metadata

  • Download URL: ocrmypdf-3.2.tar.gz
  • Upload date:
  • Size: 19.6 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for ocrmypdf-3.2.tar.gz
Algorithm Hash digest
SHA256 cff00b7564c619c241217d63dc8cdc824e426f203ffba2bd563140f11d922517
MD5 9592259f3b598e87b924dc8e2628bdd5
BLAKE2b-256 1c3c116f2030dc165d59acf37bcd3d8e632d6249d74efd590d22442337f8cae8

See more details on using hashes here.

File details

Details for the file ocrmypdf-3.2-py34-none-any.whl.

File metadata

File hashes

Hashes for ocrmypdf-3.2-py34-none-any.whl
Algorithm Hash digest
SHA256 95c1674772499532f8656315e629cb71118022f30f00cadcd2001d6572317eda
MD5 5dd6b7be4a5ec66973fda749b877df51
BLAKE2b-256 f9eac4cb6d98f9c5b06b0f81d7375ec3278c52be7289bda9ea016fa67eae632f

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page