This controls installation of all OCR-D modules from source (as git submodules).
It includes a Makefile for their installation into a virtual environment (venv) or Docker container.
(A venv is a local user directory with shell scripts to load/unload itself in the current shell environment via PATH and PYTHONHOME.)
(NOTE: If you are going to install ocrd_all, you may want to first reference the OCR-D setup guide at the OCR-D website. If you are a non-IT user, it is especially recommended you utilize the guide.)
Make sure that there is enough free disk space. 7 GiB or more is recommended for the required submodules, build data, temporary data, installed virtual environment and pip cache.
If the /tmp
directory has less than 5 GiB of free space, you can override the location
of temporary files by setting the TMPDIR
variable when calling make:
TMPDIR=/path/to/my/tempdir make all
Next, the (shell) environment must have a Unicode-based localization. (Otherwise Python code based on click
will not work, i.e. most OCR-D CLIs.) This is true for most installations today, and can be verified by:
locale | fgrep .UTF-8
This should show several LC_*
variables. Otherwise, either select another localization globally...
sudo dpkg-reconfigure locales
... or use the Unicode-based POSIX locale temporarily:
export LC_ALL=C.UTF-8
export LANG=C.UTF-8
Install GNU make, git and GNU parallel.
# on Debian / Ubuntu:
sudo apt install make git parallel
Install wget or curl if you want to download Tesseract models.
# on Debian / Ubuntu:
sudo apt install wget
Install the packages for Python3 development and for Python3 virtual environments for your operating system / distribution.
# on Debian / Ubuntu:
sudo apt install python3-dev python3-venv
Some modules use the Tesseract library. If your distribution provides Tesseract 4.1 or newer, install the development package:
# on Debian / Ubuntu:
sudo apt install libtesseract-dev
Ubuntu packages for Tesseract 5.0.0 (alpha) are available at the PPA https://launchpad.net/~alex-p/+archive/ubuntu/tesseract-ocr-devel.
Otherwise or for the latest Tesseract code it can also be built locally.
Other modules will have additional system dependencies.
System dependencies for all modules on Ubuntu 18.04 (or similar) can also be installed automatically by running:
# on Debian / Ubuntu:
sudo apt install make
sudo make deps-ubuntu
(And you can define the scope of all modules by setting the OCRD_MODULES
variable.)
Run make
with optional parameters for variables and targets like so:
make [PYTHON=python3] [VIRTUAL_ENV=./venv] [OCRD_MODULES="..."] [TARGET...]
Install system packages for all modules. (Depends on modules.)
Download/update all modules, but do not install anything.
Install executables from all modules into the venv. (Depends on modules and ocrd.)
Install only OCR-D/core and its CLI ocrd
into the venv.
(Re-)build a docker image for all modules/executables. (Depends on modules.)
Remove the venv and the modules' build directories.
Print the venv directory, the module directories, and the executable names.
Verify that all executables are runnable and the venv is consistent.
Print available targets and variables.
Further targets:
Download/update that module, but do not install anything.
Install that CLI into the venv. (Depends on that module and on ocrd.)
Override the list of git submodules to include. Targets affected by this include:
- deps-ubuntu (reducing the list of system packages to install)
- modules (reducing the list of modules to checkout/update)
- all (reducing the list of executables to install)
- docker (reducing the list of executables and modules to install)
- show (reducing the list of
OCRD_MODULES
and ofOCRD_EXECUTABLES
to print)
Name of the Python binary to use (at least python3 required).
Directory prefix to use for local installation.
(This is set automatically when activating a virtual environment on the shell. The build system will re-use the venv if one already exists here, or create one.)
Override the default path (/tmp
on Unix) where temporary files during build are stored.
Add extra options to the pip install
command like -q
or -v
or -e
.
(The latter will install Python modules in editable mode, i.e. any update to the source will directly affect the executables.)
Set to --recursive
to checkout/update all modules recursively. (This usually installs additional tests and models.)
Add more models to the minimum required list of languages (eng equ osd
) to install along with Tesseract.
Note: this only affects make install-tesseract
(or all
), but is independent of the install-models
step.
(The latter delegates to ocrd resmgr download
, which fetches all registered resources.)
Set configure
options for building Tesseract from source (--disable-openmp --disable-shared CXXFLAGS="-g -O2 -fPIC"
).
The following examples assume a working development installation of Tesseract. To build the latest Tesseract locally, run this command first:
# Get code, build and install Tesseract with the default English model.
make tesseract
Optionally install additional Tesseract models.
# Download models from tessdata_fast into the venv's tessdata directory.
make frk.traineddata
make script/Latin.traineddata
make script/Fraktur.traineddata
Optionally install Tesseract training tools.
make install-tesseract-training
Running make ocrd
or just make
downloads/updates and installs the core
module,
including the ocrd
CLI in a virtual Python 3 environment under ./venv
.
Running make ocrd-tesserocr-recognize
downloads/updates the ocrd_tesserocr
module
and installs its CLIs, including ocrd-tesserocr-recognize
in the venv.
Running make modules
downloads/updates all modules.
Running make all
additionally installs the executables from all modules.
Running make all OCRD_MODULES="core tesseract ocrd_tesserocr ocrd_cis"
installs only the executables from these modules.
To use the built executables, simply activate the virtual environment:
. ${VIRTUAL_ENV:-venv}/bin/activate
ocrd --help
ocrd-...
For the Docker image, run it with your data path mounted as a user:
docker run -it -u $(id -u):$(id -g) -v $PWD:/data ocrd/all
ocrd --help
ocrd-...
In order to make choices permanent, you can put your variable preferences
(or any custom rules) into local.mk
. This file is always included if it exists.
So you don't have to type (and memorise) them on the command line or shell environment.
For example, its content could be:
# restrict everything to a subset of modules
OCRD_MODULES = core ocrd_im6convert ocrd_cis ocrd_tesserocr tesserocr tesseract
# use a non-default path for the virtual environment
VIRTUAL_ENV = $(CURDIR)/.venv
# install in editable mode (i.e. referencing the git sources)
PIP_OPTIONS = -e
# use non-default temporary storage
TMPDIR = $(CURDIR)/.tmp
# install more languages/models for Tesseract
TESSERACT_MODELS = deu frk script/Fraktur script/Latin
# install all of Tesseract's submodules to support unit tests and training tools, too
tesseract: GIT_RECURSIVE = --recursive
Note: When local.mk
exists, variables can still be overridden on the command line,
(i.e. make all OCRD_MODULES=
will build all executables for all modules again),
but not from the shell environment
(i.e. OCRD_MODULES= make all
will still use the value from local.mk).
The project is available as prebuilt Docker images from Docker Hub as
ocrd/all
. You can choose from three tags,
minimum
, medium
and maximum
. These differ in which modules are included,
with maximum
being the equivalent of doing make all
with the default (unset) value for OCRD_MODULES
. To download the images
on the command line:
docker pull ocrd/all:minimum
# or
docker pull ocrd/all:medium
# or
docker pull ocrd/all:maximum
In addition to these base variants, there are minimum-cuda
, medium-cuda
and maximum-cuda
with GPU support. (Also needs nvidia-docker, which adds the docker --gpus
option.)
Usage is the same as if you had built the image yourself.
This table lists which tag contains which module:
Module | minimum |
medium |
maximum |
---|---|---|---|
core | ☑ | ☑ | ☑ |
ocrd_cis | ☑ | ☑ | ☑ |
ocrd_fileformat | ☑ | ☑ | ☑ |
ocrd_im6convert | ☑ | ☑ | ☑ |
ocrd_pagetopdf | ☑ | ☑ | ☑ |
ocrd_repair_inconsistencies | ☑ | ☑ | ☑ |
ocrd_tesserocr | ☑ | ☑ | ☑ |
ocrd_wrap | ☑ | ☑ | ☑ |
tesserocr | ☑ | ☑ | ☑ |
workflow-configuration | ☑ | ☑ | ☑ |
cor-asv-ann | - | ☑ | ☑ |
dinglehopper | - | ☑ | ☑ |
format-converters | - | ☑ | ☑ |
ocrd_calamari | - | ☑ | ☑ |
ocrd_keraslm | - | ☑ | ☑ |
ocrd_olahd_client | - | ☑ | ☑ |
ocrd_olena | - | ☑ | ☑ |
ocrd_segment | - | ☑ | ☑ |
tesseract | - | ☑ | ☑ |
ocrd_anybaseocr | - | - | ☑ |
ocrd_kraken | - | - | - |
ocrd_ocropy | - | - | - |
ocrd_pc_segmentation | - | - | ☑ |
ocrd_typegroups_classifier | - | - | ☑ |
sbb_binarization | - | - | ☑ |
sbb_textline_detector | - | - | ☑ |
cor-asv-fst | - | - | - |
Note: The following modules have been disabled by default and can only be
enabled by explicitly setting OCRD_MODULES
or DISABLED_MODULES
:
- cor-asv-fst (runtime issues)
- ocrd_ocropy (better implementation in ocrd_cis available)
- ocrd_kraken (currently unmaintained)
- clstm (required only for ocrd_kraken)
If you have installed ocrd_all natively and wish to uninstall, first deactivate
the virtual environment and remove the ocrd_all
directory:
rm -rf ocrd_all
Next, remove all contents under ~/.parallel/semaphores:
rm -rf ~/.parallel/semaphores
This repo offers solutions to the following problems with OCR-D integration.
The following Python modules need an installation from code for different reasons:
- clstm (needs modified code for Python3)
- cor-asv-ann (not available in PyPI)
- cor-asv-fst (not available in PyPI)
- dinglehopper (not available in PyPI)
- tesserocr (too old in PyPI)
(Solved by installation from source.)
Merging all packages into one venv does not always work. Modules may require mutually exclusive sets of dependent packages.
pip
does not even stop or resolve conflicts – it merely warns!
-
Tensorflow:
- version 2 (required by ocrd_calamari, ocrd_anybaseocr and ocrd_pc_segmentation)
- version 1 (required by cor-asv-ann, ocrd_keraslm and sbb_textline_detector)
The temporary solution is to require different package names:
tensorflow>=2
tensorflow-gpu==1.15.*
Both cannot be installed in parallel in different versions, and usually also depend on different versions of CUDA toolkit.)
-
OpenCV:
opencv-python-headless
(required by core and others, avoids pulling in X11 libraries)opencv-python
(probably dragged in by third party packages)
As long as we keep reinstalling the headless variant and no such package attempts GUI, we should be fine. Custom build (as needed for ARM) under the module
opencv-python
already creates the headless variant. -
PyTorch:
torch<1.0
torch>=1.0
-
...
(Solved by managing and delegating to different subsets of venvs.)
Not all modules advertise their system package requirements via make deps-ubuntu
.
clstm
: depends onscons libprotobuf-dev protobuf-compiler libpng-dev libeigen3-dev swig
tesseract
(when installing from source not PPA): depends onlibleptonica-dev
etc
(Solved by maintaining these requirements under deps-ubuntu
here.)
Please see our contributing guide to learn how you can support the project.
This software uses GNU parallel. GNU Parallel is a general parallelizer to run multiple serial command line programs in parallel without changing them.
Tange, Ole. (2020). GNU Parallel 20200722 ('Privacy Shield'). Zenodo. https://doi.org/10.5281/zenodo.3956817