https://github.com/ocr-d/ocrd_kraken
Wrapper for the kraken OCR engine
https://github.com/ocr-d/ocrd_kraken
ocr-d
Last synced: about 1 year ago
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Wrapper for the kraken OCR engine
- Host: GitHub
- URL: https://github.com/ocr-d/ocrd_kraken
- Owner: OCR-D
- License: apache-2.0
- Created: 2018-04-13T08:19:18.000Z (about 8 years ago)
- Default Branch: master
- Last Pushed: 2025-03-12T16:48:20.000Z (over 1 year ago)
- Last Synced: 2025-03-24T11:38:27.705Z (about 1 year ago)
- Topics: ocr-d
- Language: Python
- Size: 257 KB
- Stars: 13
- Watchers: 4
- Forks: 6
- Open Issues: 3
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- License: LICENSE
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README
# ocrd_kraken
> OCR-D wrapper for the Kraken OCR engine
[](https://github.com/OCR-D/ocrd_kraken/actions/workflows/ci.yml)
[](https://hub.docker.com/r/ocrd/kraken/tags/)
[](https://circleci.com/gh/OCR-D/ocrd_kraken)
## Introduction
This package offers [OCR-D](https://ocr-d.de/en/spec) compliant [workspace processors](https://ocr-d.de/en/spec/cli)
for (some of) the functionality of [Kraken](https://kraken.re).
(Each processor is a parameterizable step in a configurable [workflow](https://ocr-d.de/en/workflows)
of the [OCR-D functional model](https://ocr-d.de/en/about).
There are usually various alternative processor implementations for each step.
Data is represented with [METS](https://ocr-d.de/en/spec/mets) and [PAGE](https://ocr-d.de/en/spec/page).)
It includes image preprocessing (binarization), layout analysis (region and line+baseline segmentation), and text recognition.
## Installation
### With Docker
This is the best option if you want to run the software in a container.
You need to have [Docker](https://docs.docker.com/install/linux/docker-ce/ubuntu/)
docker pull ocrd/kraken
To run with Docker:
docker run --rm \
-v path/to/workspaces:/data \
-v path/to/models:/usr/local/share/ocrd-resources \
ocrd/kraken ocrd-kraken-recognize ...
# or ocrd-kraken-segment or ocrd-kraken-binarize
### Native, from PyPI
This is the best option if you want to use the stable, released version.
pip install ocrd_kraken
### Native, from git
Use this option if you want to change the source code or install the latest, unpublished changes.
We strongly recommend to use [venv](https://packaging.python.org/guides/installing-using-pip-and-virtual-environments/).
git clone https://github.com/OCR-D/ocrd_kraken
cd ocrd_kraken
sudo make deps-ubuntu # or manually from git or via ocrd_all
make deps # or pip install -r requirements.txt
make install # or pip install .
## Models
Kraken uses data-driven (neural) models for segmentation and recognition, but comes with no pretrained "official" models.
There is a [public repository](https://zenodo.org/communities/ocr_models) of community-provided models, which can also
be queried and downloaded from via `kraken` standalone CLI.
(See [Kraken docs](https://kraken.re/master/advanced.html#repo) for details.)
For the OCR-D wrapper, since all OCR-D processors must resolve file/data resources in a [standardized way](https://ocr-d.de/en/spec/cli#processor-resources), there is a general mechanism for managing models, i.e. installing and using them by name. We currently manage our own list of recommended models (without delegating to the above repo).
Models always use the filename suffix `.mlmodel`, but are just loaded by their basename.
See the [OCR-D model guide](https://ocr-d.de/en/models) and
ocrd resmgr --help
## Usage
For details, see docstrings in the individual processors and [ocrd-tool.json](ocrd_tesserocr/ocrd-tool.json) descriptions,
or simply `--help`.
Available [OCR-D processors](https://ocr-d.de/en/spec/cli) are:
- [ocrd-kraken-binarize](ocrd_kraken/binarize.py) (nlbin – not recommended)
- adds `AlternativeImage` files (per page, region or line) to the output fileGrp
- [ocrd-kraken-segment](ocrd_kraken/segment.py) (all-in-one segmentation – recommended for handwriting and simply layouted prints, or as pure line segmentation)
- adds `TextRegion`s to `Page` (if `level-of-operation=page`) or `TableRegion`s (if `table`)
- adds `TextLine`s (with `Baseline`) to `TextRegion`s (for all `level-of-operation`)
- masks existing segments during detection (unless `overwrite_segments`)
- [ocrd-kraken-recognize](ocrd_kraken/recognize.py) (benefits from annotated `Baseline`s, falls back to center-normalized bboxes)
- adds `Word`s to `TextLine`s
- adds `Glyph`s to `Word`s
- adds `TextEquiv` (removing existing `TextEquiv` if `overwrite_text`)
## Testing
make test
This downloads test data from https://github.com/OCR-D/assets under `repo/assets`, and runs some basic tests of the Python API.
Set `PYTEST_ARGS="-s --verbose"` to see log output (`-s`) and individual test results (`--verbose`).