Gerber, Mike
d8463e2ea7
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5 years ago | |
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| data@dcd3643917 | 5 years ago | |
| ocrd-bugs | 6 years ago | |
| xsd | 6 years ago | |
| .gitmodules | 6 years ago | |
| .travis.yml | 5 years ago | |
| Dockerfile | 5 years ago | |
| README.md | 5 years ago | |
| build | 5 years ago | |
| my_ocrd_workflow | 5 years ago | |
| ocrd_logging.py | 5 years ago | |
| qurator_data_lib.sh | 5 years ago | |
| requirements.txt | 5 years ago | |
| run | 5 years ago | |
README.md
My OCR-D workflow
WIP. Given a OCR-D workspace with document images in the OCR-D-IMG file group, this workflow produces:
- Binarized images
- Line segmentation
- OCR text (using Calamari and Tesseract, both with GT4HistOCR models)
- (Given ground truth in OCR-D-GT-PAGE, also an OCR text evaluation report)
If you're interested in the exact processors, versions and parameters, please take a look at the script and possibly the Dockerfile and the requirements.
Goal
Provide a test environment to produce OCR output for historical prints, using OCR-D, especially ocrd_calamari and sbb_textline_detection, including all dependencies in Docker.
How to use
It's easiest to use it as a container. To build the container using Docker:
cd ~/devel/my_ocrd_workflow
./build
To run the container on an example workspace:
# Download an example workspace
cd /tmp
wget https://qurator-data.de/examples/actevedef_718448162.first-page.zip
unzip actevedef_718448162.first-page.zip
# Run the workflow on it
cd actevedef_718448162.first-page
~/devel/my_ocrd_workflow/run
Viewing results
You may then examine the results using PRImA's PAGE Viewer:
java -jar /path/to/JPageViewer.jar --resolve-dir . OCR-D-OCR-CALAMARI/OCR-D-OCR-CALAMARI_00000024.xml
The workflow also produces OCR evaluation reports using dinglehopper, if ground truth was available:
firefox OCR-D-OCR-CALAMARI-EVAL/OCR-D-OCR-CALAMARI-EVAL_00000024.html