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58 lines
2.0 KiB
Markdown
58 lines
2.0 KiB
Markdown
My OCR-D workflow
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=================
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[](https://travis-ci.org/mikegerber/my_ocrd_workflow)
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WIP. Given a OCR-D workspace with document images in the OCR-D-IMG file group,
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this workflow produces:
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* Binarized images
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* Line segmentation
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* OCR text (using Calamari and Tesseract, both with GT4HistOCR models)
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* (Given ground truth in OCR-D-GT-PAGE, also an OCR text evaluation report)
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If you're interested in the exact processors, versions and parameters, please take a look at the [script](my_ocrd_workflow) and possibly the [Dockerfile](Dockerfile) and the [requirements](requirements.txt).
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Goal
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----
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Provide a **test environment** to produce OCR output for historical prints, using OCR-D, especially [ocrd_calamari](https://github.com/OCR-D/ocrd_calamari) and [sbb_textline_detection](https://github.com/qurator-spk/sbb_textline_detection), including all dependencies in Docker.
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How to use
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----------
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It's easiest to use it as a pre-built container. To run the container on an
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example workspace:
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~~~
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# Download an example workspace
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cd /tmp
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wget https://qurator-data.de/examples/actevedef_718448162.first-page.zip
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unzip actevedef_718448162.first-page.zip
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# Run the workflow on it
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cd actevedef_718448162.first-page
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~/devel/my_ocrd_workflow/run-docker-hub
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~~~
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### Build the container yourself
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To build the container yourself using Docker:
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~~~
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cd ~/devel/my_ocrd_workflow
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./build
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~~~
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You may then use the script `run` to use your self-built container, analogous to
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the example above.
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### Viewing results
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You may then examine the results using
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[PRImA's PAGE Viewer](https://www.primaresearch.org/tools/PAGEViewer):
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~~~
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java -jar /path/to/JPageViewer.jar --resolve-dir . OCR-D-OCR-CALAMARI/OCR-D-OCR-CALAMARI_00000024.xml
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~~~
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The workflow also produces OCR evaluation reports using
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[dinglehopper](https://github.com/qurator-spk/dinglehopper), if ground truth was
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available:
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~~~
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firefox OCR-D-OCR-CALAMARI-EVAL/OCR-D-OCR-CALAMARI-EVAL_00000024.html
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~~~
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