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wrapper | ||
.gitlab-ci.yml | ||
Dockerfile | ||
hocrtotei | ||
ocr | ||
README.md |
OCR - Optical Character Recognition
This software implements a heavily parallelized pipeline to recognize text in PDF files. It is used for nopaque's OCR service but you can also use it standalone, for that purpose a convenient wrapper script is provided.
Software used in this pipeline implementation
- Official Debian Docker image (buster-slim): https://hub.docker.com/_/debian
- Software from Debian Buster's free repositories
- ocropy (1.3.3): https://github.com/ocropus/ocropy/releases/tag/v1.3.3
- pyFlow (1.1.20): https://github.com/Illumina/pyflow/releases/tag/v1.1.20
- Tesseract OCR (4.1.1): https://github.com/tesseract-ocr/tesseract/releases/tag/4.1.1
- tessdata_best (4.1.0): https://github.com/tesseract-ocr/tessdata_best/releases/tag/4.1.0
Use this image
- Create input and output directories for the pipeline.
mkdir -p /<my_data_location>/input /<my_data_location>/output
-
Place your PDF files inside
/<my_data_location>/input
. Files should all contain text of the same language. -
Start the pipeline process. Check the pipeline help (
ocr --help
) for more details.
# Option one: Use the wrapper script
## Install the wrapper script (only on first run). Get it from https://gitlab.ub.uni-bielefeld.de/sfb1288inf/ocr/-/raw/development/wrapper/ocr, make it executeable and add it to your ${PATH}
cd /<my_data_location>
ocr -i input -l <language_code> -o output <optional_pipeline_arguments>
# Option two: Classic Docker style
docker run \
--rm \
-it \
-u $(id -u $USER):$(id -g $USER) \
-v /<my_data_location>/input:/input \
-v /<my_data_location>/output:/output \
gitlab.ub.uni-bielefeld.de:4567/sfb1288inf/ocr:development \
-i /ocr_pipeline/input \
-l <language_code> \
-o /ocr_pipeline/output \
<optional_pipeline_arguments>
- Check your results in the
/<my_data_location>/output
directory.