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) and programs from its free repositories: https://hub.docker.com/_/debian
- 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

1. Create input and output directories for the pipeline.
``` bash
mkdir -p /<my_data_location>/input /<my_data_location>/output
```

2. Place your PDF files inside `/<my_data_location>/input`. Files should all contain text of the same language.

3. Start the pipeline process. Check the [Pipeline arguments](#pipeline-arguments) section 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/1.0.0/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:1.0.0 \
        -i /input \
        -l <language_code>
        -o /output \
        <optional_pipeline_arguments>
```

4. Check your results in the `/<my_data_location>/output` directory.
```

### Pipeline arguments

`-l languagecode`
* Tells tesseract which language will be used.
* options = ara (Arabic), chi_tra (Chinese - Traditional), dan (Danish), deu (German), ell (Greek, Modern (1453-)), eng (English), enm (Middle englisch), fra (French), frk (German Fraktur), frm (Middle french), ita (Italian), por (Portuguese), rus (Russian), spa (Spanish)
* required = True

`--keep-intermediates`
* If set, all intermediate files created during the OCR process will be
kept.
* default = False
* required = False

`--nCores corenumber`
* Sets the number of CPU cores being used during the OCR process.
* default = min(4, multiprocessing.cpu_count())
* required = False

`--skip-binarisation`
* Used to skip binarization with ocropus. If skipped, only the tesseract binarization is used.
* default = False

``` bash
# Example with all arguments used
docker run \
    --rm \
    -it \
    -u $(id -u $USER):$(id -g $USER) \
    -v "$HOME"/ocr/input:/input \
    -v "$HOME"/ocr/output:/output \
    gitlab.ub.uni-bielefeld.de:4567/sfb1288inf/ocr:1.0.0 \
        -i /input \
        -l eng \
        -o /output \
        --keep_intermediates \
        --nCores 8 \
        --skip-binarisation
```