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First work on version 1.0.0
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Dockerfile
42
Dockerfile
@ -1,7 +1,7 @@
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FROM debian:buster-slim
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LABEL authors="Patrick Jentsch <p.jentsch@uni-bielefeld.de>, Stephan Porada <sporada@uni-bielefeld.de>"
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LABEL authors="Patrick Jentsch <p.jentsch@uni-bielefeld.de>"
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ENV LANG=C.UTF-8
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@ -16,26 +16,22 @@ ENV PYFLOW_RELEASE=1.1.20
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ADD "https://github.com/Illumina/pyflow/releases/download/v${PYFLOW_RELEASE}/pyflow-${PYFLOW_RELEASE}.tar.gz" .
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RUN tar -xzf "pyflow-${PYFLOW_RELEASE}.tar.gz" \
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&& cd "pyflow-${PYFLOW_RELEASE}" \
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&& apt-get update \
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&& apt-get install --no-install-recommends --yes \
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python2.7 \
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&& rm -r /var/lib/apt/lists/* \
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&& python2.7 setup.py build install \
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&& cd .. \
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&& rm -r "pyflow-${PYFLOW_RELEASE}" "pyflow-${PYFLOW_RELEASE}.tar.gz"
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## Install ocropy ##
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ENV OCROPY_RELEASE 1.3.3
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ENV OCROPY_RELEASE=1.3.3
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ADD "https://github.com/tmbdev/ocropy/archive/v${OCROPY_RELEASE}.tar.gz" .
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RUN tar -xzf "v${OCROPY_RELEASE}.tar.gz" \
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&& cd "ocropy-${OCROPY_RELEASE}" \
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&& apt-get update \
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&& apt-get install --no-install-recommends --yes \
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python-pil \
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python-tk \
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$(cat PACKAGES) \
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&& rm -r /var/lib/apt/lists/* \
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&& python2.7 setup.py install \
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&& cd .. \
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&& rm -r "ocropy-${OCROPY_RELEASE}" "v${OCROPY_RELEASE}.tar.gz"
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@ -46,7 +42,6 @@ ENV TESSERACT_RELEASE=4.1.1
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ADD "https://github.com/tesseract-ocr/tesseract/archive/${TESSERACT_RELEASE}.tar.gz" .
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RUN tar -xzf "${TESSERACT_RELEASE}.tar.gz" \
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&& cd "tesseract-${TESSERACT_RELEASE}" \
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&& apt-get update \
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&& apt-get install --no-install-recommends --yes \
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autoconf \
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automake \
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@ -59,7 +54,6 @@ RUN tar -xzf "${TESSERACT_RELEASE}.tar.gz" \
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make \
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pkg-config \
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zlib1g-dev \
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&& rm -r /var/lib/apt/lists/* \
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&& ./autogen.sh \
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&& ./configure \
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&& make \
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@ -67,30 +61,34 @@ RUN tar -xzf "${TESSERACT_RELEASE}.tar.gz" \
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&& ldconfig \
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&& cd - > /dev/null \
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&& rm -r "tesseract-${TESSERACT_RELEASE}" "${TESSERACT_RELEASE}.tar.gz"
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ADD "https://github.com/tesseract-ocr/tessdata_best/raw/master/deu.traineddata" \
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"https://github.com/tesseract-ocr/tessdata_best/raw/master/eng.traineddata" \
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"https://github.com/tesseract-ocr/tessdata_best/raw/master/enm.traineddata" \
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"https://github.com/tesseract-ocr/tessdata_best/raw/master/fra.traineddata" \
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"https://github.com/tesseract-ocr/tessdata_best/raw/master/frk.traineddata" \
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"https://github.com/tesseract-ocr/tessdata_best/raw/master/frm.traineddata" \
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"https://github.com/tesseract-ocr/tessdata_best/raw/master/ita.traineddata" \
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"https://github.com/tesseract-ocr/tessdata_best/raw/master/por.traineddata" \
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"https://github.com/tesseract-ocr/tessdata_best/raw/master/spa.traineddata" \
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"/usr/local/share/tessdata/"
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RUN chmod 644 /usr/local/share/tessdata/*.traineddata
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ENV TESSDATA_BEST_RELEASE=4.1.0
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ADD "https://github.com/tesseract-ocr/tessdata_best/archive/${TESSDATA_BEST_RELEASE}.tar.gz" .
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RUN tar -xzf "${TESSDATA_BEST_RELEASE}.tar.gz" \
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&& mv "tessdata_best-${TESSDATA_BEST_RELEASE}/deu.traineddata" "/usr/local/share/tessdata/" \
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&& mv "tessdata_best-${TESSDATA_BEST_RELEASE}/eng.traineddata" "/usr/local/share/tessdata/" \
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&& mv "tessdata_best-${TESSDATA_BEST_RELEASE}/enm.traineddata" "/usr/local/share/tessdata/" \
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&& mv "tessdata_best-${TESSDATA_BEST_RELEASE}/fra.traineddata" "/usr/local/share/tessdata/" \
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&& mv "tessdata_best-${TESSDATA_BEST_RELEASE}/frk.traineddata" "/usr/local/share/tessdata/" \
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&& mv "tessdata_best-${TESSDATA_BEST_RELEASE}/frm.traineddata" "/usr/local/share/tessdata/" \
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&& mv "tessdata_best-${TESSDATA_BEST_RELEASE}/ita.traineddata" "/usr/local/share/tessdata/" \
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&& mv "tessdata_best-${TESSDATA_BEST_RELEASE}/por.traineddata" "/usr/local/share/tessdata/" \
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&& mv "tessdata_best-${TESSDATA_BEST_RELEASE}/spa.traineddata" "/usr/local/share/tessdata/" \
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&& rm -r "tessdata_best-${TESSDATA_BEST_RELEASE}" "${TESSDATA_BEST_RELEASE}.tar.gz"
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## Further dependencies ##
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RUN apt-get update \
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&& apt-get install --no-install-recommends --yes \
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RUN apt-get install --no-install-recommends --yes \
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ghostscript \
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python-pip \
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python3.7 \
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zip \
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&& rm -r /var/lib/apt/lists/* \
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&& pip install natsort
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RUN rm -r /var/lib/apt/lists/*
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## Install Pipeline ##
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COPY hocrtotei ocr /usr/local/bin/
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85
README.md
85
README.md
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# OCR
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# OCR - Optical Character Recognition
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## Build image
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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.
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1. Clone this repository and navigate into it:
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```
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git clone https://gitlab.ub.uni-bielefeld.de/sfb1288inf/ocr.git && cd ocr
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## Software used in this pipeline implementation
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- Official Debian Docker image (buster-slim) and programs from its free repositories: https://hub.docker.com/_/debian
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- ocropy (1.3.3): https://github.com/ocropus/ocropy/releases/tag/v1.3.3
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- pyFlow (1.1.20): https://github.com/Illumina/pyflow/releases/tag/v1.1.20
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- Tesseract OCR (4.1.1): https://github.com/tesseract-ocr/tesseract/releases/tag/4.1.1
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- tessdata_best (4.1.0): https://github.com/tesseract-ocr/tessdata_best/releases/tag/4.1.0
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## Use this image
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1. Create input and output directories for the pipeline.
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``` bash
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mkdir -p /<my_data_location>/input /<my_data_location>/output
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```
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2. Build image:
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```
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docker build -t sfb1288inf/ocr:latest .
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```
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2. Place your PDF files inside `/<my_data_location>/input`. Files should all contain text of the same language.
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Alternatively build from the GitLab repository without cloning:
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1. Build image:
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```
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docker build -t sfb1288inf/ocr:latest https://gitlab.ub.uni-bielefeld.de/sfb1288inf/ocr.git
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3. Start the pipeline process. Check the [Pipeline arguments](#pipeline-arguments) section for more details.
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```
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# Option one: Use the wrapper script
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## 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}
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cd /<my_data_location>
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ocr -i input -l <language_code> -o output <pipeline_arguments>
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## Download prebuilt image
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The GitLab registry provides a prebuilt image. It is automatically created, utilizing the conquaire build servers.
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1. Download image:
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```
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docker pull gitlab.ub.uni-bielefeld.de:4567/sfb1288inf/ocr:latest
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```
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## Run
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1. Create input and output directories for the OCR software:
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```
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mkdir -p /<mydatalocation>/files_for_ocr /<mydatalocation>/files_from_ocr
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```
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2. Place your files inside the `/<mydatalocation>/files_for_ocr` directory. Files can either be PDF (.pdf) or multipage TIFF (.tiff, .tif) files. Files should all contain text of the same language.
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3. Start the OCR process.
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```
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# Option two: Classic Docker style
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docker run \
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--rm \
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-it \
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-u $(id -u $USER):$(id -g $USER) \
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-v /<mydatalocation>/files_for_ocr:/input \
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-v /<mydatalocation>/files_from_ocr:/output \
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sfb1288inf/ocr:latest \
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-v /<my_data_location>/input:/input \
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-v /<my_data_location>/output:/output \
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gitlab.ub.uni-bielefeld.de:4567/sfb1288inf/ocr:1.0.0 \
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-i /input \
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-l <languagecode> \
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-o /output
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-l <language_code>
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-o /output \
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<optional_pipeline_arguments>
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```
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The arguments below `sfb1288inf/ocr:latest` are described in the [OCR arguments](#ocr-arguments) part.
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If you want to use the prebuilt image, replace `sfb1288inf/ocr:latest` with `gitlab.ub.uni-bielefeld.de:4567/sfb1288inf/ocr:latest`.
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4. Check your results in the `/<my_data_location>/output` directory.
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```
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4. Check your results in the `/<mydatalocation>/files_from_ocr` directory.
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### OCR arguments
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### Pipeline arguments
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`-l languagecode`
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* Tells tesseract which language will be used.
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* Used to skip binarization with ocropus. If skipped, only the tesseract binarization is used.
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* default = False
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Example with all arguments used:
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```
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``` bash
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# Example with all arguments used
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docker run \
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--rm \
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-it \
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-u $(id -u $USER):$(id -g $USER) \
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-v "$HOME"/ocr/files_for_ocr:/input \
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-v "$HOME"/ocr/files_from_ocr:/output \
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sfb1288inf/ocr:latest \
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-v "$HOME"/ocr/input:/input \
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-v "$HOME"/ocr/output:/output \
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gitlab.ub.uni-bielefeld.de:4567/sfb1288inf/ocr:1.0.0 \
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-i /input \
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-l eng \
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-o /output \
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#!/usr/bin/env python3.7
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# coding=utf-8
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""""Merges hOCR files into a TEI file."""
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from xml.sax.saxutils import escape
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from argparse import ArgumentParser
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import xml.etree.ElementTree as ET
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parser = ArgumentParser(description='Merges hOCR files to one P5 file.')
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parser = ArgumentParser(description='Merges hOCR files into a TEI file.')
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parser.add_argument('i', metavar='hOCR-sourcefile', nargs='+')
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parser.add_argument('o', metavar='TEI-destfile',)
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args = parser.parse_args()
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17
ocr
17
ocr
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#!/usr/bin/env python2.7
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# coding=utf-8
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"""
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ocr
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"""An OCR pipeline for PDF file processing."""
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Usage: For usage instructions run with option --help
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Authors: Patrick Jentsch <p.jentsch@uni-bielefeld.de
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Stephan Porada <sporada@uni-bielefeld.de>
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"""
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__author__ = 'Patrick Jentsch <p.jentsch@uni-bielefeld.de>'
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__version__ = '1.0.0'
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from argparse import ArgumentParser
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from natsort import natsorted
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@ -22,7 +19,10 @@ TESSERACT_MODELS = ['deu', 'eng', 'enm', 'fra', 'frk', 'frm', 'ita', 'por', 'spa
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def parse_args():
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parser = ArgumentParser(description='OCR Pipeline utilizing tesseract.')
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parser = ArgumentParser(
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description='An OCR pipeline for PDF file processing.',
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prog='OCR pipeline'
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)
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parser.add_argument('-i', '--input-directory',
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help='Input directory (only PDF files get processed)',
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required=True)
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help='Zips all results in different archives depending'
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' on result types. Also zips everything into one '
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'archive.')
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parser.add_argument('-v', '--version',
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action='version',
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version='%(prog)s {}'.format(__version__))
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return parser.parse_args()
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#!/usr/bin/env python3
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# coding=utf-8
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"""A wrapper to execute the OCR pipeline in a Docker container"""
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from argparse import ArgumentParser
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import os
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import subprocess
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CONTAINER_IMAGE = 'gitlab.ub.uni-bielefeld.de:4567/sfb1288inf/ocr:latest'
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CONTAINER_IMAGE_TAG = '1.0.0'
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CONTAINER_IMAGE = 'gitlab.ub.uni-bielefeld.de:4567/sfb1288inf/ocr:{}'.format(CONTAINER_IMAGE_TAG) # noqa
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CONTAINER_INPUT_DIR = '/input'
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CONTAINER_INTERMEDIATE_DIR = '/intermediate'
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CONTAINER_OUTPUT_DIR = '/output'
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