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https://gitlab.ub.uni-bielefeld.de/sfb1288inf/ocr.git
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129 lines
5.2 KiB
Markdown
129 lines
5.2 KiB
Markdown
# OCR
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## Build image
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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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```
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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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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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```
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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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docker run \
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--rm \
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-it \
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-v /<mydatalocation>/files_for_ocr:/files_for_ocr \
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-v /<mydatalocation>/files_from_ocr:/files_from_ocr \
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sfb1288inf/ocr:latest \
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-i /files_for_ocr \
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-o /files_from_ocr \
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-l <languagecode>
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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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4. Check your results in the `/<mydatalocation>/files_from_ocr` directory.
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### OCR arguments
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`-i path`
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* Sets the input directory using the specified path.
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* required = True
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`-o path`
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* Sets the output directory using the specified path.
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* required = True
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`-l languagecode`
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* Tells tesseract which language will be used.
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* options = deu (German), deu_frak (German Fraktur), eng (English), enm (Middle englisch), fra (French), frm (Middle french), ita (Italian), por (Portuguese), spa (Spanish)
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* required = True
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`--keep-intermediates`
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* If set, all intermediate files created during the OCR process will be
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kept.
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* default = False
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* required = False
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`--nCores corenumber`
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* Sets the number of CPU cores being used during the OCR process.
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* default = min(4, multiprocessing.cpu_count())
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* required = False
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`--skip-binarisation`
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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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docker run \
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--rm \
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-it \
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-v $HOME/ocr/files_for_ocr:/files_for_ocr \
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-v $HOME/ocr/files_from_ocr:/files_from_ocr \
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sfb1288inf/ocr:latest \
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-i /files_for_ocr \
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-o /files_from_ocr \
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-l eng \
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--keep_intermediates \
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--nCores 8 \
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--skip-binarisation
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```
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# Additional language models for OCR
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Additional language models can be easily installed. Just add them analogical to the existing models to the `Dockerfile`.
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The standard language models for various languages can be found under https://github.com/tesseract-ocr/tessdata. Click on one of the languages and copy the link from the download button. The URL for Afrikaans (afr) would be for example https://github.com/tesseract-ocr/tessdata/raw/4.00/afr.traineddata.
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The more accurate but slower language models can be found under https://github.com/tesseract-ocr/tessdata_best. Click on one of the languages and copy the link from the download button. The URL for Afrikaans (afr) would be for example https://github.com/tesseract-ocr/tessdata_best/raw/master/afr.traineddata.
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Language models for fraktur fonts can also be found in the standard tessdata repository https://github.com/tesseract-ocr/tessdata.
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The `Dockerfile` section for the language models with added language support for Afrikaans would look like this:
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```
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RUN echo "deb https://notesalexp.org/tesseract-ocr/stretch/ stretch main" >> /etc/apt/sources.list && \
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wget -O - https://notesalexp.org/debian/alexp_key.asc | apt-key add - && \
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apt-get update && \
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apt-get install -y --no-install-recommends tesseract-ocr && \
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wget -nv https://github.com/tesseract-ocr/tessdata_best/raw/master/afr.traineddata -P /usr/share/tesseract-ocr/4.00/tessdata \
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wget -nv https://github.com/tesseract-ocr/tessdata_best/raw/master/deu.traineddata -P /usr/share/tesseract-ocr/4.00/tessdata && \
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wget -nv https://github.com/tesseract-ocr/tessdata/raw/master/deu_frak.traineddata -P /usr/share/tesseract-ocr/4.00/tessdata && \
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wget -nv https://github.com/tesseract-ocr/tessdata_best/raw/master/eng.traineddata -P /usr/share/tesseract-ocr/4.00/tessdata && \
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wget -nv https://github.com/tesseract-ocr/tessdata_best/raw/master/enm.traineddata -P /usr/share/tesseract-ocr/4.00/tessdata && \
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wget -nv https://github.com/tesseract-ocr/tessdata_best/raw/master/fra.traineddata -P /usr/share/tesseract-ocr/4.00/tessdata && \
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wget -nv https://github.com/tesseract-ocr/tessdata_best/raw/master/frm.traineddata -P /usr/share/tesseract-ocr/4.00/tessdata && \
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wget -nv https://github.com/tesseract-ocr/tessdata_best/raw/master/ita.traineddata -P /usr/share/tesseract-ocr/4.00/tessdata && \
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wget -nv https://github.com/tesseract-ocr/tessdata_best/raw/master/por.traineddata -P /usr/share/tesseract-ocr/4.00/tessdata && \
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wget -nv https://github.com/tesseract-ocr/tessdata_best/raw/master/spa.traineddata -P /usr/share/tesseract-ocr/4.00/tessdata
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```
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