mirror of
https://gitlab.ub.uni-bielefeld.de/sfb1288inf/ocr.git
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106 lines
5.6 KiB
Markdown
106 lines
5.6 KiB
Markdown
# Installation
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## Install additional packages
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1. Install `screen`. We will use this to execute commands in their own terminal session.
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## Build your own image
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1. Clone this repository and navigate into it.
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2. Build the image from the dockerfile. `docker build -t <image_name>:<tag> .` For example: `docker build -t ocr_container:latest .`
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Alternatively build directly from git.
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1. Use the following command to build directly from gitLab. `docker build -t <image_name>:<tag> https://gitlab.ub.uni-bielefeld.de/sfb1288inf/ocr.git`.
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## Folder setup
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1. Create input and output folders for the OCR files.
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2. `mkdir -p /some/path/<container-name>/ocr/files_for_ocr /some/path/<image_name>/ocr/files_from_ocr`
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## Run the container
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1. Run container from an image. <contianer_name> and /some/path are the same as mentioned in the step folder setup. We are creating two volumes based on the folder paths provided in the section Folder setup.
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```
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docker run \
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--name <container-name> \
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-dit \
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-v /some/path/<container-name>/files_for_ocr:/root/files_for_ocr \
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-v /some/path/<container-name>/files_from_ocr:/root/files_from_ocr \
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<image_name>
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```
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## Start an OCR job
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1. Place some files inside the folder _files\_for\_ocr_. Files can either be multipage tiffs or PDF files. One folder per file is needed. Files should all be of the same language.
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2. Start a screen session with `screen -dmS <container_name>`
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3. Enter the screen session with `screen -r <container-name>`. (Try this if the error "Cannot open your terminal '/dev/pts/0' - please check." appears: `script -q -c "screen -r <container-name>" /dev/null`).
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4. Start the OCR process for all files placed in _files\_for\_ocr_ with `docker exec -it <container-name> ocr -i files_for_ocr -o files_from_ocr -l <sprachcode>`.
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Valid language codes are:
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- deu (German)
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- deu_frak (German Fraktur)
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- eng (English)
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- enm (Middle englisch)
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- fra (French)
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- frm (Middle french)
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- por (Portuguese)
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- spa (Spanish)
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### Additional OCR arguments
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Below we will describe all available pipeline arguments that can be used.
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- **_-i some/path_**
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- Sets the input directory using the specified path.
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- required = True
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- **_-o some/path_**
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- Sets the output directory using the specified path.
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- required = True
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- **_-l valid_language_code_**
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- Tells tesseract which language will be used.
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- required = True
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- **_--keep_intermediates_**
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- Optional argument. If set all intermediate filese created during the OCR process will be kept.
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- default = False
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- required = False
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- **_--nCores_**
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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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## Exit an re-enter the current running OCR process
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1. You can leave the currently running OCR process by pressing `ctrl + a + d` and thus leaving the screen session.
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2. Re-enter the screen session to check the status of the running OCR job with `screen -r <container-name>`. (Try this if the error "Cannot open your terminal '/dev/pts/0' - please check." appears: `script -q -c "screen -r <container-name>" /dev/null`).
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## Use prebuilt image
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Download via regestry function with login or deploy token.
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## Add additional traineddata for OCR of additional languages.
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Additional traineddata can be easily added to the Dockerfile.
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Just append the needed data file URL after line 56 in the Dockerfile following the same syntax.
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The standard traineddata 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 traineddata 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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Traineddata 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 traineddata 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/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/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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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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``` |