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README.md
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# 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 there is an error. `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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## 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 there is an error. `script -q -c "screen -r <container-name>" /dev/null`).
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## Use prebuilt image
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## Add additional trained data for OCR of additional languages.
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TBD
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