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Dockerized word image to text recognition

Description

Given images of words, recognize the words and output the corresponding text.

Usage

To use the docker image, first pull the image using

docker pull jumpst3r/wordimage2text

And then execute

docker run -it --rm -v /PATH_TO_FOLDER_WITH_INPUTS:/input/figures -v /FULL_PATH_TO_OUTPUT_FOLDER/:/output/ jumpst3r/wordimage2text sh /input/script.sh /input/figures/example.png /input/figures/boxes.csv /output/

where PATH_TO_FOLDER_WITH_INPUTS is the full path to a folder containing the inputs described bellow_

The input consists of:

  • example.png: A document image containing possibly several words.
  • boxes.csv: A csv file containing the bounding boxes delimiting each word in the previously provided image

The output consists of:

  • A csv containing the coordinates of the words with the appended detected word:

    x1,x2,y1,y2,detected_word

  • A zip file containing the cropped out words and a csv which can be used to trace back the original words positions and textual content.

The docker image is also compatible with DIVAServices a web-based framework providing streamlined access to DOI methods.

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Dockerized text recognition

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  • Jupyter Notebook 90.3%
  • Python 9.7%