CRAFT-pytorch docker image (text detection in images)
Description
Dockerized version of the CRAFT text identification model
Usage
To use the docker image, first pull the image using
docker pull jumpst3r/craft-pytorch
And then execute
docker run -it --rm -v /FULL_PATH_TO/example.png:/input/example.png -v /FULL_PATH_TO_OUTPUT_FOLDER/:/output/ jumpst3r/craft-pytorch sh /input/script.sh /input/example.png /output/
where /FULL_PATH_TO/example.png corresponds to the local path of the image you'd like to test. The output consists of:
- A visualisation of the detected bounding boxes
- A csv file containing the coordinates of the bounding boxes.
The docker image is also compatible with DIVAServices a web-based framework providing streamlined access to DOI methods.