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A densenet implementation using tensorflow2

Project description

DenseNet implementation using Tensorflow 2

Quickstart

$ ./bin/start

Setup and use docker

Build the docker image,

$ docker build --rm -f dockerfiles/cpu-jupiter.Dockerfile -t sign-language-recognition:latest .

and now run the image

$ docker run -v "$(pwd)/notebooks:/tf/notebooks" --rm -u $(id -u):$(id -g) -p 6006:6006 -p 8888:8888 sign-language-recognition:latest

Visit that link, hey look your jupyter notebooks are ready to be created. Changes in ./notebooks will be saved.

If you want, you can attach a shell to the running container

$ docker exec -it <container-id> /bin/sh -c "[ -e /bin/bash ] && /bin/bash || /bin/sh"

Project details


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This version
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0.1

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