this is a demo to confirm availability of docker, cookie-cutter and flask. In this app, we can understand how sobel filter affect on images. You can add your photo in the application, and you get an image processed by sobel filter.

We setup the development environment in a Docker container with the following command.

• make init

This command gets the resources for training and testing, and then prepares the Docker image for the experiments. After creating the Docker image, you run the following command.

0. git clone this repository
1. make init
2. docker run -it --rm -p 8888:5000 -v $PWD:/work sobel-image
3. open "http://0.0.0.0:8888/" in your browser

This section shows the detailed usages.

When we need to add libraries in Dockerfile or requirements.txt which are added to working environment in the Docker container, we need to drop the current Docker container and image, and then create them again with the latest setting. To remove the Docker the container and image, run make clean-docker and then make init-docker command to create the Docker container with the latest setting.

Only the first time you need to create a Docker container, from the image created in make init command. make create-container creates and launch the sobel container. After creating the container, you just need run make start-container.

When you logout from shell in Docker container, please run exit in the console.

When you check the code quality, please run make lint

When you run test in tests directory, please run make test

When you want to download data in remote data sources such as S3 or NFS, sync-from-remote target downloads them.

When you modify the data in local environment, sync-to-remote target uploads the local files stored in data to specified data sources such as S3 or NFS directories.

When you see the status of Docker container, please run make profile in host machine.

To launch Jupyter Notebook, please run make jupyter in the Docker container. After launch the Jupyter Notebook, you can access the Jupyter Notebook service in http://localhost:8888.

This package was created with Cookiecutter and the cookiecutter-docker-science project template.

This repository is a reproduction of the content of 2018 summer internship. Thank you.