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.
Setup development environment
We setup the development environment in a Docker container with the following command.
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.
- git clone this repository
- make init
- docker run -it --rm -p 8888:5000 -v $PWD:/work sobel-image
- open "http://0.0.0.0:8888/" in your browser
This section shows the detailed usages.
When we need to add libraries in
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 init-docker command to create the Docker container with the latest setting.
Login Docker container
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
Logout from Docker container
When you logout from shell in Docker container, please run
exit in the console.
When you check the code quality, please run
When you run test in
tests directory, please run
Sync data source to local data directory
When you want to download data in remote data sources such as S3 or NFS,
sync-from-remote target downloads them.
Sync local data to remote source
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.
Show profile of Docker container
When you see the status of Docker container, please run
make profile in host machine.
Use Jupyter Notebook
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 repository is a reproduction of the content of 2018 summer internship. Thank you.