HackGStyle

Style transfer models and photobooth infrastructure.

The style transfer model is modified from PyTorch/examples and is located under the fast_neural_style directory along with the original license and readme.

For 'quick out of the box' localhost setup:

BACKEND:

- Use paperspace! (DL box is has versions that are too new, https://myselfhimanshu.github.io/posts/setting_paperspace_dl/) - USE ML IN A BOX
- ./setup.sh (may run into some directory issues, data directory should be on base of DetectronPytorch)
- Load appropriate env vars:
    - SENDGRID_API_KEY
    - FROM_EMAIL = hello@hackgt.com
    - CLOUD_BUCKET (new one should be made per event, just the bucket name)
    - Export service key json filename:
        - (have file in backend/)
        - export GOOGLE_APPLICATION_CREDENTIALS=<key.json>
        - https://cloud.google.com/storage/docs/reference/libraries#client-libraries-install-cpp (export/load into a file)
        - https://cloud.google.com/storage/docs/reference/libraries#client-libraries-install-cpp
- conda install -c pytorch=0.4.1
- open port, include port in address (test server up using simple get)
    - sudo ufw status verbose
    - sudo ufw enable
    - sudo ufw allow <port>/tcp
- python server.py
- Startup the backend server, link the proper address in frontend

FRONTEND:

- Clone this repo and nfc-badge-server on serving laptop 
- Use nvm to get node, npm i, npm run build
- Start nfc-badge-server and follow appropriate instructions
    - if registered, starting the server will output nfc id
- Load env vars:
    - REGISTRATION_API_KEY (find in admin panel)
    - REGISTRATION_URL (graphql for registration, make sure it's non-redirect)
    - CHECKIN_API_KEY [?]
    - CHECKIN_URL (non redirect)
- Use python3/pip3 to install everything
- python3 app.py
    - access via localhost to avoid insecure origins on chrome
- Ready camera should log 'ready to capture...'