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Web Application for deploying neural net model on Render

42okf4

TODO

  • basic html interface
  • cam in or image input
  • server.py to interface with server
  • js to receive and analyse image
  • relay audio out

The repository can be used as a starting point to deploy any model on Render.

Guide for production deployment :

  • Fork this repository or clone the app/ folder into your Github account.
  • Upload your trained model file.
  • Upload the trained model file created with learner.export (for example export.pkl) to a cloud service.
  • Edit the file server.py inside the app directory and update the export_file_url variable with the URL copied above. In the same file, update the line "classes" with the classes of your model.
  • Create a new Web Service on Render and use the repo you created above.

Local testing : To run the app server locally, run this command in your terminal:

python app/server.py serve

Changes can be tested locally by installing Docker and using the following command:

docker build -t "repo-name" . && docker run --rm -it -p 5000:5000 "repo-name"

Officially time to shift from Heroku to Render :

  • Although being expedient, moving from AWS to Render eliminated a lot of infrastructure complexity.
  • I would prefer GCP being a student but it compares nothing against AWS Services.

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Web Application for the neural net project aiSight

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