Antares

This application is intended to serve as an example of an implementation of a model trained with machine learning and deployed in a production environment.

📘 Review of the model, and the process

Screenshots

Backend

API Reference

PNL

  POST /toxic-comment/classify

Parameter	Type	Description
comment	String	Required A comment (toxic comment)

CNN

  POST /eyes/classify

Parameter	Type	Description
Image	file	Required Image of eye

  POST /fruit-or-vegetable/classify

Parameter	Type	Description
Image	file	Required Image of fruit or vegetable

Run Locally Backend

Clone the project

  git clone https://github.com/luismateoh/Antares.git

Go to the project directory

  cd Antares/backend

Install dependencies

  pip install -r requirements.txt

Start the server

  uvicorn app.main:app --reload

Run Locally Frontend

Clone the project

  git clone https://github.com/luismateoh/Antares.git

Go to the project directory

  cd Antares/frontend

Install dependencies

  npm install

Start the dev server

  npm run dev

Deploy with docker

Go to the project directory

  cd Antares

Run the docker compose

  docker-compose up -d --build

License

MIT