Shreshth Arora Project

ML Library Project 3

The Aim of the project is to provide a holistic website for easy access to ML models via a clean Interface a and options for users

Project 3:

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.

We follow a systematic Git Workflow -

Create a fork of this repo.
Clone your fork of your repo on your pc.
Add Upstream to your clone
Every change that you do, it has to be on a branch. Commits on master would directly be closed.
Make sure that before you create a new branch for new changes,syncing with upstream is neccesary.

Fork the repo and clone it.
Go in the repo and setup virtual environment using
python -m virtualenv venv
Then activate the environment using
On Windows source venv/Scripts/activate On MacOS/Linux source venv/bin/actiavte
Install requirements
pip install -r requirements.txt
Change into the ./proj directory.

All the following steps are to be executed in the proj directory.

-- below two are optional steps --

set secret key for your django project.
You can use [https://djecrety.ir/] to generate your secret key
After the above setup, run
python manage.py makemigrations
python manage.py migrate
Start the backend server
python manage.py runserver
Runs the backend server at default port 8000.
Open http://localhost:8000 to view it in the browser.

The page will reload if you make edits.

If you are adding any new requirements for the project, make sure that you are adding it to requirements.txt

Django 3.0 - The web framework used in the project.
Tensorflow - Framework used to train and test the models and responses
Postgres - Backend DB used to store final responses from the Tensorflow Emotion Detection Model

We use SemVer for versioning.