Face-Recognition-Web-App-

Prerequisite of Project: OpenCV

Image Processing with OpenCV

Face Detection with Viola-Jones and Deep Neural Networks (SSD)

Feature Extraction with OpenCV and Deep Learning Networks

Project Phase - 1: Face Recognition and Person Identity

Gather Images

Extract Faces only from Images

Labeling (Target output) Images

Data Preprocessing

Training Face Recognition with OWN Machine Learning Models.

Combine All Machine Learning Models using Ensemble Technique with Voting Classifier

Tuning Machine Learning Model

Model Evaluation

Project Phase - 2: Train Facial Emotion Recognition

Gather Emotion Images

Data Preprocessing

Train Machine Learning Models

Tuning Machine Learning Models

Model Evaluation

Project Phase -3: Django Web App Developed in Local (Computer)

Setting Up Visual Studio Code

Install all Dependencies of VS Code

Setting Virtual Environment

Freeze Requirements

Learn Django Basics

SETTINGS

URLS

VIEWS

TEMPLATES (HTML)

Face Recognition Django Project

Models Views Templates (MVT)

Design SQLite Database in Django

Store Uploaded Image in Database

Integrate Machine Learning to Django

MVT + Machine Learning Framework

Styling Django Web App with Bootstrap

Project Phase -4: Deploy Web App in Heroku Cloud for Production

Setting up Heroku Account.

Creating App in Heroku

Install Heroku CLI, GIT

Deploy Heroku in Cloud

Necessary Installation to Fix CSS in Heroku.