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Software Engineering

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Face Recognition Web App with Machine Learning Django Heroku

Develop & Deploy Face Recognition, Facial Emotion using OpenCV, Machine Learning, Django & Database in Python in Heroku

4.54 (13 reviews)

Students

7 hours

Content

Jul 2021

Last Update
Regular Price

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What you will learn

Deploy Face Recognition Django Web App in Heroku Cloud

Train your own Machine Learning based Face Recognition Model in Python

Train own Facial Emotion Recognition using Machine Learning in Python

Develop Django Web App using MVT Framework

Design SQLlite Database in Django

Train Support Vector Machines, Random Forest Model for Face Recognition in Python

Debuging error while Deploying in Heroku

Interphase Machine Learning Models with MVT Framework

Build Ensemble (stacking) Machine Learning Model combining SVM and Random Forest Models in Python

Face Detection with Deep Neural Networks

OpenCV Essentials for Face Recognition

Managing Heroku Cloud

Styling Django Web App with Bootstrap


Description

Welcome to the Course Deploy Face Recognition Web App, Machine Learning, Django & Database in Heroku Cloud !!!.

An Artificial Intelligence Project.

Computer Vision & Face recognition is one of the most widely used in the area of Artificial Intelligence and Data Science. If at all you want to develop an end-to-end application in Data Science, then you need to be a master in Machine Learning / Deep Learning, and in addition to that, you need to have knowledge in Web Development.

This course is one stop course where you will learn End to End development of a Computer-Vision Based Artificial Intelligence Project from SCRATCH. As this course is a full-stack course we designed this course into 4 phases

  • Phase-1: Machine Learning - Face Identify Recognition

    • In this phase, we majorly cover the practical concepts related to machine learning models like data preprocessing, analysis, training machine learning, and model evaluation and selection (Grid Search Hyperparameter Tuning)

    • Here I will teach you how to develop face recognition models using machine learning

  • Phase-2: Machine Learning - Facial Emotion Recognition

    • Here we will develop another machine learning-based face recognition for facial emotion recognition.

  • Phase-3: Django Web App Development

    • In this phase, I will teach you how to develop a Web App with Django.

    • We will use a powerful framework which is the MVT (Models Views Templates) framework to develop the web app.

    • You will also learn how to design a database (SQLite) for the Web App in Django.

    • Integrate Machine Learning Model to MVT framework

    • I will also explain, styling using Bootstrap

  • Phase-4: Deployment / Production

    • In this phase, we will deploy the Django web app on a cloud platform which is the HEROKU cloud

    • I will explain all the necessary steps and installation to deploy the Django Project


If you want to become an AI developer this is the perfect course to starts with. Below given is the high-level abstract of the course and the learning objectives.

What you will learn?

Prerequisite of Project: OpenCV

  1. Image Processing with OpenCV

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

  3. Feature Extraction with OpenCV and Deep Learning Networks

Project Phase - 1: Face Recognition and Person Identity

  1. Gather Images

  2. Extract Faces only from Images

  3. Labeling (Target output) Images

  4. Data Preprocessing

  5. Training Face Recognition with OWN Machine Learning Models.

    1. Logistic Regression

    2. Support Vector Machines

    3. Random Forest Classifier

  6. Combine All Machine Learning Models using Ensemble Technique with Voting Classifier

  7. Tuning Machine Learning Model

  8. Model Evaluation

    1. Precision

    2. Recall

    3. Sensitivity

    4. Specificity

    5. F1 Score

    6. Accuracy

Project Phase - 2: Train Facial Emotion Recognition

  1. Gather Emotion Images

  2. Data Preprocessing

  3. Train Machine Learning Models

  4. Tuning Machine Learning Models

  5. Model Evaluation

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

  1. Setting Up Visual Studio Code

  2. Install all Dependencies of VS Code

  3. Setting Virtual Environment

  4. Freeze Requirements

  5. Learn Django Basics

    1. SETTINGS

    2. URLS

    3. VIEWS

    4. TEMPLATES (HTML)

  6. Face Recognition Django Project

    1. Models Views Templates (MVT)

  7. Design SQLite Database in Django

  8. Store Uploaded Image in Database

  9. Integrate Machine Learning to Django

    1. MVT + Machine Learning Framework

Styling Django Web App with Bootstrap

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

  1. Setting up Heroku Account.

  2. Creating App in Heroku

  3. Install Heroku CLI, GIT

  4. Deploy Heroku in Cloud

  5. Necessary Installation to Fix CSS in Heroku.

Overview:

I will start the course by installing Python and installing the necessary libraries in Python for developing the end-to-end project. Then I will teach you one of the prerequisites of the course that is image processing techniques in OpenCV and the mathematical concepts behind the images. We will also do the necessary image analysis and required preprocessing steps for the images. Then we will do a mini project on Face Detection using OpenCV and Deep Neural Networks.

With the concepts of image basics, we will then start our project phase-1, face identity recognition. I will start this phase with preprocessing images, we will extract features from the images using deep neural networks. Then with the features of faces, we will train the different Machine learning models like logistic regression, support vector machines, random forest. Then we combine all machine learning models with Voting Classifier (stacking method). I will teach you the model selection and hyperparameter tuning for face recognition models

In Phase-2, we will apply the machine learning techniques used in face identity recognition for facial emotion recognition. After that, we will combine all different detection and recognition models into a pipeline.

Once our machine learning model is ready, will we move to Phase-3, and develop a Web Application in Django by rendering HTML CSS and bootstrap in the frontend and in the backend written in Python. Here I will teach you the necessary prerequisite of Django. Then we will develop a web app using the MVT (Models, Views, and Templates) framework. We will start developing Django App by designing a database in SQLite. Here I will also teach you to interphase machine learning pipeline models to the MVT framework. In the end, we will style our app using Bootstrap.

Finally, we will deploy the entire Django Web App in Heroku Cloud for production and get a URL/domain where you can access it anywhere in the world. I will also teach all the necessary installation required and explain how to solve errors whenever you have encountered them while deploying your web app.

What are you waiting for? Start the course develop your own Computer Vision Django Web Project using Machine Learning, Python and Deploy it in Cloud with your own hands.

I will see you inside the course.


Screenshots

Face Recognition Web App with Machine Learning Django Heroku
Face Recognition Web App with Machine Learning Django Heroku
Face Recognition Web App with Machine Learning Django Heroku
Face Recognition Web App with Machine Learning Django Heroku

Content

Introduction

Introduction

Setting Up Course

Install Python

Download requirements.txt

Install CMake & Dlib on Windows

Image Processing with OpenCV

What will you learn ?

Download Resources

What is Pixel

Load Image

Display Image

Save Image

Acessing Pixels

Manipulate Pixels

Color Space - Split BGR

Color Space - Convert Colors

Drawings - Line

Drawings - Line part2

Drawings - Rectangle

Drawings - Polygon

Drawings - Circles

Put Text

Knowledge Check

Object Detection with OpenCV

What you will Learn ?

Download the Resources

Viola-Jones Object Detection Intuition

Download Cascade Classifier

Face Detection with Cascade Classifier

Multiple Faces Detection

Eyes Detection

Smile Detection

Face Detection & Feature Extraction using DNN OpenCV

What you will Learn ?

Download the Resourses

Face Detection with Deep Neural Network Framework

Face Detection with DNN part-1

Face Detection with DNN part -2

Face Detection with DNN part-3

Feature Extraction Framework

Facial Feature Extraction: part-1

Facial Feature Extraction: part-2 (Landmark Detection)

Facial Feature Extraction: part-3 (Face Descriptors)

Phase-1: Face Recognition Project (Person Identity)

Project phase -1, Face Recognition

Face Recognition Framework

Data Preprocessing

Data Preprocessing - face detection

Data Preprocessing - feature extraction

Machine Learning - Data

Machine Learning - Logistic Regression

Machine Learning - Support Vector Classifier

Machine Learning - Random Forest

Machine Learning - Voting Classifier

Grid Search Parameter Tuning

Save Face Recognition Model in Pickle

Facial Emotion Recognition

Get the Data

Data Preprocessing

Train Machine Learning Model

Pipeline All Models

Pipeline Model

Pipeline Model part-2

Pipeline Model part-3

Pipeline Model Part-4

Phase-2: Setting Up Web App Project

Phase-2: Django Web App

Install Visual Studio Code

Setting Up Visual Studio Code

Create Virtual Environment from Visual Studio Code (Windows)

Install & Freeze Requirements

Django Basics

Your First Django App

Django Overview

HttpRespones in Django

Templates

Static

Face Recognition Webapp with Django

Model Views Templates + Machine Learning Framework

Download the Django Project

Upload Images into Models - part-1

Connect Models, Views, Template part-2

Connect Models, Views, Template part-3

Import Machine Learning Models in Django App

Get Face Recognition Predictions from Machine Learning in Django

Display Face Recognition Output in Django Templates

Display Face Recognition Output in Django Templates part-2

Styling Django Web App with Bootstrap

Styling Django Web App with Bootstrap part2

Styling Django Web App with Bootstrap part3

Phase-3: Deploy Face Recognition Django WebApp in Heroku Cloud

Project Phase-3: Deploy Face Recognition Web App in Heroku

Download the Django Project for your reference

Create Heroku Account

Install GIT

Install Heroku CLI

Deploy Django in Heroku - part1

Deploy Django in Heroku - part2

Solution for missing Static in Heroku- collectstatic


Coupons

DateDiscountStatus
7/3/202194% OFFExpired

4021172

Udemy ID

5/2/2021

Course created date

6/12/2021

Course Indexed date
medo3abed
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