Face Recognition Web App with Machine Learning in Flask

person icon Srikanth Guskra

Face Recognition Web App with Machine Learning in Flask

Create an Face Recognition (AI) project from scratch with Python, OpenCV , Machine Learning Algorithms and Flask

updated on icon Updated on Sep, 2023

language icon Language - English

person icon Srikanth Guskra

architecture icon Development,Data Science and AI ML,Machine Learning,Web Development


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Course Description

Face Recognition Web Project using Machine Learning in Flask Python

Face recognition is one of the most widely used in my application. If at all you want to develop and deploy the application on the web only knowledge of machine learning or deep learning is not enough. You also need to know the creation of pipeline architecture and call it from the client-side, HTTP request, and many more. While doing so you might face many challenges while developing the app. This course is structured in such a way that you can able to develop the face recognition based web app from scratch.

What you will learn?

  1. Python

  2. Image Processing with OpenCV

  3. Image Data Preprocessing

  4. Image Data Analysis

  5. Eigenfaces with PCA

  6. Face Recognition Classification Model with Support Vector Machines

  7. Pipeline Model

  8. Flask (Jinja Template, HTML, CSS, HTTP Methods)

  9. Face recognition Web App in Flask

  10. Deploy app in Railway app and Heroku

You will learn image processing techniques in OpenCV and the concepts behind the images. We will also do the necessary image analysis and required preprocessing steps for images. 

For the preprocess images, we will extract features from the images, ie. computing Eigen images using principal component analysis. With Eigen images, we will train the Machine learning model and also learn to test our model before deploying, to get the best results from the model we will tune with the Grid search method for the best hyperparameters.

Once our machine learning model is ready, will we learn and develop a web server gateway interphase in flask by rendering HTML CSS and bootstrap in the frontend and in the backend written in Python.  Finally, we will create the project on the Face Recognition project by integrating the machine learning model to Flask App.


What will you learn in this course:

  • Automatic Face Recognition in images and videos
  • Automatically detect faces from images and videos
  • Evaluate and Tune Machine Learning
  • Building Machine Learning Model for Classification
  • Make Pipeline Model for deploying your application
  • Image Processing with OpenCV
  • Data Preprocessing for Images
  • Create REST APIs in Flask
  • Template Inheritance in Flask
  • Integrating Machine Learning Model in Flask App
  • Deploy Flask App in Heroku Cloud


What are the prerequisites for this course?

  • Should be at-least beginner level in Python
  • Be able to understand HTML and CSS
  • Basic Understanding of Machine Learning Concepts
Face Recognition Web App with Machine Learning in Flask


Check out the detailed breakdown of what’s inside the course

5 Lectures
  • play icon Introduction 02:36 02:36
  • play icon Clone Face Recognition Template 00:44 00:44
  • play icon Create and Install Virtual Environment & Packages 03:12 03:12
  • play icon Next steps 00:14 00:14
  • play icon Download Resources
Image Processing with OpenCV
12 Lectures
Develop Face Recognition Model with Machine Learning from Scratch
35 Lectures
Face Recognition Project (Integrating HTML Model to Flask App)
15 Lectures
Deploy Web App in Heroku Cloud
7 Lectures
Deploying in another open-course cloud.
3 Lectures

Instructor Details

Srikanth Guskra

Srikanth Guskra

Data Scientist


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