Face Recognition Web App with Machine Learning in FLASK

Face Recognition Web App with Machine Learning in FLASK
Face Recognition Web App with Machine Learning in FLASK
English | MP4 | AVC 1280×720 | AAC 44KHz 2ch | 7.5 Hours | 3.70 GB

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

In this course, you will learn end to end process and able to build any artificial intelligence Project. Starting from

  • Gathering the data,
  • Data Understanding
  • Data Preprocessing
  • Data Analysis
  • Predictive Modelling
  • Create REST APIs in Flask

You will 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 Grid search method for best hyperparameters.

Once our machine learning model is ready, will we learn and develop 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 you’ll learn

  • 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
Table of Contents

Introduction
1 Introduction
2 Installing Python
3 Install and Create Virtual Environment
4 Installing OpenCV and Dependencies

Image Processing with OpenCV
6 Introduction
7 Understanding Images
8 Display Images and Depth in Image
9 Understanding Image Pixels – Part 1
10 Understanding Image Pixels – Part 2
11 Image Resizing
12 Object Detection
13 Working on Videos

Build Face Recognition Model with Machine Learning
14 Introduction
15 Machine Learning Pipeline Architecture
16 Data Understanding
17 Crop Faces from Image Data
18 Dealing with Unstructured Data (Faces) – part1
19 Dealing with Unstructured Data (Data Analysis) – part2
20 Dealing with Unstructured Data – part3
21 Data Preprocessing
22 Eigen Faces with Principal Component Analysis – part1
23 Eigen Faces with PCA – part2
24 Train Eigen Faces with Machine Learning Model
25 Model Evaluation
26 Tuning Machine Learning Model – part1
27 Tuning Machine Learning Model – part2
28 Make Pipeline Model (all together)

Flask App
30 Installing Flask and Visual Studio Code
31 Your First Flask App
32 Flask Routing
33 URL Building
34 Flask Templates – Part 1
35 Flask Templates – Part 2
36 Flask Templates – Part 3
37 Template Inheritance
38 Static Files
39 Http Methods in Flask
40 File Upload in Flask

Face Recognition Project (Integrating HTML Model to Flask App)
41 Face Recognition Project Overview
42 Build Base HTML Part-1
43 Build Base HTML Part-2
44 Face App Page
45 Gender Classification Page – Part 1
46 Gender Classification Page – Part 2
47 Integrating Machine Learning Model to Flask App