Face Mask Recognition: Deep Learning based Desktop App

Project that you will be Developing:

Prerequisite of Project: OpenCV

Image Processing with OpenCV

Section –0 : Setting Up Project

Install Python

Install Dependencies

Section –1 : Data Preprocessing

Gather Images

Extract Faces only from Images

Labeling (Target output) Images

Data Preprocessing

RGB mean subtraction image

Section – 2: Develop Deep Learning Model

Training Face Recognition with OWN Deep Learning Model.

Convolutional Neural Network

Model Evaluation

Section – 3: Prediction with CNN Model

1. Putting All together

Section – 4: PyQT Basics

Section –5: PyQt based Desktop Application

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 Deep learning models like Convolutional Neural Network.  I will teach you the model selection and hyperparameter tuning for face recognition models