Face Detection using OpenCV Haar Cascades
- Artificial Intelligence
- Computer Vision
- Project length: 2h 44m
Ever thought of creating your own Haar Cascade for Face Detection? This project will teach you how to do the same. We will start from the basics of OpenCV and then move to advance concepts of the Viola-Jones algorithm.
This tutorial will cover all the details (resources, tools, languages, etc) that are necessary to create Haar Cascade for Face Detection. You will be guided through all the steps and concepts, starting from the basic ones like the basics of OpenCV to the more advanced topics related to the development.
What are the requirements?
- Python basics
- Most important is: desire to learn
What is the target audience?
- Learners who want to enhance their knowledge
- This course will help the students who are doing their final projects
Session 1: OpenCV Basics
- Session 1.1: Introduction to OpenCV:
Loading, displaying, resizing, rotating images using OpenCV
- Session 1.2: Basic OpenCV:
Blurring, drawing geometric shapes, edge detection using OpenCV
Session 1.3: K means Clustering in OpenCV
Session 1.4: Reverse a Video
Session 2: Haar Cascade Theory
Session 2.1: Intro to Viola-Jones, Haar Features and Integral Image
Session 2.2: Adaboost and Cascading
Session 3: Haar Cascade Coding
Session 3.1: Face and eye detection using Haar cascade
Session 3.2: Create negative images
Session 3.3: Create positive images
Session 3.4: Preparing final data for training
Session 3.5: Training custom Haar cascade 1
Session 3.6: Training custom Haar cascade 2
Session 3.7: Generating XML cascade files
Session 3.8: Using our custom Haar cascade