Description
This hands-on course on OpenCV not only helps you learn computer vision and ML with OpenCV 4 but also enables you to apply these skills to your projects. You will firstly set up your development environment for building interesting computer vision applications for Face and Eyes detection, Emotion recognition, and Fast QR code detection. You will then explore essential machine learning and deep learning concepts such as supervised learning, unsupervised learning, neural networks, and learn how to combine them with other OpenCV functionality for image processing and object detection. Along the way, you will also get some tips and tricks to work efficiently.
Learning Outcomes
- Build real-time applications that deal with image and video processing
- Build an Optical Character Recognition (OCR) engine from scratch
- Get to know how to train face recognition system
- Create your own real-time object classifier
- Build computer vision applications
- Create DNN based Image Classifier
- How to apply various Machine Learning algorithms to real-life problems
- Explore Supervised Learning and Unsupervised Learning approaches in Computer Vision
Requirements
- Working knowledge of Python programming is required.
Target Audience-
- This course is intended for Python developers, computer vision developers, and enthusiasts who want to learn machine learning algorithms and implement them with OpenCV 4 for building computer vision applications.
Course Features
- Lectures 0
- Quizzes 0
- Duration 30 Mins class each
- Skill level All levels
- Language English
- Students 183
- Assessments Yes