This is the code repository for OpenCV 4 Computer Vision with Python Recipes [Video], published by Packt. It contains all the supporting project files necessary to work through the video course from start to finish.
Have you ever wondered how self-driving cars work? Have you ever wanted to land a highly paid job in Computer Vision industry? We have compiled this course so you seize your opportunity to get noticed by building awesome Computer Vision applications.This course kicks-off with Introduction to OpenCV 4 and familiarizes you with the advancements in this version. We’ll educate you on how to handle images, enhance and transform them. We’ll also develop some cool applications including Face and Eyes detection, Emotion recognition and Fast QR code detection & decoding that you can deploy anywhere. We’ll also share some tips & tricks to make you more productive. By the end of the course, you will have profound knowledge on what Computer Vision is and how we can leverage OpenCV 4 to build real-world applications without much effort.
The code bundle for this video course is available at - https://github.com/PacktPublishing/OpenCV-4-Computer-Vision-with-Python-Recipes
- How to build real-world Computer Vision applications.
- Deploy Face and Eyes Detection with HAAR Cascade Classifiers.
- Recognize Age, Gender and Emotions and Roadside Landmarks.
- Develop Fast QR Code Detection and Decoding application.
- Create DNN based Image Classifier.
- Train an Object Detection Model and Detect Persons, and Vehicles.
To fully benefit from the coverage included in this course, you will need:
This course is for developers who have a basic knowledge of Python. If you are aware of the basics of OpenCV and are ready to build computer vision systems that are smarter, faster, more complex, and more practical than the competition, then this course is for you.
This course has the following software requirements:
Operating system: Any
Browser: Chrome
Spyder / Sublime