OpenCV 4 Computer Vision with Python Recipes [Video]

• 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.

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.

This course helps you learn the core concepts of OpenCV faster by taking a recipe-based approach where you can try out different code snippets to understand a concept. Every operation is performed step-by-step and the code is neatly documented so it’s easier for the audience to reuse the modules in their own projects.

• Explore the latest feature set and modern APIs in OpenCV 4
• Build computer vision applications with OpenCV functionality via Python API
• Get to grips with image processing, object detection and machine learning
• Learn to use deep learning models for image classification, object detection, and face recognition