MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch

Genre: eLearning | Language: English + .srt | Duration: 43 lectures (9 hour, 45 mins) | Size: 3.75 GB

The Complete Course of OpenCV: Step-by-Step Instructions

What you'll learn

Starting with an overview of what the course will be covering

We move on to discussing morphological operations and practically learn how they work on images

We will then learn contrast enhancement using equalization and contrast limiting

We will learn 3 methods to subtract the background from the video and implement them using OpenCV

Requirements

The course offers you a unique approach of learning how to code by solving real world problems

Prior programming experience is a requirement for this course

We will be using the Python programming language inside the crash course. If you don't have any Python experience, don't worry! The language is super easy to pick up and learn

Description

OpenCV is used for all sorts of image and video analysis, like facial recognition and detection, license plate reading, photo editing, advanced robotic vision, optical character recognition, and a whole lot more.

We will be working through many Python examples here. Getting started with OpenCV's Python bindings is actually much easier than many people make it out to be initially

Who this course is for:

Computer vision and machine learning

Detect and recognize faces, identify objects, classify human actions in videos, track camera movements, track moving objects, extract 3D models of objects, produce 3D point clouds from stereo cameras

Stitch images together to produce a high resolution image of an entire scene

Find similar images from an image database, remove red eyes from images taken using flash, follow eye movements, recognize scenery and establish markers to overlay it with augmented reality, etc