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The Complete Course of OpenCV: Step-by-Step Instructions
What you’ll learn
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Starting with an overview of what the course will be covering
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We move on to discussing morphological operations and practically learn how they work on images
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We will then learn contrast enhancement using equalization and contrast limiting
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We will learn 3 methods to subtract the background from the video and implement them using OpenCV
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
- 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
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