OpenCV Complete Dummies Guide to Computer Vision with Python

Description:

Hello and let me welcome you to the magical world of Computer Vision.

Computer Vision is an AI based, that is, Artificial Intelligence based technology that allows computers to understand and label images. Its now used in Convenience stores, Driver-less Car Testing, Security Access Mechanisms, Policing and Investigations Surveillance, Daily Medical Diagnosis monitoring health of crops and live stock and so on and so forth. Even to analyze data coming from outer space stars, planets etc also we use Computer Vision.

A common example will be face detection and unlocking mechanism that you use in your mobile phone. We use that daily. That is also a big application of Computer Vision. And today, top technology companies like Amazon, Google, Microsoft, Facebook etc are investing millions and millions of Dollars into Computer Vision based research and product development.

So Learning and mastering this fantastic world of Computer Vision based technology is surely up-market and it will make you proficient in competing with the swiftly changing Image Processing technology arena.

And this course is designed in such a way that even the very beginner to programming can master the Computer Vision based technology.

Here are the major topics that we are going to cover in this course.

Session 1 - Introduction to OpenCV Session 2 - Installing Virtual Box and Ubuntu 18 Session 3 - Installing Libraries and Dependencies Session 4 - Installing Sublime Text Editor for Ubuntu Session 5 - Image Processing Concepts Session 6 - OpenCV - Read Load and Save Image - Sample Program Session 7 - OpenCV Pixel and Area Manipulation Session 8 - 10 - OpenCV - Drawing Lines, Rectangles, Simple, Concentric Circles, Random Circles Session 11 - 15 - OpenCV Image Transformation - Translation, Rotation, Resizing, Flipping, Cropping Session 16 - 17 - OpenCV Image Arithmetic Operations, Bitwise / Logical Operations: Session 18 - OpenCV - Image Masking Session 19 - Image Color Channels Merging and Splitting Session 20 - OpenCV - Other Color Spaces - GRAY, HSV, LAB Session 21 - 22 - OpenCV - Gray scale Histograms, Color Histograms Session 23 - OpenCV - Histogram Equalization Session 24 - 25 - OpenCV - Image Blurring, Image Threshold Session 26 - OpenCV - Image Gradient Detectio Session 27 - OpenCV- Canny Edge Detection Session 28 - OpenCV - Image Contours Session 29 - Face Detection using OpenCV Session 30 - Face Recognition using Machine Learning Session 31 - Digital Makeup Session 32 - Face Distance Calculation Session 32 - Real Time Face Recognition using Machine Learning Session 33 - Optical Character Recognition - OCR using PyTesseract Library Session 34 - Simple Real-time motion detector using OpenCV from Camera Video Stream Session 35 - Object Recognition using pre-trained models Session 36 - Real-time Facial Expression Recognition System from Camera Video Stream

Basic knowledge:

A decent configuration computer to run Virtual Box and Linux. Only basic programming knowledge required.

Who this course is for:

Beginners who are interested in Computer Vision based technology. Developers who wish to use Computer Vision in their applications.

Course Completion Certificate

What will you learn:

Learn all the important functionalities of OpenCV Library. Implement Face Detection, Face Recognition and Optical Character Recognition

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