Description

Welcome to one of the most thorough and well taught courses on OpenCV, where you’ll learn how to Master Computer Vision using newest version of OpenCV4 in Python!

You will be learning:

   The key concepts of Computer Vision & OpenCV (using the newest version OpenCV 4)
   To perform image manipulations such as transformations, cropping, blurring, thresholding, edge detection and cropping.
   To segment images by understanding contours, circle, and line detection. You’ll even learn how to approximate contours, do contour filtering and ordering as well as approximations.
   Use feature detection (SIFT, SURF, FAST, BRIEF & ORB) to do object detection.
   Implement Object Detection for faces, people & cars.
   Extract facial landmarks for face analysis, applying filters and face swaps.
   Implement Machine Learning in Computer Vision for handwritten digit recognition.
   Implement Facial Recognition.
   Implement and understand Motion Analysis & Object Tracking.
   Use basic computational photography techniques for Photo Restoration (eliminate marks, lines, creases, and smudges from old damaged photos).
   How to become a true computer vision expert by getting started in Deep Learning ( 3+ hours of Deep Learning with Keras in Python)
   How to develop Computer Vision Product Ideas
   How to perform Multi Object Detection (90 Object Types)
   How to colorize Black & White Photos and Video
   Neural Style Transfers – Apply the artistic style of Van Gogh, Picasso and others to any image even your webcam input
   How to make your own Automatic Number-Plate Recognition (ALPR
   Credit Card Number Identification (Build your own OCR Classifier with PyTesseract)

OpenCV Projects Include:

   Live Drawing Sketch using your webcam
   Identifying Shapes
   Counting Circles and Ellipses
   Finding Waldo
   Single Object Detectors using OpenCV
   Car and Pedestrian Detector using Cascade Classifiers
   Live Face Swapper (like MSQRD & Snapchat filters!!!)
   Yawn Detector and Counter
   Handwritten Digit Classification
   Facial Recognition
   Ball Tracking
   Photo-Restoration
   Automatic Number-Plate Recognition (ALPR)
   Neural Style Transfer Mini Project
   Multi Object Detection in OpenCV (up to 90 Objects!) using SSD (Single Shot Detector)
   Colorize Black & White Photos and Video

Deep Learning Projects Include:

   Build a Handwritten Digit Classifier
   Build a Multi Image Classifier
   Build a Cats vs Dogs Classifier
   Understand how to boost CNN performance using Data Augmentation
   Extract and Classify Credit Card Numbers

Why Learn Computer Vision in Python using OpenCV?

Computer vision applications and technology are exploding right now! With several apps and industries making amazing use of the technology, from billion dollar apps such as Pokémon GO, Snapchat and up and coming apps like MSQRD and PRISMA.

Even Facebook, Google, Microsoft, Apple, Amazon, and Tesla are all heavily utilizing computer vision for face & object recognition, image searching and especially in Self-Driving Cars!

As a result, the demand for computer vision expertise is growing exponentially!

However, learning computer vision is hard! Existing online tutorials, textbooks, and free MOOCs are often outdated, using older an incompatible libraries or are too theoretical, making it difficult to understand.

This was my problem when learning Computer Vision and it became incredibly frustrating. Even simply running example code I found online proved difficult as libraries and functions were often outdated.

I created this course to teach you all the key concepts without the heavy mathematical theory while using the most up to date methods.

I take a very practical approach, using more than 50 Code Examples.

At the end of the course, you will be able to build 12 Awesome Computer Vision Apps using OpenCV in Python.

I use OpenCV which is the most well supported open source computer vision library that exists today! Using it in Python is just fantastic as Python allows us to focus on the problem at hand without being bogged down by complex code.

If you’re an academic or college student I still point you in the right direction if you wish to learn more by linking the research papers of techniques we use.

So if you want to get an excellent foundation in Computer Vision, look no further.

This is the course for you!

In this course, you will discover the power of OpenCV in Python, and obtain skills to dramatically increase your career prospects as a Computer Vision developer.

You get 3+ Hours of Deep Learning in Computer Vision using Keras, which includes:

   A free Virtual Machine with all Deep Learning Python Libraries such as Keras and TensorFlow pre-installed
   Detailed Explanations on Neural Networks and Convolutional Neural Networks
   Understand how Keras works and how to use and create image datasets
   Build a Handwritten Digit Classifier
   Build a Multi Image Classifier
   Build a Cats vs Dogs Classifier
   Understand how to boost CNN performance using Data Augmentation
   Extract and Classify Credit Card Numbers

As for Updates and support:

I will be continuously adding updates, fixes, and new amazing projects every month!

I will be active daily in the ‘questions and answers’ area of the course, so you are never on your own.

So, are you ready to get started? Enroll now and start the process of becoming a master in Computer Vision today!
Who this course is for:

   Beginners who have an interest in computer vision
   College students looking to get a head start before starting computer vision research
   Anyone curious using Deep Learning for Computer Vision
   Entrepreneurs looking to implement computer vision startup ideas
   Hobbyists wanting to make a cool computer vision prototype
   Software Developers and Engineers wanting to develop a computer vision skillset

Requirements

   Little to no programming knowledge is needed, but basic programing knowledge will help
   Windows 10 or Ubuntu or a MacOS system
   A webcam to implement some of the mini projects

Last updated 6/2019