Master Computer Vision™ OpenCV4 in Python with Deep Learning

Requirements

Basic programming knowledge is helpful, but not essential.
Windows 10, Ubuntu, or MacOS systems
You can use the webcam to execute some of these mini-projects

Description

OpenCV’s most comprehensive and well-taught course is now open! Here you’ll learn how OpenCV works. Master Computer Vision with the latest version OpenCV4 in Python!

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NOTE: Some of the poor reviews were made during an outdated period in the course material. Many of the example codes were broken. However, this has been corrected as of early 2019.

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Computer Artificial Intelligence deals with Vision. with Computer algorithms are able to decipher what they see in images! Master This skill will allow you to finish your University/College Projects and automate some at work. You can also start developing your startup idea, or get the skills to be a high-paying ($400-$1000 USD/Day). Computer Vision Engineer.

Here’s What You’ll Get in Master Computer Vision™ OpenCV4 in Python with Deep Learning

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Last Updated: Aug 2019. You will learn:

These are the key concepts Computer Vision & OpenCV (using the newest version OpenCV4)

There are many techniques for image manipulations. Such as cropping, blurring or thresholding, edge detection, cropping, and transformations.

Segmentation of images is possible by understanding contours, circle and line detection. Even more, you’ll learn how to approximate contours and do contour filtering as well as ordering and approximations.

Feature detection (SIFT, SURF, FAST, BRIEF & ORB) to do object detection.

Object Detection for faces, people & cars.

For face analysis, face filters and face swaps, extract facial landmarks.

Machine Learning in Computer Vision for handwritten digit recognition.

Facial Recognition

Motion Analysis & Object Tracking.

Photo Restoration using Computational Photography Techniques (remove marks, lines, wrinkles, and smudges)

Deep Learning (3+ hours) Deep Learning with Keras in Python)

Computer Vision Product and Startup Ideas

Multi Object Detection (90 Object Types)

Colorize Black & White Photos and Video (using Caffe)

Neural Style Transfers – Add the artistic style and flair of Picasso, Van Gogh, and other artists to any image you input with your webcam.

Automatic Number-Plate Recognition

Credit Card Number Identification with PyTesseract)

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You will also be involved in 21 amazing projects!

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OpenCV Projects include:

Live Drawing Sketch with your webcam

How to Identify Shapes

Counting Ellipses and Circles

Finding Waldo

Single Object Detectors using OpenCV

Cascade Classifiers are used to detect pedestrians and cars

Live Face Swapper (like MSQRD & Snapchat filters!!!)

Yawn Detector, and Counter

Handwritten Digit Classification

Facial Recognition

Ball Tracking

Photo-Restoration

Automatic Number-Plate Recognition

Neural Style Transfer Mini Project

Multi Object Detection in OpenCV (upto 90 objects!) using SSD (Single Shot Detector)

Colorize Black & White Photos and Video

Deep Learning These projects include:

Make a handwritten digital classifier

Create a multi-image classifier

Make a Cats-vs. Dogs Classifier

How to improve CNN performance with Data Augmentation

Sort and classify credit card numbers

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These are the words of former students:

“I’m amazed at the possibilities. Very educational, learning more than what I ever thought was possible. Now, being able to actually use it in a practical purpose is intriguing…. much more to learn & apply”

“Extremely well taught and informative Computer Vision course! I’ve trawled the web looking for Opencv python tutorials resources but this course was by far the best amalgamation of relevant lessons and projects. Loved some of the projects and had lots of fun tinkering them.”

“Awesome instructor and course. The explanations are really easy to understand and the materials are very easy to follow. Definitely a really good introduction to image processing.”

Get your instant download Master Computer Vision™ OpenCV4 in Python with Deep Learning
“I am extremely impressed by this course!! I think this is by far the best Computer Vision course on Udemy. I’m a college student who had previously taken a Computer Vision course in undergrad. This 6.5 hour course blows away my college class by miles!!”

“Rajeev did a great job on this course. I had no idea how computer vision worked and now have a good foundation of concepts and knowledge of practical applications. Rajeev is clear and concise which helps make a complicated subject easy to comprehend for anyone wanting to start building applications.”

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Why Learn Computer Vision in Python OpenCV?

Computer Vision applications and technology are on the rise 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!

Computer vision expertise is in high demand.

But, computer vision is difficult to learn! Online tutorials, textbooks, or free MOOCs can be difficult to comprehend because they often use outdated libraries and are too theoretical.

This was my problem while learning. Computer Vision was frustrating and difficult to use. Even running an example of code that I found online was difficult because libraries and functions were frequently outdated.

This course teaches you the fundamental concepts of the subject without any heavy mathematics and uses the most current methods.

I am very practical and use more than 50 Code Examples.

You will be able build 12 Awesome things at the end of this course. Computer Vision Apps using OpenCV in Python.

OpenCV, the most supported open-source computer visual library available, is what I use. Use it in Python This is amazing! Python It allows us focus on the problem at issue without worrying about complex code.

I can still point you in the right direction if you are a college student or academic. in If you are interested in learning more, we can point you in the right direction by linking to the research papers and techniques that we use.

If you are looking for a great foundation, in Computer Vision, you don’t need to look any further.

This is your course!

This course will teach you how to use OpenCV. in PythonGet skills to significantly improve your career prospects. Computer Vision developer.

You will get more than 3 hours of training Deep Learning in Computer Vision with Keras includes:

Get a free virtual machine with All Deep Learning Python Libraries like Keras or TensorFlow are pre-installed

A detailed explanation of Neural Networks, Convolutional Neural networks and their applications

How Keras works. Learn how to use Keras and how you can create image datasets.

Make a handwritten digital classifier

Create a multi-image classifier

Make a Cats-vs. Dogs Classifier

How to improve CNN performance with Data Augmentation

Extract and classify credit card number

For updates and support:

Each month I will keep you updated with new fixes and amazing projects.

I will be present every day in You will never be on your own in the ‘questions, answers’ section.

Are you ready to start? Register now to begin the journey of becoming a master. in Computer Vision today!
Who is this course for?

If you are a beginner and have an interest in computer vision
For college students who want to get a jump start on their computer vision research,
If you are interested in using it, Deep Learning For Computer Vision
Computer vision startups for entrepreneurs
Hobbyists looking to create a cool prototype of computer vision
Software developers and engineers who want to learn computer vision skills