Requirements

Programming knowledge is not necessary, but it will be helpful to have some programming knowledge.
Windows 10 or Ubuntu or MacOS
You can use the webcam to execute some of these mini-projects

Description

You’re invited to attend one of the best OpenCV courses, where you will learn how to use OpenCV. Master Computer Vision using the most recent 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NOTE: Some of the poor reviews were made during an outdated period in the course material.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.

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Last Updated: Aug 2019. You will be learning:

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

There are many techniques for image manipulation. These include cropping, blurring and thresholding, edge detection, cropping, cropping, blurring, thresholding, thresholding, and cropping.

Segmentation by understanding contours and circle. You will also learn how contour filters and ordering can be used.

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 by Computational Photography (eliminate marks and lines from damaged photos, creases, and streaks).

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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21 amazing projects will also be implemented!

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OpenCV Projects:

• Live Drawing Sketch with your webcam
• Identifying Shapes
• Counting Ellipses and Circles
• Finding Waldo
• Single Object Detectors using OpenCV
• Cascade Classifiers for Car and Pedestrian Detector
• Live Face Swapper (like MSQRD & Snapchat filters!!!)
• Yawn Detector & 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 Some of the projects are:
• Make a handwritten digital classifier
• Create a multi-image classifier
• Create a Cats and 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.”

“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. It was difficult to even run example code that I had found online, as libraries and functions are often out of date.

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.

The course will allow you to create 12 Awesome Projects at the end. 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 It is simply 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 You are in the right place if you want to know more.

You should consider these things if you wish to have a solid foundation. in Computer Vision is what you need.

This is the right course!

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

You will get more than 3 hours of training Deep Learning in Computer Vision using Keras, including:

Get a free virtual machine with All Deep Learning Python Libraries like Keras and TensorFlow already installed

Details on Convolutional Neural and Neural Networks

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

Make a handwritten digital classifier

A Multi-Image Classifier can be built

Create a Cats and Dogs Classifier

How to improve CNN performance with Data Augmentation

Sort and classify credit card numbers

Support and Updates:

Every month, I will continue to add updates, fixes, or new projects!

I will be present every day in The ‘questions & answers’ section of the course will ensure that you are always in the know.

Are you ready? Start the journey to mastery by enrolling now in Computer Vision today!

Who is this course for?

• Beginners who are interested in learning in computer vision
• For college students who want to get a jump start on their computer vision research,
• Anybody interested in learning more about it Deep Learning For Computer Vision
• Entrepreneurs seeking to start a computer vision startup
• Hobbyists who want to build a cool prototype for computer vision
• Software developers and engineers who want to learn computer vision skills