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What you'll learn


  • ✓ Understand and use OpenCV4 in Python                                            ✓ How to use Deep Learning using Keras & TensorFlow

  • ✓ Create Face Detectors & Recognizers                                                 ✓ Object Detection, Tracking and Motion Analysis

  • ✓ Create Augmented Reality Apps                                                          ✓ Programming skills such as basic Python and Numpy

  • ✓ How to use Computer Vision in executing cool startup ideas               ✓ Understand Neural and Convolutional Neural

  • ✓ Learn to build simple Image Classifiers                                               ✓ Learn to build an OCR Reader for Credit Cards

  • ✓ Learn to Perform Neural Style Transfer Using OpenCV                      ✓ Multi Object Detection in OpenCV (up to 90 Objects!)

  • ✓ convert black and white Images to color using Caffe                          ✓ Automatic Number (License) Plate Recognition (ALPR)

Course content:


20 sections    • 116 lectures   • 10h 6m 4s total length                                                                            Expand all sections

Introduction


• Introduction to Computer Vision and OpenCV


• About this course


• READ THIS - Guide to installing and setting up your OpenCV4.0.1 Virtual Machine


• Setup your OpenCV4.0.1 Virtual Machine


• Installation of OpenCV & Python on Windows


• Installation of OpenCV & Python on Mac


• Installation of OpenCV & Python on Linux


• Set up course materials (DOWNLOAD LINK BELOW) - Not needed if using the new VM


• What are Images?


• How are Images Formed?


• Storing Images on Computers


• Getting Started with OpenCV - A Brief OpenCV Intro


• Grayscaling - Converting Color Images To Shades of Gray


• Understanding Color Spaces - The Many Ways Color Images Are Stored Digitally


• Histogram representation of Images - Visualizing the Components of Images


• Creating Images & Drawing on Images - Make Squares, Circles, Polygons & Add Text


• Transformations, Affine And Non-Affine - The Many Ways We Can Change Images


• Image Translations - Moving Images Up, Down. Left And Right


• Rotations - How To Spin Your Image Around And Do Horizontal Flipping


• Scaling, Re-sizing and Interpolations - Understand How Re-Sizing Affects Quality


• Intro to Methods on a Series Object


• Image Pyramids - Another Way of Re-Sizing


• Cropping - Cut Out The Image The Regions You Want or Don't Want


• Arithmetic Operations - Brightening and Darkening Images


• Bitwise Operations - How Image Masking Works


• Sharpening - Reverse Your Images Blurs


• Thresholding (Binarization) - Making Certain Images Areas Black or White


• Dilation, Erosion, Opening/Closing - Importance of Thickening/Thinning Lines


• Edge Detection using Image Gradients & Canny Edge Detection


• Perspective & Affine Transforms - Take An Off Angle Shot & Make It Look Top Down


• Mini Project 1 - Live Sketch App - Turn your Webcam Feed Into A Pencil Drawing


• Segmentation and Contours - Extract Defined Shapes In Your Image


• Sorting Contours - Sort Those Shapes By Size


• Approximating Contours & Finding Their Convex Hull - Clean Up Messy Contours


• Matching Contour Shapes - Match Shapes In Images Even When Distorted


• Mini Project 2 - Identify Shapes (Square, Rectangle, Circle, Triangle & Stars)


• Line Detection - Detect Straight Lines E.g. The Lines On A Sudoku Game


• Circle Detection


• Blob Detection - Detect The Center of Flowers


• Mini Project 3 - Counting Circles and Ellipses


• Object Detection Overview


• Mini Project # 4 - Finding Waldo (Quickly Find A Specific Pattern In An Image)


• Feature Description Theory - How We Digitally Represent Objects


• Finding Corners - Why Corners In Images Are Important to Object Detection


• SIFT, SURF, FAST, BRIEF & ORB - Learn The Different Ways To Get Image Features


• Mini Project 5 - Object Detection - Detect A Specific Object Using Your Webcam


• Histogram of Oriented Gradients - Another Novel Way Of Representing Images


• HAAR Cascade Classifiers - Learn How Classifiers Work And Why They're Amazing


• Face and Eye Detection - Detect Human Faces and Eyes In Any Image


• Mini Project 6 - Car and Pedestrian Detection in Videos


• Face Analysis and Filtering - Identify Face Outline, Lips, Eyes Even Eyebrows


• Merging Faces (Face Swaps) - Combine Two Faces For Fun & Sometimes Scary Results


• Mini Project 7 - Live Face Swapper (like MSQRD & Snapchat filters!!!)


• Mini Project 8 - Yawn Detector and Counter


• Machine Learning Overview - What Is It & Why It's Important to Computer Vision


• Mini Project 9 - Handwritten Digit Classification


• Mini Project # 10 - Facial Recognition - Make Your Computer Recognize You


• Filtering by Color


• Background Subtraction and Foreground Subtraction


• Using CAMshift for Object Tracking


• Using Meanshift for Object Tracking


• Optical Flow - Track Moving Objects In Videos


• Mini Project # 11 - Ball Tracking


• Mini Project # 12 - Photo-Restoration


• Mini Project # 13 - Automatic Number-Plate Recognition (ALPR


• Course Summary and how to become an Expert


• Latest Advances, 12 Startup Ideas & Implementing Computer VIsion in Mobile Apps


Description:


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

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NOTE: Many of the earlier poor reviews was during a period of time when the course material was outdated and many of the example code was broken, however, this has been fixed as of early 2019 :)

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Computer Vision is an area of Artificial Intelligence that deals with how computer algorithms can decipher what they see in images! Master this incredible skill and be able to complete your University/College Projects, automate something at work, start developing your startup idea or gain the skills to become a high paying ($400-$1000 USD/Day) Computer Vision Engineer.

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Last Updated Aug 2019, you will be learning:

  1. Key concepts of Computer Vision & OpenCV (using the newest version OpenCV4)

  2. Image manipulations (dozens of techniques!) such as transformations, cropping, blurring, thresholding, edge detection and cropping.

  3. Segmentation of 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.

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

  5. Object Detection for faces, people & cars.

  6. Extract facial landmarks for face analysis, applying filters, and face swaps.

  7. Machine Learning in Computer Vision for handwritten digit recognition.

  8. Facial Recognition.

  9. Motion Analysis & Object Tracking.

  10. Computational photography techniques for Photo Restoration (eliminate marks, lines, creases, and smudges from old damaged photos).

  11. Deep Learning ( 3+ hours of Deep Learning with Keras in Python)

  12. Computer Vision Product and Startup Ideas

  13. Multi-Object Detection (90 Object Types)

  14. Colorize Black & White Photos and Video (using Caffe)

  15. Neural Style Transfers - Apply the artistic style of Van Gogh, Picasso, and others to any image even your webcam input

  16. Automatic Number-Plate Recognition (ALPR

  17. Credit Card Number Identification (Build your own OCR Classifier with PyTesseract)

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You'll also be implementing 21 awesome projects! 

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OpenCV Projects Include:

  1. Live Drawing Sketch using your webcam

  2. Identifying Shapes

  3. Counting Circles and Ellipses

  4. Finding Waldo

  5. Single Object Detectors using OpenCV

  6. Car and Pedestrian Detector using Cascade Classifiers

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

  8. Yawn Detector and Counter

  9. Handwritten Digit Classification

  10. Facial Recognition

  11. Ball Tracking

  12. Photo-Restoration

  13. Automatic Number-Plate Recognition (ALPR)

  14. Neural Style Transfer Mini Project

  15. Multi-Object Detection in OpenCV (up to 90 Objects!) using SSD (Single Shot Detector)

  16. Colorize Black & White Photos and Video

Deep Learning Projects Include:

  1. Build a Handwritten Digit Classifier

  2. Build a Multi-Image Classifier

  3. Build a Cats vs Dogs Classifier

  4. Understand how to boost CNN performance using Data Augmentation

  5. Extract and Classify Credit Card Numbers

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What previous students have said: 

"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."

"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 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 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:

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:


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