Section 1 : Course Introduction and Setup
Lecture 1 Introduction 00:01:57 Duration
Lecture 2 Introduction to Computer Vision and OpenCV 00:03:09 Duration
Lecture 3 About this course 00:05:14 Duration
Lecture 4 READ THIS - Guide to installing and setting up you
Lecture 5 Recomended - Setup your OpenCV4.0.1 Virtual Machin 00:05:42 Duration
Lecture 6 Windows+OpenCV+Installation
Lecture 7 Installation of OpenCV & Python on Mac
Lecture 8 Installation of OpenCV & Python on Linux
Lecture 9 Set up course materials (DOWNLOAD LINK BELOW) - No 00:01:42 Duration

Section 2 : Basics of Computer Vision and OpenCV
Lecture 1 What are Images 00:02:27 Duration
Lecture 2 How are Images Formed 00:03:20 Duration
Lecture 3 Storing Images on Computers 00:05:24 Duration
Lecture 4 Getting Started with OpenCV - A Brief OpenCV Intro 00:09:20 Duration
Lecture 5 Grayscaling - Converting Color Images To Shades of 00:02:00 Duration
Lecture 6 Understanding Color Spaces - The Many Ways Color I 00:12:13 Duration
Lecture 7 Histogram representation of Images - Visualizing t 00:04:38 Duration
Lecture 8 Creating Images & Drawing on Images - Make Squares 00:03:47 Duration

Section 3 : Image Manipulations & Processing
Lecture 1 Transformations, Affine And Non-Affine - The Many 00:02:22 Duration
Lecture 2 Image Translations - Moving Images Up, Down. Left 00:02:47 Duration
Lecture 3 Rotations - How To Spin Your Image Around And Do H 00:03:11 Duration
Lecture 4 Scaling, Re-sizing and Interpolations - Understand 00:04:27 Duration
Lecture 5 Image Pyramids - Another Way of Re-Sizing 00:01:53 Duration
Lecture 6 Cropping - Cut Out The Image The Regions You Want 00:02:42 Duration
Lecture 7 Arithmetic Operations - Brightening and Darkening 00:03:37 Duration
Lecture 8 Bitwise Operations - How Image Masking Works 00:03:36 Duration
Lecture 9 Blurring - The Many Ways We Can Blur Images & Why 00:07:29 Duration
Lecture 10 Sharpening - Reverse Your Images Blurs 00:01:51 Duration
Lecture 11 Thresholding (Binarization) - Making Certain Image 00:08:39 Duration
Lecture 12 Dilation, Erosion, OpeningClosing - Importance of 00:04:58 Duration
Lecture 13 Edge Detection using Image Gradients & Canny Edge 00:04:52 Duration
Lecture 14 Perspective & Affine Transforms - Take An Off Ang 00:03:56 Duration
Lecture 15 Mini Project 1 - Live Sketch App - Turn your Webca 00:05:03 Duration

Section 4 : Image Segmentation & Contours
Lecture 1 Segmentation and Contours - Extract Defined Shapes 00:11:11 Duration
Lecture 2 Sorting Contours - Sort Those Shapes By Size 00:13:00 Duration
Lecture 3 Approximating Contours & Finding Their Convex Hull 00:05:42 Duration
Lecture 4 Matching Contour Shapes - Match Shapes In Images E 00:05:28 Duration
Lecture 5 Mini Project 2 - Identify Shapes (Square, Rectangl 00:05:30 Duration
Lecture 6 Line Detection - Detect Straight Lines E.g. The Li 00:06:24 Duration
Lecture 7 Circle Detection
Lecture 8 Blob Detection - Detect The Center of Flowers 00:03:20 Duration
Lecture 9 Mini Project 3 - Counting Circles and Ellipses 00:06:06 Duration

Section 5 : Object Detection in OpenCV
Lecture 1 Object Detection Overview 00:03:20 Duration
Lecture 2 Mini Project # 4 - Finding Waldo (Quickly Find A S 00:02:46 Duration
Lecture 3 Feature Description Theory - How We Digitally Repr 00:04:37 Duration
Lecture 4 Finding Corners - Why Corners In Images Are Import 00:06:46 Duration
Lecture 5 SIFT, SURF, FAST, BRIEF & ORB - Learn The Differen 00:10:16 Duration
Lecture 6 Mini Project 5 - Object Detection - Detect A Speci 00:14:58 Duration
Lecture 7 Histogram of Oriented Gradients - Another Novel Wa 00:08:10 Duration

Section 6 : Object Detection - Build a Face, People and CarVehicle Detec
Lecture 1 HAAR Cascade Classifiers - Learn How Classifiers W 00:05:12 Duration
Lecture 2 Face and Eye Detection - Detect Human Faces and Ey 00:10:40 Duration
Lecture 3 Mini Project 6 - Car and Pedestrian Detection in V 00:06:46 Duration

Section 7 : Augmented Reality (AR) - Facial Landmark Identification (Fac
Lecture 1 Face Analysis and Filtering - Identify Face Outlin 00:10:57 Duration
Lecture 2 Merging Faces (Face Swaps) - Combine Two Faces For 00:09:27 Duration
Lecture 3 Mini Project 7 - Live Face Swapper (like MSQRD & S
Lecture 4 Mini Project 8 - Yawn Detector and Counter 00:08:45 Duration

Section 8 : Simple Machine Learning using OpenCV
Lecture 1 Machine Learning Overview - What Is It & Why It's 00:08:54 Duration
Lecture 2 Mini Project 9 - Handwritten Digit Classification 00:20:00 Duration
Lecture 3 Mini Project # 10 - Facial Recognition - Make Your 00:12:07 Duration

Section 9 : Object Tracking & Motion Analysis
Lecture 1 Filtering by Color 00:06:15 Duration
Lecture 2 Background Subtraction and Foreground Subtraction 00:06:55 Duration
Lecture 3 Using Meanshift for Object Tracking 00:04:56 Duration
Lecture 4 Using CAMshift for Object Tracking 00:04:04 Duration
Lecture 5 Optical Flow - Track Moving Objects In Videos 00:07:18 Duration
Lecture 6 Mini Project # 11 - Ball Tracking 00:05:02 Duration

Section 10 : Computational Photography & Make a License Plate Reader
Lecture 1 Mini Project # 12 - Photo-Restoration 00:06:34 Duration
Lecture 2 Mini Project # 13 - Automatic Number-Plate Recogn

Section 11 : Conclusion
Lecture 1 Course Summary and how to become an Expert 00:02:51 Duration
Lecture 2 Latest Advances, 12 Startup Ideas & Implementing C 00:07:06 Duration

Section 12 : BONUS - Deep Learning Computer Vision 1 - Setup a Deep Learn
Lecture 1 Setup your Deep Learning Virtual Machine 00:10:28 Duration
Lecture 2 Intro to Handwritten Digit Classification (MNIST) 00:05:47 Duration
Lecture 3 Intro to Multiple Image Classification (CIFAR10) 00:02:52 Duration

Section 13 : BONUS - Deep Learning Computer Vision 2 - Introduction to Ne
Lecture 1 Neural Networks Chapter Overview 00:01:35 Duration
Lecture 2 Machine Learning Overview 00:08:26 Duration
Lecture 3 Neural Networks Explained 00:03:51 Duration
Lecture 4 Forward Propagation 00:08:34 Duration
Lecture 5 Activation Functions 00:08:31 Duration
Lecture 6 Training Part 1 – Loss Functions 00:09:13 Duration
Lecture 7 Training Part 2 – Backpropagation and Gradient Des 00:09:57 Duration
Lecture 8 Backpropagation & Learning Rates – A Worked Exampl 00:13:36 Duration
Lecture 9 Regularization, Overfitting, Generalization and Te 00:15:25 Duration
Lecture 10 Epochs, Iterations and Batch Sizes 00:03:38 Duration
Lecture 11 Measuring Performance and the Confusion Matrix 00:07:07 Duration
Lecture 12 Review and Best Practices 00:04:16 Duration

Section 14 : BONUS - Deep Learning Computer Vision 3 - Convolutional Neur
Lecture 1 Convolutional Neural Networks Chapter Overview 00:01:00 Duration
Lecture 2 Introduction to Convolutional Neural Networks (CNN 00:05:24 Duration
Lecture 3 Convolutions & Image Features 00:13:20 Duration
Lecture 4 Depth, Stride and Padding 00:06:51 Duration
Lecture 5 ReLU 00:01:48 Duration
Lecture 6 Pooling 00:04:37 Duration
Lecture 7 The Fully Connected Laye
Lecture 8 Training CNNs 00:03:08 Duration
Lecture 9 Designing Your Own CNN 00:03:48 Duration

Section 15 : BONUS - Deep Learning Computer Vision 4 - Build CNNs in Pyth
Lecture 1 Introduction to Keras & Tensorflow
Lecture 2 Building a CNN in Keras 00:12:15 Duration
Lecture 3 Building a Handwriting Recognition CNN 00:01:48 Duration
Lecture 4 Loading Our Data 00:05:42 Duration
Lecture 5 Getting our data in ‘Shape’ 00:04:04 Duration
Lecture 6 Hot One Encoding 00:02:55 Duration
Lecture 7 Building & Compiling Our Model 00:03:45 Duration
Lecture 8 Training Our Classifier 00:04:58 Duration
Lecture 9 Plotting Loss and Accuracy Charts 00:02:52 Duration
Lecture 10 Saving and Loading Your Model 00:02:52 Duration
Lecture 11 Displaying Your Model Visually 00:02:43 Duration
Lecture 12 Building a Simple Image Classifier using CIFAR10 00:07:20 Duration

Section 16 : BONUS - Deep Learning Computer Vision 5 - Build a Cats vs Do
Lecture 1 Data Augmentation Chapter Overview 00:01:00 Duration
Lecture 2 Splitting Data into Test and Training Datasets 00:10:13 Duration
Lecture 3 Train a Cats vs. Dogs Classifier
Lecture 4 Boosting Accuracy with Data Augmentation 00:05:13 Duration
Lecture 5 Types of Data Augmentation

Section 17 : BONUS - Build a Credit Card Number Reader
Lecture 1 Step 1 - Creating a Credit Card Number Datase
Lecture 2 Step 2 - Training Our Model
Lecture 3 Step 3 - Extracting A Credit Card from the Backgro
Lecture 4 Step 4 - Use our Model to Identify the Digits & D

Section 18 : BONUS - Neural Style Transfer with OpenCV
Lecture 1 Perform Neural Style Transfer Using OpenCV4

Section 19 : BONUS - Object Detection - Use SSDs (Single Shot Detector) f
Lecture 1 Using an SSD In OpenCV

Section 20 : BONUS - Colorize Black and White Images
Lecture 1 Colorizing Black and White Images Using Caffe