Section 1 : Course Overview and Introduction
Lecture 1 About Certification
Lecture 2 INTRODUCTION TO BRAINMEASURES PROCTOR SYSTEM
Lecture 3 Course Curriculum Overview 00:04:40 Duration
Lecture 4 Getting Set-Up for the Course Content 00:12:45 Duration

Section 2 : NumPy and Image Basics
Lecture 1 Introduction to Numpy and Image Section 00:00:41 Duration
Lecture 2 NumPy Arrays 00:16:49 Duration
Lecture 3 What is an image 00:05:53 Duration
Lecture 4 Images and NumPy 00:12:23 Duration
Lecture 5 NumPy and Image Assessment Test 00:02:40 Duration
Lecture 6 NumPy and Image Assessment Test - Solutions 00:08:46 Duration

Section 3 : Image Basics with Open CV
Lecture 1 Introduction to Images and OpenCV Basics 00:02:37 Duration
Lecture 2 Opening Image files in a notebook 00:19:30 Duration
Lecture 3 Opening Image files with OpenCV 00:10:50 Duration
Lecture 4 Drawing on Images - Part One - Basic Shapes 00:10:01 Duration
Lecture 5 Drawing on Images Part Two - Text and Polygons 00:09:30 Duration
Lecture 6 Direct Drawing on Images with a mouse - Part One 00:09:36 Duration
Lecture 7 Direct Drawing on Images with a mouse - Part Two 00:02:42 Duration
Lecture 8 Direct Drawing on Images with a mouse - Part Three 00:10:26 Duration
Lecture 9 Image Basics Assessment 00:05:16 Duration
Lecture 10 Image Basics Assessment Solutions

Section 4 : Image Processing
Lecture 1 Introduction to Image Processing 00:00:40 Duration
Lecture 2 Remove - INTRODUCTION TO BRAINMEASURES PROCTOR SYS
Lecture 3 Blending and Pasting Images 00:14:15 Duration
Lecture 4 Blending and Pasting Images Part Two - Masks 00:15:56 Duration
Lecture 5 Image Thresholding 00:17:41 Duration
Lecture 6 Blurring and Smoothing 00:06:43 Duration
Lecture 7 Blurring and Smoothing - Part Two 00:19:45 Duration
Lecture 8 Morphological Operators 00:15:27 Duration
Lecture 9 Gradients 00:13:40 Duration
Lecture 10 Histograms - Part One 00:12:34 Duration
Lecture 11 Histograms - Part Two - Histogram Eqaulization 00:12:20 Duration
Lecture 12 Histograms Part Three - Histogram Equalization 00:08:13 Duration
Lecture 13 Image Processing Assessment 00:03:52 Duration
Lecture 14 Image Processing Assessment Solutions 00:08:31 Duration

Section 5 : Video Basics with Python and Open CV
Lecture 1 Introduction to Video Basics 00:01:05 Duration
Lecture 2 Connecting to Camera 00:14:14 Duration
Lecture 3 Using Video Files 00:07:00 Duration
Lecture 4 Drawing on Live Camera 00:16:46 Duration
Lecture 5 Video Basics Assessment
Lecture 6 Video Basics Assessment Solutions 00:05:01 Duration

Section 6 : Object Detection with Open CV and Python
Lecture 1 Introduction to Object Detection 00:02:27 Duration
Lecture 2 Template Matching 00:17:42 Duration
Lecture 3 Corner Detection - Part One - Harris Corner Detect 00:14:09 Duration
Lecture 4 Corner Detection - Part Two - Shi-Tomasi Detection 00:14:09 Duration
Lecture 5 Edge Detection
Lecture 6 Grid Detection 00:08:17 Duration
Lecture 7 Contour Detection 00:11:11 Duration
Lecture 8 Feature Matching - Part One 00:12:26 Duration
Lecture 9 Feature Matching - Part Two 00:18:29 Duration
Lecture 10 Watershed Algorithm - Part One.
Lecture 11 Watershed Algorithm - Part Two 00:20:15 Duration
Lecture 12 Custom Seeds with Watershed Algorithm 00:18:55 Duration
Lecture 13 Introduction to Face Detection 00:09:12 Duration
Lecture 14 Face Detection with OpenCV
Lecture 15 Detection Assessment 00:03:27 Duration
Lecture 16 Detection Assessment Solutions 00:07:11 Duration

Section 7 : Object Tracking
Lecture 1 Introduction to Object Tracking 00:00:35 Duration
Lecture 2 Optical Flow 00:05:38 Duration
Lecture 3 Optical Flow Coding with OpenCV - Part One 00:18:35 Duration
Lecture 4 Optical Flow Coding with OpenCV - Part Two 00:10:58 Duration
Lecture 5 MeanShift and CamShift Tracking Theory 00:05:48 Duration
Lecture 6 MeanShift and CamShift Tracking with OpenCV 00:14:42 Duration
Lecture 7 Overview of various Tracking API Methods 00:06:50 Duration
Lecture 8 Tracking APIs with OpenCV 00:06:53 Duration

Section 8 : Deep Learning for ComputerVision
Lecture 1 Introduction to Deep Learning for Computer Vision 00:02:29 Duration
Lecture 2 Machine Learning Basics 00:06:55 Duration
Lecture 3 Understanding Classification Metrics 00:14:13 Duration
Lecture 4 Introduction to Deep Learning Topics 00:01:25 Duration
Lecture 5 Understanding a Neuron 00:05:13 Duration
Lecture 6 Understanding a Neural Network 00:06:31 Duration
Lecture 7 Cost Functions 00:03:40 Duration
Lecture 8 Gradient Descent and Back Propagation 00:03:21 Duration
Lecture 9 Keras Basics 00:18:02 Duration
Lecture 10 MNIST Data Overview 00:04:41 Duration
Lecture 11 Convolutional Neural Networks Overview - Part One 00:18:53 Duration
Lecture 12 Convolutional Neural Networks Overview - Part Two 00:04:24 Duration
Lecture 13 Keras Convolutional Neural Networks with MNIST 00:17:08 Duration
Lecture 14 Keras Convolutional Neural Networks with CIFAR-10 00:11:59 Duration
Lecture 15 LINK FOR CATS AND DOGS ZIP
Lecture 16 INTRODUCTION TO BRAINMEASURES PROCTOR SYSTEM
Lecture 17 Deep Learning on Custom Images - Part Two 00:19:35 Duration
Lecture 18 Deep Learning and Convolutional Neural Networks As 00:02:37 Duration
Lecture 19 Deep Learning and Convolutional Neural Networks As 00:07:08 Duration
Lecture 20 Introduction to YOLO v3 00:03:17 Duration
Lecture 21 YOLO Weights Download
Lecture 22 YOLO v3 with Python 00:17:05 Duration

Section 9 : Capstone Project
Lecture 1 Introduction to CapStone Project 00:00:51 Duration
Lecture 2 Capstone Part One - Variables and Background funct 00:07:47 Duration
Lecture 3 Capstone Part Two - Segmentation 00:06:01 Duration
Lecture 4 Capstone Part Three - Counting and ConvexHull 00:14:18 Duration
Lecture 5 Capstone Part Four - Bringing it all together 00:12:15 Duration