OpenCV Complete Dummies Guide to Computer Vision with Python

OpenCV Complete Dummies Guide to Computer Vision with Python
OpenCV Complete Dummies Guide to Computer Vision with Python
English | MP4 | AVC 1280×720 | AAC 44KHz 2ch | 9 Hours | 4.87 GB

Includes all OpenCV Image Processing Features with Simple Examples. Deep Learning Face Detection, Face Recognition & OCR

Computer Vision is an AI based, that is, Artificial Intelligence based technology that allows computers to understand and label images. Its now used in Convenience stores, Driver-less Car Testing, Security Access Mechanisms, Policing and Investigations Surveillance, Daily Medical Diagnosis monitoring health of crops and live stock and so on and so forth..

Even to analyze data coming from outer space stars, planets etc also we use Computer Vision.

A common example will be face detection and unlocking mechanism that you use in your mobile phone. We use that daily. That is also a big application of Computer Vision. And today, top technology companies like Amazon, Google, Microsoft, Facebook etc are investing millions and millions of Dollars into Computer Vision based research and product development.

So.. Learning and mastering this fantastic world of Computer Vision based technology is surely up-market and it will make you proficient in competing with the swiftly changing Image Processing technology arena.

And this course is designed in such a way that even the very beginner to programming can master the Computer Vision based technology.

Here are the major topics that we are going to cover in this course.

  • Session 1: Introduction to OpenCV
  • Session 2: Installing Virtual Box and Ubuntu 18
  • Session 3: Installing Libraries and Dependencies
  • Session 4: Installing Sublime Text Editor for Ubuntu
  • Session 5: Image Processing Concepts
  • Session 6: OpenCV: Read Load and Save Image – Sample Program
  • Session 7: OpenCV Pixel and Area Manipulation
  • Session 8 – 10: OpenCV – Drawing Lines, Rectangles, Simple, Concentric Circles, Random Circles
  • Session 11 – 15: OpenCV Image Transformation – Translation, Rotation, Resizing, Flipping, Cropping
  • Session 16 – 17: OpenCV Image Arithmetic Operations, Bitwise / Logical Operations
  • Session 18: OpenCV – Image Masking
  • Session 19: Image Color Channels Merging and Splitting
  • Session 20: OpenCV – Other Color Spaces – GRAY, HSV, LAB
  • Session 21 – 22: OpenCV – Gray scale Histograms, Color Histograms
  • Session 23: OpenCV – Histogram Equalization
  • Session 24 – 25: OpenCV – Image Blurring, Image Threshold
  • Session 26: OpenCV – Image Gradient Detection
  • Session 27: OpenCV- Canny Edge Detection
  • Session 28: OpenCV – Image Contours
  • Session 29: Face Detection using OpenCV
  • Session 30: Face Recognition using Machine Learning
  • Session 33: Optical Character Recognition – OCR using PyTesseract Library
  • Session 34: Simple Real-time motion detector using OpenCV from Camera Video Stream
  • Session 35: Object Recognition using pre-trained models
  • Session 36: Real-time Facial Expression Recognition System from Camera Video Stream
Table of Contents

Course Intro and Table of Contents
1 Course Intro and Table of Contents

Introduction to OpenCV
2 Introduction to OpenCV

Installing Virtual Box and Ubuntu 18
3 Installing Virtual Box and Ubuntu 18 – Part 1
4 Installing Virtual Box and Ubuntu 18 – Part 2

Installing Libraries and Dependencies
5 Installing Libraries and Dependencies – Part 1
6 Installing Libraries and Dependencies – Part 2

Installing Sublime Text Editor for Ubuntu
7 Installing Sublime Text Editor for Ubuntu

Image Processing Concepts
8 Image Processing Concepts

OpenCV Read Load and Save Image – Sample Program
9 OpenCV Read Load and Save Image – Sample Program – Part 1
10 OpenCV Read Load and Save Image – Sample Program – Part 2

OpenCV Pixel and Area Manipulation
11 OpenCV Pixel and Area Manipulation Part 1
12 OpenCV Pixel and Area Manipulation Part 2

OpenCV – Drawing Lines and Rectangles
13 OpenCV – Drawing Lines and Rectangles

OpenCV – Drawing Circles – Simple and Concentric Circles
14 OpenCV Drawing Circles – Simple and Concentric Circles

OpenCV – Drawing Random Circles
15 OpenCV – Drawing Random Circles

OpenCV Image Transformation – Translation
16 OpenCV Image Transformation – Translation – Part 1
17 OpenCV Image Transformation – Translation – Part 2

OpenCV Image Transformation – Rotation
18 OpenCV Image Transformation – Rotation

OpenCV Image Transformation – Resizing
19 OpenCV Image Transformation – Resizing – Part 1
20 OpenCV Image Transformation – Resizing – Part 2

OpenCV Image Transformation – Flipping
21 OpenCV Image Transformation – Flipping

OpenCV Image Transformation – Cropping
22 OpenCV Image Transformation – Cropping

OpenCV Image Arithmetic Operations
23 OpenCV Image Arithmetic Operations – Part 1
24 OpenCV Image Arithmetic Operations – Part 2

OpenCV Image Bitwise Logical Operations
25 OpenCV Image Bitwise Logical Operations – Part 1
26 OpenCV Image Bitwise Logical Operations – Part 2

OpenCV – Image Masking
27 OpenCV – Image Masking – Part 1
28 OpenCV – Image Masking – Part 2

Image Color Channels Merging and Splitting
29 OpenCV Image Color Channels Merging and Splitting Part 1
30 OpenCV Image Color Channels Merging and Splitting Part 2

OpenCV – Other Color Spaces – GRAY, HSV, LAB
31 OpenCV – Other Color Spaces – GRAY, HSV, LAB

OpenCV – Gray scale Histograms
32 OpenCV – Gray scale Histograms – Part 1
33 OpenCV – Gray scale Histograms – Part 2

OpenCV – Color Histograms
34 OpenCV – Color Histograms

OpenCV – Histogram Equalization
35 OpenCV – Histogram Equalization

OpenCV – Image Blurring
36 OpenCV – Image Blurring – Part 1
37 OpenCV – Image Blurring – Part 2

OpenCV – Image Threshold
38 OpenCV – Image Threshold – Part 1
39 OpenCV – Image Threshold – Part 2
40 OpenCV – Image Threshold – Part 3

OpenCV – Image Gradient Detection
41 OpenCV – Image Gradient Detection – Part 1
42 OpenCV – Image Gradient Detection – Part 2

OpenCV- Canny Edge Detection
43 OpenCV- Canny Edge Detection

OpenCV – Image Contours
44 OpenCV – Image Contours – Part 1
45 OpenCV – Image Contours – Part 2

Face Detection using OpenCV
46 Face Detection using OpenCV – Part 1
47 Face Detection using OpenCV – Part 2
48 Face Detection using OpenCV – Part 3

Face Recognition using Machine Learning
49 Face Recognition using Machine Learning – Part 1
50 Face Recognition using Machine Learning – Part 2
51 Face Recognition using Machine Learning – Part 3

Digital Face Makeup
52 Digital Face Makeup – Part 1
53 Digital Face Makeup – Part 2

Face Distance Value of Face Recognition
54 Face Distance Value of Face Recognition

Real Time Face Recognition
55 Face Recognition in Real Time

OpenCV – Real time Facial Expression Recognition
56 Real time Facial Expression Recognition – Part 1
57 Real time Facial Expression Recognition – Part 2

A Basic Motion Detection System using Open CV
58 A Basic Motion Detection System using Open CV

Optical Character Recognition – OCR using PyTesseract Library
59 Optical Character Recognition – OCR – Part 1
60 Optical Character Recognition – OCR – Part 2
61 Optical Character Recognition – OCR – Part 3

System Preparation – Object Detection using Pre-Trained Models – Introduction
62 Object Detection using Pre-Trained Models – System Preparation & Introduction

SSD MobileNet – Object Detection using Pre-Trained Models
63 Object Detection using Pre-Trained Models – SSD MobileNet – Part 1
64 Object Detection using Pre-Trained Models – SSD MobileNet – Part 2

Mask R-CNN – Object Detection using Pre-Trained Models
65 Mask R-CNN – Object Detection using Pre-Trained Models – Part 1
66 Mask R-CNN – Object Detection using Pre-Trained Models – Part 2
67 Mask R-CNN – Object Detection using Pre-Trained Models – Part 3

YOLO – Object Detection using Pre-Trained Models
68 YOLO – Object Detection using Pre-Trained Models