English | MP4 | AVC 1920×1080 | AAC 48KHz 2ch | 8h 50m | 2.32 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. So, learning and mastering this fantastic world of Computer Vision-based technology is surely up-market. 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.
So, overall this is a complete package in which you can learn Computer Vision-based Technology, Deep Learning-based Face Detection, then Face Recognition and Optical Character Recognition.
And by the end of this course, we will provide you with a course completion certificate which you can keep with you and mention it in your portfolio so that you will be having more weight when you are dealing with jobs based on Computer Vision Technology.
So without wasting much time, let’s dive into this magical world. See you soon in the class room. Have a great time.
This course is designed in such a way that each section will cover new scenarios and a step by step approach to help you learn and understand the concept.
What You Will Learn
- Learn all the important functionalities of OpenCV Library
- Implement Face Detection, Face Recognition and Optical Character Recognition
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 Blurring – Part 1
39 OpenCV – Image Blurring – Part 2
40 OpenCV – Image Blurring – 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
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