Image Processing using OpenCV from Zero to Hero, 8 Projects

Image Processing using OpenCV from Zero to Hero, 8 Projects

English | MP4 | AVC 1280×720 | AAC 44KHz 2ch | 5h 13m | 1.85 GB

Complete practical and project based learning on image processing with OpenCV Python

Image Processing is one of the areas of Data Science and has a wide variety of applications in the industries in the current world. Many industries looking for a Data Scientist with these skills. This course is completely project-based learning. Where you will do the project after completion of every module. Here I will cover the image processing from basics to advanced techniques including applied machine learning algorithms and models to images.


  • Image Basics
  • Drawings
  • Image Translation
  • Image Processing Techniques
  • Smoothing Filters
  • Filters
  • Graphical Use Interphase (GUI) in OpenCV

Key Highlights in Section 1 to 7

We will start the course with very basic like load, display images. With that, we will understand the basic mathematics background behind the images. Also, I will teach you the concepts of Drawings and Videos.

Projects (Object Detection):

Face Detection using Viola-Jones Algorithm

Face Detection using Deep Neural Networks (SSD ResNet 10, Caffe Implementation)

Real-Time Face Detection

Facial Landmark Detection

Key Highlights in Section 8 to 11

We will slowly move into image processing concepts related to image transformations like image translation, flipping, rotating, and cropping. I will also teach arithmetic operations in OpenCV.

Project (Brightness Control):

5. GUI based Brightness Control in Images

6. Real-Time Brightness Control

Key Highlights in Section 12,13

In these sections, I will introduce new concepts on bitwise operations and masking, where you will learn the truth table and different bitwise operations like “AND”, “OR”, “NOT”, “XOR”.

Key Highlights in Section 14

Then we will extend our discussion on Smoothing Filter which is a very important image processing technique. In this section, I will teach smoothing techniques like Average Blur, Gaussian Blur, Median Blur & Bilateral Filter.

You will have complete access to Images, Data, Jupyter Notebook files that are used in this course. The code used in this course is written in such a way that you can directly plug the function into the real-time scenario and get the output.

Table of Contents

1 Load Display Save Image
2 What is Pixel
3 Converting Color
4 Accessing and Manipulate Pixels

5 Download the Resources
6 Line
7 Rectangle
8 Cricle
9 Abstract Circles

Working on Videos
10 Download the Resources
11 Load and Display Video
12 Frames Per Seconds (FPS) & Controlling FPS
13 Accessing Web Camera
14 Stacking Multiple Web Cameras

Project -1 Face Detection with OpenCV
15 Download the Resources
16 Download Cascade Classifier
17 Load Image and Cascade Classifier using OpenCV
18 Apply Viola-Jone Framework (cascade classifier) to Image
19 Draw Bounding Box
20 Face Detection Function

Project -2 Real Time Face Detection with OpenCV
21 Real Time Face Detection with OpenCV

Project -3 Face Detection with Deep Neural Network (DNN) OpenCV
22 Download the Resources
23 Face Detection with DNN Module
24 Load SSD ResNet 10 Caffe Model with OpenCV
25 Calculate Blob from Image
26 Get Face Detections Bounding Boxes from the DNN Model
27 Bounding Box Set the threshold Confidence Score
28 Bounding Box De-Normalize Bounding Box Co-ordinates
29 Bounding Box Draw Rectangle and Put Text (confidence score)
30 Create Face Detection Function

Project-4 Real Time Face Detection with DNN OpenCV
31 Real Time Face Detection with DNN and OpenCV

Image Transformations
32 Download the Resources
33 Image Translation or Shifting
34 Rotating Image
35 Resizing Image
36 Flipping Image
37 Cropping Image

Arithmetic Operations in Images
38 Download the Resources
39 Addition in Image
40 Subtraction in Image
41 Blending Image Idea
42 Blending Image – OpenCV Python

Project – 5 Controlling Brightness of Image with GUI using OpenCV
43 Download the Resources
44 What we will develop
45 Controlling Brightness in Image

Project – 6 Real Time Brightness Control with GUI using OpenCV
46 Controlling Brightness in Videos

Bitwise Operations
47 Download the Resources
48 Truth Table for AND, OR, NOT, XOR
49 Bitwise AND
50 Bitwise OR
51 Bitwise NOT
52 Bitwise XOR

53 Download the Resources
54 Masking Image
55 Preparing Mask Image
56 Masking Image using mask
57 Example-2 Mask image with different shape
58 Example-3 Masking circle shape

Smoothing Filters
59 Download the Resources
60 Average Blur & Convolution Process
61 OpenCV Average Blur
62 Gaussian Blur
63 OpenCV Gaussian Blur
64 Median Blur
65 OpenCV Median Blur for Salt Pepper Noise

Project-7 Pencil Sketch Image in Real Time
66 What will you Develop
67 Load Image and Flow
68 Convert image into grayscale
69 Apply Gaussian Blur to Gray Scale Image
70 Divide Grayscale image and Gaussian Blur Image
71 Adjust Gamma to Division Image
72 Pencil Sketch Function
73 GUI Control Panel
74 Calibrate k-size to odd numbers
75 Calibrate Gamma to 0 to 1 Scale
76 Pencil Sketch in Real Time

Project – 8 Automatic Facial Blur
77 Project Flow
78 Load Image
79 Step-1, Face Detection Get Detections
80 Step-1, Face Detection Select Faces using Confidence Score
81 Step-1, Face Detection Get the Bounding Box
82 Step-1, Face Detection Draw Rectangle Box
83 Step-2, Create Mask Image
84 Step-3, Calculate Background and Foreground Image using Bitwise AND
85 Step-4, Blur the Faces
86 Step-5, Addition Operation

87 Bonus Lecture