Practical Image Processing with OpenCV & Python with Project
Last updated 10/2023
Duration: 6h23m | .MP4 1280x720, 30 fps(r) | AAC, 44100 Hz, 2ch | 2.4 GB
Genre: eLearning | Language: English
Last updated 10/2023
Duration: 6h23m | .MP4 1280x720, 30 fps(r) | AAC, 44100 Hz, 2ch | 2.4 GB
Genre: eLearning | Language: English
Learn Practical Python OpenCV concepts and develop projects on completion of every module.
What you'll learn
Learn OpenCV with Python
9 OpenCV Project
Image Processing with OpenCV
Image Translation
Smoothing Filters
Bitwise Operations and Masking
Convolution Process
Thresholding Concepts
Requirements
Python Basics
Description
Welcome to
"
Image Processing using OpenCV from Zero to Hero
" !!!
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.
WHAT YOU WILL LEARN?
Image Basics
Drawings
Image Translation
Image Processing Techniques
Smoothing Filters
Filters
Graphical Use Interphase (GUI) in OpenCV
Thresholding
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.
Key Highlights in Section 15
Project on automatics facial blur
Key Highlights in Section 16
Thresholding filter: Here we will deep dive into thresholding concepts (BINARY, TOZERO, TRUNC, ADAPTIVE MEAN, ADAPTIVE GAUSSIAN) and implement with OpenCV and Python
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.
–––––––––––-
Data Science Anywhere
Who this course is for:
Anyone who are passionate to learn image Processing with OpenCV
More Info