Image Processing using OpenCV from Zero to Hero

5VzhzhcQSjMA5zkEhsu5u1tgasX4Wf3b图像处理是数据科学的领域之一,在当今世界的行业中有着广泛的应用。许多行业都在寻找具有这些技能的数据科学家。本课程完全是基于项目的学习。完成每个模块后您将在哪里进行项目。在这里,我将介绍从基础到高级技术的图像处理,包括将机器学习算法和模型应用于图像。

Genre: eLearning | MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.31 GB | Duration: 3h 58m

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


What you’ll learn
Learn OpenCV with Python
6 OpenCV Project
Image Processing with OpenCV
Image Translation
Smoothing Filters
Bitwise Operations and Masking
Convolution Process

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

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.

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