Learn OpenCV using Python with Practice

OpenCV with Python

Created by : Rated :4 623 views

Last Updated: 2023-03-17 08:03:52 English Course Type: Self Learning

You will mastery the OpenCV
Object detection from images
Object detection from videos
Object Detection
Learn OpenCV with Python
Learn Basic Operations with OpenCV
Learn Pixel Data
Learn Data Types, Structures, Image Types, Colour Schemas/Channels
Learn Pixel Manipulation and Filtering
Learn Blur, Dilation and Erosion
Learn Scale and Rotate Images and use input videos
Learn Segmentation and Binary Images
Learn Simple and Adaptive Thresholding
Learn Skin Detection
Learn Contours and Object Detection
Learn Area, Perimeter, Centre and Curvatures
Learn Canny Edge Detection
Learn Face Detection with OpenCV
Learn Template Matching
Learn Haar Cascading

OpenCV is a library of programming functions mainly aimed at real-time computer vision. Originally developed by Intel, it was later supported by Willow Garage then Itseez. The library is cross-platform and free for use under the open-source Apache 2 License.(Wikipedia)

It is one of the most popular tools for facial recognition, used in a wide variety of security, marketing, and photography applications, and it powers a lot of cutting-edge tech, including augmented reality and robotics. This course offers Python developers a detailed introduction to OpenCV 3, starting with installing and configuring your Mac, Windows, or Linux development environment along with Python 3. Learn about the data and image types unique to OpenCV, and find out how to manipulate pixels and images. Then comes the real power of OpenCV: object, facial, and feature detection. Learn how to leverage the image-processing power of OpenCV using methods like template matching and machine learning data to identify and recognise features.

Introduction to OpenCV
Installation & Personalisation
Basic operations
Pixel Data, Data Types, Structures
Pixel manipulation & filtering
Object Detection with OpenCV
Segmentation & Binary Images
Simple & Adaptive Thresholds
Contours , Area perimeters, Center & Curvature
Object, Canny Edges Detection
Assignments
Areas of Application
- 2D & 3D Toolkits
- Egomotion Estimation
- Facial & Gesture recognition
- Human computer interaction
- Mobile robotics
- SFM
- Motion Tracking
- Augmented Reality
- Object Detection
- Segmentation & Recognition

Python
Some programming experience
Passionate to learn the stuff
This course is meant for people with at least some programming experience

Who are working in Computer Vision
Data Scientist
Object Detection
Driverless Cars
Engineers looking forward to work with driver less cars
Have some programming experiences who wants to enter in computer vision and object detection world in data science!

Section 1 : Course Overview 4 Lectures 00:14:57
Lecture 1 :
Course Overivew Preview
Lecture 2 :
What you should know?
Lecture 3 :
Installation and Personalisation
Lecture 4 :
OpenCV Installation
Section 2 : Basic Operations 16 Lectures 00:04:17
Lecture 1 :
Get Started with OpenCV and Python
Lecture 2 :
Understanding and Accessibility of Pixel Data
Lecture 3 :
Data Type and Structures
Lecture 4 :
Data Types & Structures operate & create metrics or Numpy Arrays
Lecture 5 :
Image Types and Color Channels - Part-01
Lecture 6 :
Image Types and Color Channels - Part-02
Lecture 7 :
Image Types and Color Channels - Part-03
Lecture 8 :
Pixel manipulation and filtering
Lecture 9 :
Gaussian Blur, Dilation and Erosion Filter Part-01
Lecture 10 :
Gaussian Blur, Dilation and Erosion Filter Part-02
Lecture 11 :
Gaussian Blur, Dilation and Erosion Filter Part-03
Lecture 12 :
Scale and Rotate Images
Lecture 13 :
Video Capturing Input
Lecture 14 :
Image Types and Color Channels - Part-02
Lecture 15 :
Assignment 01
Lecture 16 :
Assignment 01 - Solution
Section 3 : Object Detection 10 Lectures 00:56:04
Lecture 1 :
Segmentation and Binary Image
Lecture 2 :
Simple Thresholding
Lecture 3 :
Adaptive Thresholding
Lecture 4 :
Skin Detection
Lecture 5 :
Contour Object Detection
Lecture 6 :
Area, Perimeter, Centre and Curvature
Lecture 7 :
Canny Object Detection
Lecture 8 :
Object Detection Overview
Lecture 9 :
Assignment 02 - Object Detection
Lecture 10 :
Assignment 02 - Object Detection Solution
Section 4 : Face and Feature Detection 7 Lectures 00:03:59
Lecture 1 :
Face and Feature Detection Overview
Lecture 2 :
Template Matching Overivew
Lecture 3 :
Application of Template Matching
Lecture 4 :
Haar Cascading
Lecture 5 :
Face Detection
Lecture 6 :
Assignment 03 - Eye Detection
Lecture 7 :
Assignment 03 - Eye Detection Solution

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Yes absolutely & thats one of the advantage of self-paced courses. You can anytime pause or resume the course & come back & forth from one lecture to another lecture, play the videos mulitple times & so on.
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Nasr Ullah,

1246 Course Views

1 Courses

A passionate leader with 10+ years of experience, strong tech fundamentals, with an entrepreneurial mindset. I never stop learning new things and brushing up on my skills. I believe in: 1. Teamwork - keep smooth communication, empowerment, problem solution, rapid feedback, develop soft skills, strategic thinking. 2. Result-oriented, data-driven engineering – optimizing the overall flow, for scalability and velocity increase. 3. Product vision, strategy and roadmaps building effectively 4. Building efficient teams across the globe Skilled in agile methodologies(agile/scrum/kanban), project management, software development(web, mobile, data products), and managing simultaneously multiple teams & projects. Strong Research & Development Skills and a positive learning attitude. Extensively worked on JIRA, Wrike, Basecamp, Asana, Trello, MS Project, Google Docs, MS Office. Worked with MS Visual Studio, MS Visual Studio Code, Microsoft Sharepoint, Xcode, Atom, Sublime, R-Studio, VSS, Github, Bitbucket, CICD, Jenkins, Kubernetes, Dockers, Python Scripting, ActiveMQ, RabbitMQ, OP5 monitor plugins, Kafka, REST API, FastAPI, Servereless, Lambda, NewRelic, Object Detection using Tensorflow, OpenCV and Pre & Post trained models. Performed data analysis using R and built custom dashboards using shiny apps. Worked on Google Cloud, AWS, and MS Azure cloud computing platforms. Worked on marketing & strategy solutions Adjust, CleverTap, Moengage and Mixpanel. Got Microsoft, Oracle, Oracle E-Business Suite R12, IBM Blockchain, and internal coding standards certificates. Managed 120+ resources team and worked with clients like : Rocket Internet, Jeeny, Etisalat, Dubai RTA, Emirates Post, Ajman Free Zone, IACAD, Salesforce, US Census Bureau, PTCL & Microsoft Surface, 401kplans and delivered the projects successfully within the time frame, budget & quality.