Description
This course is your ultimate guide for entering into the realm of Computer Vision. We will start from the very basics i.e Image Formation and Characteristics, Perform basic image processing (Read/Write Image & Video + Image Manipulation), make CV applications interactive using Trackbars and Mouse events, build your skillset with Computer Vision techniques (Segmentation, Filtering & Features) before finally Mastering Advanced Computer Vision Topics i.e Object Detection, Tracking, and recognition.
Right at the end, we will develop a complete end-to-end Visual Authorization System (Secure Access).
The course is structured with below main headings.
- Computer Vision Fundamentals
- Image Processing Basics (Coding)
- CV-101 (Theory + Coding)
- Advanced CV (Theory + Coding) – Due on 1st Dec 22-
- Project: Secure Access (End-to-end project development & deployment) – Due on 5th Dec 22-
From Basics to Advanced, each topic will accompany a coding session along with theory. Programming assignments will also be added* for testing your knowledge. Python Object Oriented programming practices will be utilized for better development.
* Assignments and their solution will be added completely by 10th Dec 22
Learning Outcomes
– Computer Vision
- Read/Write Image & Video + Image Manipulation
- Interactive CV applications with Trackbars & MouseEvents
- Learn CV Techniques i.e (Transformation, Filtering, Segmentation, and Features)
- Understand, train, and deploy advanced topics i.e (Object Detection, Tracking, and Recognition) – Coming 1st Dec 22 –
- [Project] Develop an end-to-end Visual Authorization System for your Computer. – Coming 5th Dec 22 –
– Algorithms
- Facial recognition algorithms like LBP and Dlib-Implementation
- LBP (Fast-Less accurate)
- Dlib-Implementation (Slow-Accurate)
- Single Object Trackers
- CSRT, KCF
- Multiple Object Trackers
- DeepSort (Slow-Accurate)
- Object Detection
- Haar Cascades (Fast-Less accurate)
- YoloV3 (Slow-Accurate)
- Computer Vision Techniques
- Sift | Orb Feature Matching
- Canny Edge detection
- Binary, Otsu, and Adaptive Thresholding
- Kmeans Segmentation
- Convex hull Approximation
Pre-Course Requirments
Software Based
- OpenCV4
- Python
Skill Based
- Basic Python Programming
- Motivated mind 🙂
All the codes for reference are available on the GitHub repository of this course.
Get a good idea by going through all of our free previews available and feel free to contact us in case of any confusion 🙂
Who this course is for:
- Beginner Python developers curious about Computer Vision
- Undergrads wanting to investigate/opt-in to Computer Vision
- University Graduates looking to add Computer Vision in their skillset
- Computer Vision Programmers wanting to brush up on some basics
Requirements
- Python basic Programming
Last Updated 11/2022
Download Links
Direct Download
Computer Vision 2022 Masterclass with OpenCV4 and Python.zip (5.3 GB) | Mirror
