Master Computer Vision with Deep learning, OpenCV4 & Python

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). Master Computer Vision with Deep learning, OpenCV4 & Python Udemy

The course is structured with below main headings.

1. Computer Vision Fundamentals

2. Image Processing Basics (Coding)

3. CV-101 (Theory + Coding)

4. Advanced CV (Theory + Coding)

5. Project: Secure Access (End-to-end project development & deployment) - Due on 30th Dec 22-

From Basics to Advanced, each topic will accompany a coding session along with theory. Programming assignments are also available for testing your knowledge. Python Object Oriented programming practices will be utilized for better development.

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)

• Test your knowledge by completing assignments with each topic.

• [Project] Develop an end-to-end Visual Authorization System for your Computer. - Coming 30th 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  :)