Master Computer Vision with Deep learning, OpenCV4 & Python

Become a Computer Vision Guru, Implement object detection, tracking and recognition using OpenCV4, Dlib & Deep Learning


What you'll learn
Become a Master Computer Vision Programmer by learning from the field experts.
Start from the ground up by Coding Image Processing basics i.e. (Image access and manipulations)
Make your CV Projects interactive by learning to utilize Trackbars and Mouse Events
Deep-dive into CV_101 topics i.e. (Transformations, Filtering, Segmentation, Contours and Features )
Conquer advanced techniques like Object detection, Object Tracking, Object Recognition
Understand, Train and deploy Haar Cascade and YOLOv3 for Object detection
Perform Single Object Tracking using CSRT, KCF etc. and Multi-Object Tracking using DeepSort.
Implement and compare Simple Face-Recognizers like LBP, FisherFaces with highly accurate dlib Implementation.
Secure Access: Create a python executable that only allows access on your pc to authorized personnel's through a complete end-to-end development.

Requirements
Python basic Programming
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)

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 :)

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