Master Computer Vision with Deep learning, OpenCV4 & Python
Become a Computer Vision Guru, Implement object detection, tracking and recognition using OpenCV4, Dlib & Deep Learning
Ratings 5.00 / 5.00
What You Will 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.
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 [Detecion] (Theory + Coding)
Advanced [Tracking] (Theory + Coding)
Project: PeopleTrackr ( Crowd Monitoring System )
Advanced [Recognition] (Theory + Coding)
Project: EasyAttend ( Live Attendance System )
Project: Secure Access (End-to-end project development & deployment)
Goodbye
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-1] PeopleTrackr: Crowd Monitoring System
[Project-2] EasyAttend: Live attendance System for Classrooms and offices.
[Final-Project] Secure Access: End-to-end Visual Authorization System for your Computer.
- 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 Should Attend!
- 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
