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 FundamentalsImage 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)GoodbyeFrom 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 VisionRead/Write Image & Video + Image ManipulationInteractive CV applications with Trackbars & MouseEventsLearn 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.- AlgorithmsFacial recognition algorithms like LBP and Dlib-ImplementationLBP (Fast-Less accurate)Dlib-Implementation (Slow-Accurate)Single Object TrackersCSRT, KCFMultiple Object TrackersDeepSort (Slow-Accurate)Object DetectionHaar Cascades (Fast-Less accurate)YoloV3 (Slow-Accurate)Computer Vision TechniquesSift Orb Feature MatchingCanny Edge detectionBinary, Otsu, and Adaptive ThresholdingKmeans SegmentationConvex hull ApproximationPre-Course RequirmentsSoftware BasedOpenCV4PythonSkill BasedBasic Python ProgrammingMotivated 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 :)
