Course Overview

As you know Object Detection is the most used application of Computer Vision, in which the computer will be able to recognize and classify objects inside an image. 

In this course, we will be specifically focusing on YOLO (You Only Look Once) which is an effective real-time object recognition algorithm that is featured in Darknet, an open-source neural network framework. This course is equally divided into two halves. The first half will deal with object recognition using a predefined dataset called the coco dataset which can classify 80 classes of objects. And the second half we will try to create our own custom dataset and train the YOLO model. We will also try to create our own coronavirus detection model. 

By the end of the course, you will have mastered YOLO and object detection. 

What You Will Learn

  • Python based YOLO Object Detection using Pre-trained Dataset Models as well as Custom Trained Dataset Models
  • Case study of coronavirus detector using YOLO
  • Explore YOLO custom training
  • Learn about YOLO V4 Object Detection
  • Learn about YOLO V4 Object Recognition

Program Curriculum

  • Introduction to YOLO Object Detection
  • $7 Million Cybersecurity Scholarship by EC-Council
  • Chapter 1 Quiz

  • Environment Setup - Installing Anaconda
  • Chapter 2 Quiz

  • Python Basics - Assignment
  • Python Basics - Flow Control
  • Python Basics - Data Structures
  • Python Basics - Functions
  • Chapter 3 Quiz

  • Installing OpenCV Library
  • Chapter 4 Quiz

  • Introduction to CNN
  • Chapter 5 Quiz

  • YOLO Pre-trained Object Detection from Image - Part 1
  • YOLO Pre-trained Object Detection from Image - Part 2
  • YOLO Pre-trained Object Detection from Image - Part 3
  • YOLO Pre-trained Object Detection from Image - Part 4
  • Chapter 6 Quiz

  • YOLO Pre-trained Object Detection from Image - NMS - Part 1
  • YOLO Pre-trained Object Detection from Image - NMS - Part 2
  • Chapter 7 Quiz

  • YOLO Pre-trained Object Detection from Real-time Webcam Video
  • Chapter 8 Quiz

  • YOLO Pre-trained Object Detection from Pre-saved Video
  • Chapter 9 Quiz

  • Introduction to Custom Trained YOLO Model
  • Chapter 10 Quiz

  • YOLOv4 Custom Training Phase 1 - YOLOv4 Introduction and Downloading Weights
  • YOLOv4 Custom Training Phase 1 - YOLOv4 Preparing Darknet
  • Chapter 11 Quiz

  • YOLOv4 Custom Training Phase 2 - Data Collection - Part 1
  • YOLOv4 Custom Training Phase 2 - Data Collection - Part 2
  • Chapter 12 Quiz

  • YOLOv4 Custom Training Phase 2 - Image Labelling - Part 1
  • Chapter 13 Quiz

  • YOLOv4 Custom Training Phase 2 - Train Test Split
  • Chapter 14 Quiz

  • YOLOv4 Custom Training Phase 2 - Data Preparation - Part 1
  • YOLOv4 Custom Training Phase 2 - Data Preparation - Part 2
  • Chapter 15 Quiz

  • YOLOv4 Custom Training Phase 3 - Preparing Files Sync to Drive
  • YOLOv4 Custom Training Phase 3 - Connecting Colab and Drive
  • Chapter 16 Quiz

  • YOLOv4 Custom Training Phase 4 - Compile and Test Darknet - Part 1
  • Chapter 17 Quiz

  • YOLOv4 Custom Training Phase 5 - Chart and Training Progress Analysis
  • Chapter 18 Quiz

  • YOLOv4 Custom Training Phase 5 - Finalizing Training Download Weights
  • Chapter 19 Quiz

Chapter 2 Quiz

  • OpenCV Upgrade for YOLOv4
  • Chapter 21 Quiz

  • YOLOv4 Pretrained Object Recognition from Image and Video
  • Chapter 22 Quiz

  • YOLOv4 Custom Coronavirus Detection from Image
  • Chapter 23 Quiz

  • YOLOv4 Custom Coronavirus Detection from Video
  • Chapter 24 Quiz

  • Other Sample Real-world Case Studies
  • Chapter 25 Quiz
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Instructor

Abhilash Nelson

Abhilash Nelson is a pioneering, talented and security-oriented Android/iOS Mobile and PHP/Python Web Developer Application Developer offering more than eight years’ overall IT experience which involves designing, implementing, integrating, testing and supporting impact-full web and mobile applications. He is a Postgraduate Master's Degree holder in Computer Science and Engineering and is currently serving full time as a Senior Solution Architect managing my client's projects from start to finish to ensure high quality, innovative and functional design.

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