YOLOv8 The Ultimate Course for Object Detection Tracking

YOLO, Introduction to YOLOv8, Train Custom Dataset, Object Detection, Segmentation, Tracking, Real World 17 + Projects
YOLOv8 The Ultimate Course for Object Detection Tracking
File Size :
10.79 GB
Total length :
10h 6m

Category

Instructor

Muhammad Moin

Language

Last update

3/2023

Ratings

0/5

YOLOv8 The Ultimate Course for Object Detection Tracking

What you’ll learn

Introduction to YOLO
Fundamentals of YOLOv8
How to run a YOLOv8 program for Object Detection, Segmentation, Classification
How to find the dataset
Data annotation/labeling/ Automatic Dataset Splitting
How to train YOLOv8 using custom dataset, transfer learning and resume training
Visualize the Training Perfromances
Multiple Object Tracking using YOLOv8
Object Segmentation using YOLOv8
How to train YOLOv8 Segmentation using custom dataset, transfer learning and resume training
YOLOv8 Segmentation with Multiple Object Tracking
Real World 17 + Projects with YOLOv8: Unleashing the Power of YOLOv8

YOLOv8 The Ultimate Course for Object Detection Tracking

Requirements

Python Programming experience is an advantage but not required
Laptop/PC

Description

Welcome to the YOLOv8: The Ultimate Course for Object Detection & Tracking with Hands-on Projects and Applications. YOLOv8 is the state-of-the-art object detection model. It is the 8th version of YOLO and is an improvement over the previous versions in terms of speed, accuracy and efficiency. What will you learn in this course:Introduction to YOLOOverview of CNN, RCNN, Fast RCNN, Faster RCNN, Mask R-CNNIntroduction to YOLOv8Comparison of YOLOv8 and YOLOv7 considering the License Plate Detection ProblemRunning YOLOv8 on WindowsRunning YOLOv8 in Google ColabHow to find the datasetData annotation/labeling/ Automatic Dataset SplittingHow to train YOLOv8 using custom dataset, transfer learning and resume trainingTraining Custom YOLOv8: Potholes DetectionTraining Custom YOLOv8: Personal Protective Equipment Detection Training Custom YOLOv8: Pen and Book DetectionIntroduction to Multi-Object TrackingImplementing YOLOv8 with Multi-Object Tracker DeepSORT AlgorithmImplementing YOLOv8 with Multi-Object Tracker DeepSORT Algorithm | Google ColabTraffic Counting using YOLOv8 and DeepSORT Object TrackingCar Velocity Calculation + Traffic CountingVehicles Counting (Entering and Leaving) using YOLOv8 & DeepSORT Object TrackingCar Velocity Calculation + Vehicles Counting (Entering and Leaving)Run YOLOv8 Segmentation on Google ColabYOLOv8 Segmentation with TrackingHow to train YOLOv8 Segmentation using custom dataset, transfer learning and resume trainingPotholes Segmentation using YOLOv8Traffic Lights Detection and Color Recognition using YOLOv8 | Custom DatasetCracks Segmentation using YOLOv8.Helmet Detection and Segmentation using YOLOv8Traffic Watch: Automated Vehicle Direction Detection and Counting using YOLOv8.Face Detection, Gender Classification, Crowd Counting, Tracking with Alert and Analytics using YOLOv8.Licence Plate Detection and Recognition using YOLOv8 and EasyOCR.Object Blurring using YOLOv8 with Object TrackingVehicles Segmentation and Tracking with Vehicles Counting and Speed Estimation

Overview

Section 1: YOLOv8 Introduction

Lecture 1 Introduction to YOLO

Lecture 2 Overview of CNN, RCNN, Fast RCNN, Faster RCNN, Mask R-CNN

Lecture 3 Introduction to YOLOv8

Lecture 4 Comparison of YOLOv8 and YOLOv7 considering the License Plate Detection Problem

Section 2: YOLOv8 Implementation

Lecture 5 Running YOLOv8 on Windows

Lecture 6 Running YOLOv8 in Google Colab

Section 3: Training Custom YOLOv8

Lecture 7 Potholes Detection Part1

Lecture 8 Potholes Detection Part2

Lecture 9 Personal Protective Equipment Detection| Google Colab| Part 1

Lecture 10 PPE Detection Part 2| Live Webcam Testing

Lecture 11 Pen and Book Detection Part 1

Lecture 12 Pen and Book Detection Part2

Lecture 13 Pen and Book Detection Part3

Section 4: YOLOv8 Object Tracking

Lecture 14 Introduction to Multi-Object Tracking

Lecture 15 Implementing YOLOv8 with Multi-Object Tracker DeepSORT Algorithm

Lecture 16 Implementing YOLOv8 with Multi-Object Tracker DeepSORT Algorithm | Google Colab

Lecture 17 Traffic Counting using YOLOv8 and DeepSORT Object Tracking

Lecture 18 Car Velocity Calculation + Traffic Counting

Lecture 19 Vehicles Counting (Entering and Leaving) using YOLOv8 & DeepSORT Object Tracking

Lecture 20 Vehicles Counting Entering and Leaving Part1

Lecture 21 Vehicles Counting Entering and Leaving Part2

Lecture 22 Car Velocity Calculation + Vehicles Counting (Entering and Leaving)

Section 5: YOLOv8 Object Segmentation and Tracking

Lecture 23 YOLOv8 Segmentation

Lecture 24 Run YOLOv8 Segmentation on Google Colab

Lecture 25 YOLOv8 Segmentation with Tracking

Section 6: Training YOLOv8 Segmentation Model on Custom Dataset

Lecture 26 YOLOv8 Segmentation on Custom Dataset | Potholes Segmentation | Part 1

Lecture 27 YOLOv8 Segmentation on Custom Dataset | Potholes Segmentation | Part 2

Lecture 28 YOLOv8 Segmentation on Custom Dataset | Potholes Segmentation | Part 3

Section 7: YOLOv8 Apps

Lecture 29 Traffic Lights Detection and Color Recognition using YOLOv8 | Custom Dataset

Lecture 30 Cracks Segmentation using YOLOv8.

Lecture 31 Helmet Detection and Segmentation using YOLOv8

Lecture 32 TrafficWatch: Automated Vehicle Direction Detection and Counting using YOLOv8

Lecture 33 License Plate Detection and Recognition using YOLOv8

Lecture 34 Face Detection, Gender Classification, Counting, Tracking, Alert and Analytics

Lecture 35 Face Detection, Gender Classification, Counting, Tracking, Alert and Analytics

Lecture 36 Object Blurring using YOLOv8 with Object Tracking

Lecture 37 Vehicles Segmentation and Tracking with Vehicles Counting and Speed Estimation

For Everyone who is interested in Computer Vision,For Everyone who study Computer Vision and want to know how to use YOLO for Object Detection,For Everyone who wants to learn the latest YOLOv8 version,Building Deep learning Apps with Computer Vision

Course Information:

Udemy | English | 10h 6m | 10.79 GB
Created by: Muhammad Moin

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