YOLOv8 & YOLO11: Custom Object Detection & Web Apps 2024

• Introduction to YOLO
• Fundamentals of YOLOv8
• How to run a YOLOv8 program for Object Detection, Segmentation, Classification
• How to find the appropriate dataset
• Data annotation/labeling/ Automatic Dataset Splitting
• Train / Fine-Tune YOLOv8 Object Detection Model on Custom Dataset
• Visualize the Training Performances
• Multi-Object Tracking using YOLOv8
• Instance Segmentation using YOLOv8
• Train/ Fine-Tune YOLOv8 Instance Segmentation Model on a Custom Dataset
• YOLOv8 Instance Segmentation with Multiple Object Tracking
• Object Detection in the Browser using YOLOv8 and Flask
• Potholes Detection using YOLOv8
• Personal Protective Equipment Detection using YOLOv8
• Pen and Book Detection using YOLOv8
• Traffic Counting using YOLOv8 and DeepSORT Object Tracking
• Car Velocity Calculation + Traffic Counting
• Vehicles Counting (Entering and Leaving) using YOLOv8 & DeepSORT Object Tracking
• Car Velocity Calculation + Vehicles Counting (Entering and Leaving)
• Potholes Detection and Segmentation using YOLOv8
• Traffic Lights Detection and Color Recognition using YOLOv8
• Cracks Segmentation using YOLOv8.
• Helmet Detection and Segmentation using YOLOv8
• Traffic Watch: Automated Vehicle Direction Detection and Counting using YOLOv8
• License Plate Detection and Recognition using YOLOv8
• Face Detection, Gender Classification, Counting, Tracking, Alert and Analytics
• Object Blurring using YOLOv8 with Object Tracking
• Vehicles Segmentation and Tracking with Vehicles Counting and Speed Estimation
• Personal Protective Equipment (PPE) Detection Web App
• 17 + Projects with YOLOv8: Unleashing the Power of YOLOv8
• Object Detection, Instance Segmentation, Pose Estimation and Image Classification using YOLO11
• Training / Fine-Tuning YOLO11 Models on Custom Dataset
• Multi-Object Tracking with Ultralytics YOLO
• Develop Streamlit Application for Object Detection with YOLO11.

YOLOv8 and YOLO11: Cutting-Edge Object Detection Models

YOLOv8 and YOLO11 are the latest state-of-the-art object detection models from Ultralytics, surpassing previous versions in both speed and accuracy. These models build upon the advancements of earlier YOLO versions, introducing significant architectural and training improvements, making them versatile tools for a variety of computer vision tasks.

The YOLOv8 and YOLO11 models support a wide range of applications, including object detection, instance segmentation, image classification, pose estimation, and oriented object detection (OBB).

Course Structure

This course is divided into two parts:

Part 1: YOLOv8

1. Introduction to YOLO

   • Overview of CNN, RCNN, Fast RCNN, Faster RCNN, Mask R-CNN

   • Introduction to YOLOv8

   • Comparison of YOLOv8 and YOLOv7 with a focus on License Plate Detection

2. Running YOLOv8

   • Setting up YOLOv8 on Windows

   • Using YOLOv8 in Google Colab

3. Dataset Preparation

   • How to find datasets

   • Data annotation, labeling, and automatic dataset splitting

4. Training YOLOv8

   • Train/ Fine-Tune YOLOv8 Model on a Custom Dataset

   • Custom Projects:

     • Potholes Detection

     • Personal Protective Equipment (PPE) Detection

     • Pen and Book Detection

5. Multi-Object Tracking

   • Introduction to Multi-Object Tracking

   • Implementing YOLOv8 with the DeepSORT algorithm

     • Running on Google Colab

   • Traffic Analysis:

     • Vehicle counting and car velocity calculation

     • Vehicle entry and exit counting

   • YOLOv8 Segmentation with Tracking

6. Advanced Applications

   • Potholes Segmentation

   • Traffic Lights Detection and Color Recognition

   • Cracks Segmentation

   • Helmet Detection and Segmentation

   • Automated Vehicle Direction Detection and Counting

   • Face Detection, Gender Classification, Crowd Counting, and Tracking

   • License Plate Detection and Recognition with EasyOCR

   • Object Blurring with Object Tracking

   • Vehicle Segmentation, Counting, and Speed Estimation

7. Web Integration

   • Integrating YOLOv8 with Flask

   • Creating a Complete Web App for PPE Detection

Part 2: YOLO11

1. What's New in YOLO11

   • Key updates and features in Ultralytics YOLO11

2. Using YOLO11 for Various Tasks

   • Object Detection, Instance Segmentation, Pose Estimation, and Image Classification on Windows/Linux.

3. Model Performance Evaluation

   • Testing and analyzing YOLO11 performance

4. Training YOLO11

   • Train/ Fine-Tune YOLO11 Object Detection Model on a CustomDataset for Personal Protective Equipment Detection.

   • Train/ Fine-Tune YOLO11 Instance Segmentation Model on a Custom Dataset for Potholes Detection.

   • Fine-Tune YOLO11 Pose Estimation Model on a CustomDataset for Human Activity Recognition.

   • Train/ Fine-Tune YOLO11 Image Classification Model on a CustomDataset for Plant Classification.

5. Advanced Multi-Object Tracking

   • Implementing Multi-Object tracking with Bot-SORT and ByteTrack algorithms

6. Specialized Projects

   • License Plate Detection & Recognition with YOLO11 and EasyOCR

7. Web Integration with YOLO11

   • Integrating YOLO11 with Flask to build a web app

   • Creating a Streamlit Web App for object detection