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YOLO26 Bootcamp: Real-Time Detection, Segmentation & Pose

Name: YOLO26 Bootcamp: Real-Time Detection, Segmentation & Pose
Rating: 4.9 (5 reviews)

YOLO26 with Python for real-time detection, segmentation, pose estimation, classification, OBB & model deployment

Created byMuhammad Moin

Last updated 3/2026

English

What you'll learn

Introduction to YOLO26: Architecture, Innovations, and Benchmarks
Using YOLO26 for Detection, Segmentation, Pose Estimation, OBB, and YOLOE-26
Step-by-Step YOLO26 Setup on Windows with Google Antigravity
YOLO26 vs YOLO11: Speed and Accuracy Comparison
YOLO26 Custom Object Detection: Dataset Creation & Model Training
YOLO26 Instance Segmentation: Dataset Annotation & Model Training
Fine-Tuning YOLO26 for Pose Estimation on a Custom Dataset
Training YOLO26 for Image Classification on a Custom Dataset
Exporting Models with Ultralytics YOLO26
Building a Vehicle Intensity Heatmap from YOLO26 Detections
Real-Time Bird’s Eye View (BEV) System using YOLO26 and OpenCV

Course content

13 sections • 15 lectures • 5h 19m total length

Introduction to YOLO26: Architecture, Innovation, and Benchmarks21:54
This lecture introduces YOLO26, the latest release in the Ultralytics YOLO object detection series. YOLO26 delivers faster and more accurate real-time performance across images and videos, powered by architectural improvements and refined training strategies that push practical performance even further.
Key Highlights of YOLO26
Improved detection of small objects.
Up to 43% faster CPU inference compared to previous versions
End-to-End, NMS-free inference for cleaner and faster predictions
Multi-task support, including:
Object Detection
Instance Segmentation
Pose Estimation
Image Classification
Oriented Bounding Boxes (OBB)
Optimized backbone and training pipeline for improved stability and accuracy

How to Annotate/ Label a Custom Dataset Using Roboflow21:30
In this lecture, you will learn how to annotate and label a custom dataset using Roboflow for object detection tasks. We will cover image upload, creating classes, drawing bounding boxes, organizing data, and exporting the dataset in YOLO format. By the end of this lecture, you will have a fully prepared dataset ready for training your YOLO26 object detection model.
Train YOLO26 on a Custom Pothole Dataset for Pothole Detection19:57
In this lecture, you will learn how to train a YOLO26 object detection model on a custom pothole dataset. We will cover dataset configuration, training setup, model parameters, and performance monitoring. You will also learn how to evaluate the trained model and run inference to detect potholes in new images and videos.

How to Annotate & Label a Custom Dataset for Instance Segmentation with Roboflow16:55
In this lecture, you will learn how to annotate and label a custom dataset for instance segmentation using Roboflow. We will cover creating classes, drawing masks, organizing data, and exporting it in YOLO26 format. By the end, your dataset will be fully prepared for training a YOLO26 instance segmentation model.
Train a YOLO26 Instance Segmentation Model on a Custom Pothole Dataset14:50
In this lecture, you will learn how to train a YOLO26 instance segmentation model on a custom pothole dataset. The lecture covers dataset configuration, model setup, training, performance evaluation, and running inference to detect and segment potholes in images and videos. By the end, you will be able to build a custom instance segmentation model using YOLO26.

Requirements

Mac / Windows / Linux - all operating systems work with this course!

Description

YOLO26 is the latest evolution in the Ultralytics YOLO object detection family, designed to deliver faster, more accurate, and more efficient real-time performance across images and videos. With architectural upgrades and improved training strategies, YOLO26 pushes practical computer vision performance to a new level.

Key Highlights of YOLO26

Improved small object detection
Up to 43% faster CPU inference compared to previous YOLO versions
End-to-end, NMS-free inference for cleaner and faster predictions
Optimized backbone and training pipeline for better stability and accuracy
Multi-task support in a single framework:
- Object Detection
- Instance Segmentation
- Pose Estimation
- Image Classification
- Oriented Bounding Boxes (OBB)

YOLO26 is built to handle a wide range of computer vision applications with high speed and precision.

What You Will Learn

YOLO26 Fundamentals

YOLO26 architecture, innovations, and performance benchmarks
Understanding how YOLO26 differs from earlier YOLO versions

Model Usage & Setup

Step-by-step YOLO26 setup on Windows
Running detection, segmentation, pose estimation, OBB, and YOLOE-26

Performance Analysis

YOLO26 vs YOLO11: Speed and accuracy comparison

YOLO26 Custom Object Detection: Dataset Creation & Model Training

How to Annotate / Label a Custom Dataset Using Roboflow
Train YOLO26 on a Custom Pothole Dataset for Pothole Detection

YOLO26 Instance Segmentation: Dataset Annotation & Model Training

How to Annotate & Label a Custom Dataset for Instance Segmentation with Roboflow
Train a YOLO26 Instance Segmentation Model on a Custom Pothole Dataset

Training on Custom Datasets

Training YOLO26 for Object Detection
Training YOLO26 for Instance Segmentation
Fine-tuning YOLO26 for Pose Estimation
Training YOLO26 for Image Classification

Advanced Real-World Projects

Building a Vehicle Intensity Heatmap from YOLO26 Detections
Real-Time Bird’s Eye View (BEV) System using YOLO26 and OpenCV

Deployment

Model Export with Ultralytics YOLO26

This course gives you hands-on experience building, training, and deploying YOLO26 models for real-world computer vision tasks.

Who this course is for:

Anyone who is interested in Computer Vision
Anyone who study Computer Vision and want to know how to use YOLO26 for Object Detection, Instance Segmentation, Pose Estimation, Image Classification & OBB
Anyone who aims to build Deep learning Apps with Computer Vision

YOLO26 Bootcamp: Real-Time Detection, Segmentation & Pose

What you'll learn

Explore related topics

Course content

YOLO26: Setting a New Global Standard for Edge-First Vision AI1 lecture • 22min

YOLO26 Hands-On in Google Colab: Detection, Segmentation, Pose, OBB & YOLOE-261 lecture • 32min

YOLO26 Implementation on Windows (Google Antigravity)1 lecture • 21min

Ultralytics YOLO26 vs YOLO11: Performance Comparison1 lecture • 12min

YOLO26 Custom Object Detection: Dataset Creation & Model Training2 lectures • 41min

YOLO26 Instance Segmentation: Dataset Annotation & Model Training2 lectures • 32min

Training YOLO26 for Object Detection on a Custom Dataset1 lecture • 22min

Training YOLO26 Instance Segmentation on a Custom Dataset1 lecture • 24min

Fine-Tuning YOLO26 Pose Estimation with a Custom Dataset1 lecture • 24min

Training YOLO26 for Image Classification on a Custom Dataset1 lecture • 14min

Requirements

Description

Who this course is for: