Udemy – YOLOv12 Custom Object Detection, Tracking & WebApps
English | Tutorial | Size: 7.42 GB
YOLOv12, Learn Custom Object Detection and Tracking with YOLOv12, and Build Web Apps with Flask
YOLOv12 is the latest state-of-the-art computer vision model architecture, surpassing previous versions in both speed and accuracy. Built upon the advancements of earlier YOLO models, YOLOv12 introduces significant architectural and training enhancements, making it a versatile tool for various computer vision tasks.
The YOLOv12 model supports a wide range of tasks, including object detection, instance segmentation, image classification, pose estimation, and oriented object detection (OBB).
Course Structure
This course is divided into multiple sections, covering everything from the fundamentals of YOLOv12 to advanced applications.
Introduction to YOLOv12
What’s New in YOLOv12
Key updates and features in YOLOv12
Non-Maximum Suppression & Mean Average Precision in Computer Vision
Running YOLOv12
Setting up YOLOv12
Using YOLOv12 for Object Detection
Evaluating YOLOv12 Model Performance: Testing and Analysis
Dataset Preparation
How to find and prepare datasets
Data annotation, labeling, and automatic dataset splitting
Training YOLOv12
Fine-Tuning YOLOv12 for Object Detection on Custom Datasets
Custom Projects:
Train YOLOv12 for Personal Protective Equipment (PPE) Detection
Train YOLOv12 for Potholes Detection
Advanced Multi-Object Tracking
Implementing Multi-Object tracking with Bot-SORT and ByteTrack algorithms
Advanced Applications
Blurring Objects with YOLOv12 and OpenCV-Python
Generating Intensity Heatmaps to Identify Congestion Zones
Building a Tennis Analysis System with YOLO, OpenCV, and PyTorch
Web Integration
Developing Web Apps with YOLOv12 and Flask
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