Yolov12: Custom Object Detection, Tracking & Webapps

YOLOv12, Learn Custom Object Detection and Tracking with YOLOv12, and Build Web Apps with Flask

What you'll learn

YOLOv12 architecture and how it really works

What is Non Maximum Suppression & Mean Average Precision

How to use YOLOv12 for Object Detection

Evaluating YOLOv12 Model Performance on Images, Videos & on the Live Webcam Feed

Blurring Objects with YOLOv12 and OpenCV-Python

Data annotation/labeling using Roboflow

Build a Tennis Analysis System with YOLO, OpenCV and PyTorch

Training and Fine-Tuning YOLOv12 Models on Custom Datasets

Object Detection in the Browser using YOLOv12 and Flask

Requirements

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

Description

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 StructureThis course is divided into multiple sections, covering everything from the fundamentals of YOLOv12 to advanced applications.Introduction to YOLOv12What’s New in YOLOv12Key updates and features in YOLOv12Non-Maximum Suppression & Mean Average Precision in Computer VisionRunning YOLOv12Setting up YOLOv12Using YOLOv12 for Object DetectionEvaluating YOLOv12 Model Performance: Testing and AnalysisDataset PreparationHow to find and prepare datasetsData annotation, labeling, and automatic dataset splittingTraining YOLOv12Fine-Tuning YOLOv12 for Object Detection on Custom DatasetsCustom Projects:Train YOLOv12 for Personal Protective Equipment (PPE) DetectionTrain YOLOv12 for Potholes DetectionAdvanced Multi-Object TrackingImplementing Multi-Object tracking with Bot-SORT and ByteTrack algorithmsAdvanced ApplicationsBlurring Objects with YOLOv12 and OpenCV-PythonGenerating Intensity Heatmaps to Identify Congestion ZonesBuilding a Tennis Analysis System with YOLO, OpenCV, and PyTorchWeb IntegrationDeveloping Web Apps with YOLOv12 and Flask

Overview

Section 1: YOLOv12: The Future of Real-Time Object Detection with Attention Mechanisms

Lecture 1 What's New in YOLOv12?

Section 2: Non Maximum Suppression & Mean Average Precision

Lecture 2 Non Maximum Suppression

Lecture 3 Mean Average Precision

Section 3: YOLOv12 Implementation | Google Colab

Lecture 4 How to use YOLOv12 for Object Detection

Section 4: Evaluating YOLOv12 Model Performance: Testing and Analysis

Lecture 5 Testing and Analyzing YOLOv12 Model Performance

Section 5: Blurring Objects with YOLOv12 and OpenCV-Python

Lecture 6 Blurring Objects with YOLOv12 and OpenCV-Python

Section 6: Training Custom YOLOv12

Lecture 7 Dataset Preparation | Potholes Detection

Lecture 8 Fine-Tune YOLOv12 Model on Custom Dataset for Potholes Detection

Lecture 9 Fine-Tune YOLOv12 Object Detection Model on Custom Dataset for PPE Detection

Section 7: Build a Tennis Analysis System with YOLO, OpenCV and PyTorch

Lecture 10 Building a Tennis Analysis System with YOLO, OpenCV, and PyTorch

Section 8: Building Web Apps with YOLOv12 and Flask

Lecture 11 YOLOv12 for Object Detection

Lecture 12 Integrating YOLOv12 with Flask to Build a Web App

Lecture 13 Updating the HTML Page in the Flask App

Lecture 14 Adding a Line Chart in the Flask App to Display People Count

Lecture 15 Generating Intensity Heatmaps to Identify the Congestion Zones

Anyone who is interested in Computer Vision,Anyone who study Computer Vision and want to know how to use YOLOv12 for Object Detection,Anyone who aims to build Deep learning Apps with Computer Vision