YOLO11: Custom Object Detection & Web Apps in Python 2024

[BaDshaH]

Published 10/2024
Created by Muhammad Moin
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 10 Lectures ( 5h 28m ) | Size: 5.55 GB

Learn Custom Object Detection, Tracking and Pose Estimation with YOLO11, and Build Web Apps with Flask and Streamlit

What you'll learn
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.
Object Detection in the Browser using YOLO11 and Flask

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

Description
YOLO11 is the latest state-of-the-art object detection model from Ultralytics, surpassing previous versions in both speed and accuracy. Built upon the advancements of earlier YOLO models, YOLO11 introduces significant improvements in architecture and training, making it a versatile tool for various computer vision tasks.YOLO11 models support a wide range of tasks, including object detection, instance segmentation, image classification, pose estimation, and oriented object detection (OBB).In this course, you will learn:What's New in Ultralytics YOLO11.How to use Ultralytics YOLO11 for Object Detection, Instance Segmentation, Pose Estimation, and Image Classification.Running Object Detection, Instance Segmentation Pose Estimation and Image Classification with YOLO11 on Windows/Linux.Evaluating YOLO11 Model Performance: Testing and AnalysisTraining a YOLO11 Object Detection Model on a Custom Dataset in Google Colab for Personal Protective Equipment (PPE) Detection. Step-by-Step Guide: YOLO11 Object Detection on Custom Datasets on Windows/Linux.Training YOLO11 Instance Segmentation on Custom Datasets for Pothole Detection.Fine-Tuning YOLO11 Pose Estimation for Human Activity Recognition.Fine-Tuning YOLO11 Image Classification for Plant Classification.Multi-Object Tracking with Bot-SORT and ByteTrack Algorithms.License Plate Detection & Recognition using YOLO11 and EasyOCR.Integrating YOLO11 with Flask to Build a Web App.Creating a Streamlit Web App for Object Detection with YOLO11.

Who this course is for
Anyone who is interested in Computer Vision
Anyone who study Computer Vision and want to know how to use YOLO11 for Object Detection, Instance Segmentation, Pose Estimation and Image Classification
Anyone who aims to build Deep learning Apps with Computer Vision

Homepage

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