YOLO11: Custom Object Detection & Web Apps in Python 2024

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Muhammad Moin

4:41:23

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1 - YOLO11 Implementation Google Colab

1 -Object Detection, Instance Segmentation, Pose Estimation & Image Classification.mp4

20:55

1 -YOLO11 Google Colab.zip

2 - YOLO11 Implementation Windows & Linux

1 -Object Detection, Instance Segmentation, Pose Estimation & Image Classification.mp4

22:28

1 -yolo11 window rec.zip

3 - Evaluating YOLO11 Model Performance Testing and Analysis

1 -Testing and Analyzing YOLO11 Model Performance.mp4

49:31

1 -test yolo11 model perfornance.zip

4 - Training Custom YOLO11

1 -YOLO11CustomObjectDetectionCompleteFile.zip

1 -YOLO11 Object Detection on Custom Dataset for PPE Detection.mp4

37:09

5 - Multi-Object Tracking with Ultralytics YOLO11

1 -Multi-Object and Multithreaded Tracking Using Ultralytics YOLO11.mp4

44:49

1 -Object Tracking YOLO11.zip

6 - Train YOLO11 Instance Segmentation Model on a Custom Dataset

1 -Instance Segmentation using YOLO11 on a Custom Dataset.mp4

28:17

1 -Train YOLO11 Segmentation Custom Dataset Updated.zip

7 - Image Classification with YOLO11 on a Custom Dataset

1 -Image Classification YOLO11 Updated.zip

1 -YOLO11 Image Classification on Custom Dataset.mp4

16:59

8 - Human Activity Recognition with YOLO11 Fine-Tune YOLO11 Pose Estimation Model

1 -Human Activity Recognition YOLO11 Updated.zip

1 -Train YOLO11 Pose Estimation Model on a Custom Dataset.mp4

24:30

9 - License Plate Detection and Recognition using YOLO11 and EasyOCR

1 -Automatic Number Plate Recognition (ANPR) with Yolo11 and EasyOCR.mp4

36:45

1 -Licence Plate Detection.zip

1 -Licence Plate Detection Recognition.zip

Description

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

Who is this 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

What You Need to Know?

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

More details

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 Analysis
Training 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

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Python

Muhammad Moin

Instructor's Courses

Machine Learning | Computer Vision Engineer with over 3 years of experience working in AI product development. I have worked on state of the art Object Detection and Tracking algorithms including YOLOv8, YOLOv7, YOLOR, YOLOv4 in Tracking I have reviewed and implemented, SORT, DeepSORT and ByteTrack in different projects. I also have an hands on experience on Classical and Traditional Machine Learning Algorithms. I have also reviewed and implemented state of the art Deep Learning Algorithms in different project which include VGG16, ResNet50, GoogLeNet, MobileNet. I have expertise in Natural Language and Time Series Forecasting as well and done plenty of project for different clients as well. I have created a real time Stock Price Forecasting Web App using state of the art Time Series Forecasting Model. I have done deployment on AWS servers, Google Cloud and Heroku as well.

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