YOLOv9: Learn Object Detection, Tracking with WebApps

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Muhammad Moin

7:19:32

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1. Introduction to the Course

1. Introduction.mp4

04:07

2. Non Maximum Suppression & Mean Average Precision

1.1 Non Maximum Suppression_final.pptx

1.2 non_max_suppression_final_final.zip

1. Non Maximum Suppression.mp4

29:49

2.1 new_mean average precision in object detection.zip

2. Mean Average Precision.mp4

23:52

3. YOLOv9 Learning What You Want to Learn Using Programmable Gradient Information

1.1 what is yolov9.zip

1. What is YOLOv9.mp4

19:07

4. Object Detection on Images, Videos & Live Webcam Feed using YOLOv9

1.1 output1.mp4

00:43

1.2 output2.mp4

00:13

1.3 run_yolov9_googlecolab.zip

1. Object Detection in Images and Videos with YOLOv9 in Google Colab.mp4

19:00

2. Testing YOLOv9 Model Performance Image, Video, and Webcam Tutorial.mp4

27:43

5. Training fine-tuning the YOLOv9 model on a custom dataset

1.1 best.zip

1.2 train_yolov9_custom_dataset_ppe.zip

1. Personal Protective Equipment (PPE) Detection using YOLOv9.mp4

26:24

6. Object Tracking using YOLOv9 and DeepSORT SORT Algorithm

1.1 YOLOv9_DeepSORT_OT_recording.zip

1. Real-Time Object Tracking using YOLOv9 and DeepSORT Algorithm.mp4

47:01

2.1 YOLOv9_SORT.zip

2. Real-Time Object Tracking using YOLOv9 and SORT Algorithm.mp4

37:43

3.1 Entering_Leaving_Counting_YOLOv9_DeepSORT_Recording.zip

3.2 Instructions.txt

3. Person Vehicles Counting (Entry and Exit) using YOLOv9 and DeepSORT.mp4

54:45

7. YOLO-World Real-Time, Zero-Shot Object Detection

1. YOLO-World Real-Time, Zero-Shot Object Detection.mp4

11:06

2.1 zero_shot_object_detection_yolo_world.zip

2. How to Detect Objects with YOLO-World.mp4

19:15

8. YOLOv9 WebApps Integrate YOLOv9 with Flask

1.1 Code-File-Link.txt

1. Introduction.mp4

02:25

2.1 Code-File-Link.txt

2. Object Detection on Images Videos Live Webcam Feed using YOLOv9.mp4

23:20

3.1 Code-File-Link.txt

3. Integrating YOLOv9 with Flask.mp4

18:06

4.1 Code-File-Link.txt

4. Integrating YOLOv9 with Flask and Creating a WebApp.mp4

24:41

5.1 Code-File-Link.txt

5. WebApp Layout Design.mp4

50:12

Description

Object Detection, Object Tracking, WebApps using Flask, Object Detection on Custom Dataset, YOLO-World Object Detection

What You'll Learn?

Basics of Computer Vision
Objects Detection using YOLOv9
Training YOLOv9 on a Custom Dataset
Object Tracking using YOLOv9 and DeepSORT Algorithm
Object Tracking using YOLOv9 and SORT Algorithm
Objects Detection using YOLO-World
Integrating YOLOv9 with Flask and Creating Web Apps
Personal Protective Equipment (PPE) detection using YOLOv9
Person/Vehicles counting (entry and exit) using YOLOv9 and the DeepSORT algorithm.
Object Detection in the Browser using YOLOv9 and Flask

Who is this for?

For Everyone who is interested in Computer Vision

For Everyone who wants to learn the latest YOLOv9 version

For Everyone who study Computer Vision and want to know how to use YOLO for Object Detection

For Everyone who aims to build Deep learning Apps with Computer Vision

What You Need to Know?

Laptop/PC

More details

Description
YOLOv9 represents the latest advancement in computer vision object detection models. This course begins by covering the fundamentals of computer vision, including Non-Maximum Suppression and Mean Average Precision. Moving forward, we delve deeply into YOLOv9, exploring its architecture and highlighting how it surpasses other object detection models. In Section 04, we demonstrate object detection on images and videos using YOLOv9, evaluating its performance across various parameters.
Subsequently, in Section 05, we train the YOLOv9 model on a custom dataset for Personal Protective Equipment (PPE) detection. Additionally, Section 06 focuses on object tracking, where we integrate YOLOv9 with the DeepSORT & SORT algorithms. Here, we also develop an application for person/vehicle counting (entry and exit) using YOLOv9 and the DeepSORT algorithm.
Section 07 provides a review of YOLO-World and a step by step guide to perform object detection using YOLO-World. Finally, in Section 09, we will create web applications by integrating YOLOv9 with Flask.
This comprehensive course covers a range of topics, including:
Mean Average Precision (mAP).
Non Maximum Suppression (NMS).
What is YOLOv9 | Architecture of YOLOv9.
Object Detection using YOLOv9.
Testing YOLOv9 Model Performance on Images, Videos and on the Live Webcam Feed.
Training YOLOv9 on a Custom Dataset.
Personal Protective Equipment (PPE) DetectionÂ using YOLOv9.
Object Tracking using YOLOv9 and DeepSORT.
Object Tracking using YOLOv9 and SORT.
Person/ Vehicles Counting (Entering and Leaving) using YOLOv9 and DeepSORT algorithm.
Introduction to YOLO-World.
Object Detection on Images and Videos using YOLO-World.
Integrating YOLOv9 with Flask and Creating Web Apps.
Object Detection in the Browser using YOLOv9 and Flask

Who this course is for:
For Everyone who is interested in Computer Vision
For Everyone who wants to learn the latest YOLOv9 version
For Everyone who study Computer Vision and want to know how to use YOLO for Object Detection
For Everyone who aims to build Deep learning Apps with Computer Vision

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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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