Build an AI/ML Tennis Analysis system with YOLO, PyTorch, and Key Point Extraction

In this video, you'll learn how to use machine learning, computer vision and deep learning to create a tennis analysis system. This project utilizes YOlO a state of the art object detector to detect the players and the tennis balls. It also utilizes trackers to track those object across frames. We also write our own conveloutional Nueral network to detect court key points. Github link is provided bellow.

In this video you will learn how to:
1. Use ultralytics and YOLOv8 to detect objects in images and videos.
2. Fine tune and train your own YOLO on your own custom dataset.
3. Train a CNN with pytorch to extract keypoints.
4. Use object trackers to track objects across frames.
5. Use CV2 to read, manipulate and save a video.
6. Analyze detection data and take a data driven approach to develop features.
7. Put all those ML/DL model output into one big project that have a concrete output.

🔑 TIMESTAMPS
================================
0:00 - Introduction
1:00- Object detection with YOLO
11:30 - Train YOLO on tennis balls
22:35- Object Tracking
25:40- Train key point detection with Pytorch
50:55- Tennis Analyzer

[ArrowKy]

As soon as I saw the Activate Windows. I knew this was going to be a banger of a video

[cmpuipf]

very little comments and views, i feel like i'm in such a select company, will definitely try this, you efforts, sir are unimaginably valued

[mbsanga]

im completely new in this field but the first 10 minutes of this video im already feeling like im pro. thank you for the video.

[lazarobeas]

Wow, perfect. Love that it's long and proper. Will be building this along with you!

[sohamjana]

This has been a gem of a project…!! A lot of concepts have been explained and learnt a lot. Thank you.

[varunsuresh]

Love these long tutorials.. comforting.. will be watching it over the weekend! Thanks!

[psykick]

This is amazing! It is very rare and difficult to find help and resources like this anywhere. Really appreciate it. Hope to see more of this kind of content!

[LyuboslavPetrov]

This is some fantastic work and presentation of grand value. Thank you

[Amnskary]

This projects are insane, please continue the series, it has been very helpful.

[boogersincoffee]

I was about to go to bed. Finding this video got me so excited that I'll probably be up another hour. Can't wait to watch this tomorrow.

[senzeit]

Ohhhh ive been searching for some ML projects and today yt funally recommend me your channel, you should def keep doing more oroject videos, ill def try this

[RishabhBohra]

commenting so this gets recommended to everyone in next 5 years

[CHNLTV]

Impressive! love the detail provided. Thank You!

[booky]

Worth watching. Lots of learning. Thank you for sharing!

[varram]

this is gonna be the perfect into to AI and python development for me as a guy coming for a mostly node.js backend background

[huyphanducnhat]

Banger, we are graduating university with this vid 🔥🔥

[atlasguilt]

Thanks, exactly what I was looking for.

[ztech-consulting]

Excellent work man!!! I don't code but I watched the whole video.

[jayeshbaviskar]

awesome content! would love to see similar project with action detections for Football

[oqjuvpj]

Wow! Very cool and not super complex project. Thank you for yolo introduction!!