🎯Learn how to annotate custom data for pose detection using a computer vision annotation tool.
📊Understand the process of training a pose detector using YOLO V8 on local computers or Google Colab.
✨Discover how to conduct a super comprehensive evaluation of the trained model.
🔗Understand the importance of following a specific order when annotating key points in the data.
🚀Learn how to structure your data and file system in the required format for YOLO V8.
What is the YOLO V8 model?
—YOLO V8 (You Only Look Once Version 8) is a popular object detection model that can detect and classify objects in an image or video.
Why is pose detection important?
—Pose detection can be used in various applications, such as sports analytics, fitness tracking, and motion capture.
What is the purpose of data annotation?
—Data annotation involves labeling the key points in an image or video to train a model for pose detection.
Can I train a pose detector on my custom data?
—Yes, this tutorial shows you how to annotate and train a pose detector on your custom data.
What is the significance of following a specific order in key point annotation?
—Following a specific order ensures consistency in labeling the key points, allowing the model to learn the correct associations between the points.
00:00Introduction to the comprehensive tutorial on pose detection using YOLO V8
02:46How to annotate custom data using a computer vision annotation tool
08:27Extracting and formatting annotations from the annotation tool
10:16Structuring the data and file system for YOLO V8 training
19:05Training the pose detection model using YOLO V8
