Instance Segmentation in 12 minutes with YOLOv8 and Python
YOLOv8 is the latest installment of the highly influential YOLO (You Only Look Once) architecture. YOLOv8 was developed by Ultralytics, a team known for its work on YOLOv3 and YOLOv5.
Following the trend set by YOLOv6 and YOLOv7, we have at our disposal object detection, but also instance segmentation, and image classification. The model itself is created in PyTorch and runs on both the CPU and GPU. As with YOLOv5, we also have a number of various exports such as TF.js or CoreML.
In this video, I'll take you through a step-by-step tutorial on Google Colab, and show you how to train your own YOLOv8 instance segmentation model.
Chapters:
0:00 Introduction
1:03 Setting up the Python environment
3:08 Inference with YOLOv8 model pre-trained on COCO dataset
5:42 Download custom dataset from Roboflow Universe
7:26 Train YOLOv8 model on custom dataset
9:16 YOLOv8 model evaluation
11:05 Custom YOLOv8 model inference
11:43 Conclusion
Resources:
🌏 Roboflow: https://roboflow.com
🌌 Roboflow Universe: https://universe.roboflow.com
📝 How to Train YOLOv8 Instance Segmentation on a Custom Dataset Blogpost: https://blog.roboflow.com/how-to-trai...
📓How to Train YOLOv8 Instance Segmentation on a Custom Dataset Notebook: https://colab.research.google.com/git...
⭐ YOLOv8 repository: https://github.com/ultralytics/ultral...
📄 YOLOv8 docs: https://v8docs.ultralytics.com
📓 Learn more about YOLOv8 and other Computer Vision models with Roboflow Notebooks: https://github.com/roboflow/notebooks
🆕 What's New in YOLOv8 Architecture: https://blog.roboflow.com/whats-new-i...
💯 RF100 Dataset https://blog.roboflow.com/roboflow-100
Stay up to date with the projects I'm working on at https://github.com/roboflow and https://github.com/SkalskiP! ⭐
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