Segmentation with pre-trained Ultralytics YOLOv8 models in Python

Let’s take a look at the world of object segmentation with the Ultralytics YOLOv8 model. In this blogpost we’ll guide you through the ins and outs of setting up and running segmentation with ease in Python.

Link to this sectionSetting the stage for segmentation#

Let's kick things off by focusing on YOLOv8. Installing this powerhouse model is a breeze, and within moments, you'll be primed and ready to tap into its segmentation capabilities.

Instance segmentation takes you one step further from object detection by pinpointing individual objects within an image and separating them from the background.

Its output comprises masks or contours outlining each object, accompanied by class labels and confidence scores. This technique proves invaluable when precise object shapes are essential, providing not just object location but also detailed information on their form.

With a few simple commands, you'll be able to execute predictions from the command line, witnessing first-hand the innovation and simplicity that YOLOv8 brings to the table.

Link to this sectionLive segmentation: Bringing images to life#

But why limit ourselves to static images when we can experience segmentation in real time? Our Python script is your gateway to the dynamic world of live segmentation.

By leveraging the YOLO class and integrating it seamlessly with OpenCV, you can breathe life into your projects, uncovering hidden insights and patterns as you go.

From identifying chairs to delineating plants, the possibilities are as endless as your imagination.

Fig 1. Nicolai Nielsen outlining the COCO segmentation pre-trained models.

At Ultralytics, we also provide support for COCO segmentation pre-trained models, which serve as an excellent starting point for any use case. You can then fine-tune these models for your specific needs.

As a whole, we offer support for various datasets, such as carparts instance segmentation, crack segmentation, and industrial package segmentation. Training segmentation models on these datasets is made simple with a single command available in our documentation:

Link to this sectionStay tuned#

Join us in the coming videos as we dive deeper into the realm of YOLOv8, exploring custom training and inference on your very own datasets.

We are committed to simplifying the complexities of AI and machine learning, one segment at a time. Our mission is to empower individuals and organizations alike to harness the full potential of cutting-edge technologies like YOLOv8. With our guidance and your curiosity, there's no telling what incredible breakthroughs await.

Join us as we unlock the full potential of Ultralytics YOLOv8. Watch the full video Watch the full video!