Instance Segmentation

The YOLOv5 instance segmentation and the Detectron2 Mask RCNN models are commonly used for instance segmentation.

Instance segmentation models are useful when you need to identify the exact pixels that are connected with an object. This is useful in a number of situations, such as:

• Analyzing medical images to detect abnormalities.
• Identifying disease on plants.
• Identifying different objects on a road to guide a self-driving car.

‍

Instance segmentation identifies objects in an image and maps each pixel to the identified objects. With instance segmentation, you can find exactly where an object is in an image. For example, one could use an instance segmentation model to find all the pixels associated with a forklift in an image.