Image Segmentation, Semantic Segmentation, Instance Segmentation, and Panoptic Segmentation

let's learn four concepts today image segmentation semantic segmentation instant segmentation and panoptic segmentation image segmentation refers to dividing the image into groups of pixels based on some criteria a segmentation algorithm takes an image as input and outputs a collection of regions or segments you can represent these regions as contours or as masks the mask representation is much more common these days we assign a different grayscale value to differentiate between different segments in this representation often we use pseudo coloring to color these segments for better visualization now let's see what is semantic segmentation in semantic segmentation the goal is to assign a label like car building person road etc to every pixel in the image here is an example of semantic segmentation the red color represents the person light green is the grass class dark green represents the tree class and blue shows the sky class you can see which pixels belong to the person class by simply checking if the mask color is red at that pixel but we cannot say if two red colored pixels belong to the same person or different ones we just know that red means it belongs to the person class but what if we want to differentiate between instances of the same class we want to say these group of pixels belong to person one and these other group of pixels belong to person two they both belong to the person class but we want to differentiate between instances of the same class person one and person two well in such cases we use instant segmentation which is closely related to object detection however unlike object detection the output is a mask or contour containing the object instead of a bounding box unlike semantic segmentation usually we do not label every pixel in the image we are only interested in finding the boundaries of specific objects we see the mask for every person has a different color so we can tell them apart however not every pixel has a class label associated with it i know what you're thinking now can we combine semantic segmentation with instance segmentation and get the best of both the worlds fortunately there is a class of techniques which does exactly this and that's called panoptic segmentation every pixel is assigned a class but if there are multiple instances of a class we know which pixel belong to which instance of the class it combines the goodies from both semantic segmentation as well as instant segmentation every pixel has a different color-coded label for example the sky in this example is blue the trees are dark green the grass is light green and people are colored in different yellow red and purple shades so whenever we see something yellow red or purple we can say that it is a person but at the same time we can also say that it is person one versus person two versus person three etc the colors yellow and red both point to the same class person but to different instances of this class we can tell different people apart by just looking at the mask color so to summarize in image segmentation our goal is to divide the image into different regions semantic segmentation is a kind of image segmentation where every pixel is assigned a class label instant segmentation is like object detection but instead of finding bounding box around the object we find the precise mask for the objects in the image panoptix segmentation combines semantic segmentation with instant segmentation you can find the links to the state-of-the-art algorithms for each type of segmentation in the description below that's all we wanted to cover in today's video if you like it please share it with your friends and colleagues see you in the next video this is satyam alex signing off your guide to the fascinating world of computer vision and ai thank you

Channel: LearnOpenCV

Views: 34,886

Keywords: semantic segmentation, image segmentation, instance segmentation, deep learning, artificial intelligence, instance segmentation opencv, panoptic segmantation, image processing, image segmentation python, instance segmentation vs semantic segmentation vs object detection, image segmentation example, image segmentation algorithms, image segmentation deep learning, panoptic segmentation vs semantic segmentation, image segmentation keras, best image segmentation models, learnopencv

Id: 5QUmlXBb0MY

Length: 5min 3sec (303 seconds)

Published: Mon Apr 11 2022