Image-Segmentation

This article is a continuation of the previous article on Semantic Image Segmentation in the browser using TensorFlow.js pre-trained DeepLab model. Here, we will use the DeepLab model’s output to manipulate specific parts of the image based on user selection. Essentially, we will allow the user to remove or restore a specific segment of an image that corresponds to an object class identified by the model. ...

In Computer Vision, one of the main challenges is to understand an image at a higher level like the way we humans do, i.e., to identify the objects, their location and their surroundings to make sense of the scene captured in the image. Semantic Image Segmentation is the process of identifying the objects present in the image and labelling each pixel by associating it to an identified object class. Semantic Image Segmentation can be applied to a wide variety of use cases such as human body segmentation, separating the background from foreground in an image, and understanding the surroundings for self-driving cars, just to name a few. ...

As most of us are working from home now, it has become a normal thing to set a custom background for our video calls through popular apps such as Zoom or Microsoft Teams. In this article, we will look at how to change the background for live webcam videos using TensorFlow.js . Person Segmentation in action We will be making use of the BodyPix model which is a pre-trained TensorFlow.js model. This model performs image segmentation - specifically person and human body parts segmentation. ...

Most of us interested in TensorFlow.js would be familiar with the popular demo of disappearing people in real time by Jason Mayes. This is a fantastic example of what is possible using TensorFlow.js in the browser. Jason is gracious to share the code of this application for others to learn and implement their own versions of such applications. In this article, I will attempt to document and walkthrough this code, so that it helps anyone who is trying to understand the code for this app. ...