Human Portrait Drawing with U-Squared Net and PyTorch

Have you ever tried an app for drawing portraits that allows you to get an AI-generated image of yourself in a matter of seconds by uploading a photo? This project will help you understand the app's capabilities by revealing its fundamental structure, which is the most advanced U-squared Network (U2-Net). Prepare yourself for the mass production of AI-generated human portraits! Data Scientist hired by a non-profit organization which has recently launched an initiative to help people who have disabilities improve their self-confidence. In the course of this campaign, the group will offer people free self-portraits. Because of the popularity of this campaign, it will be costly to employ numerous people to create these images. So, your task is to utilize AI to make it easier for the process of drawing portraits. In this project that is guided you will discover how a drawing application for portraits operates and create your own tool for drawing portraits by studying the structure of the cutting-edge **U-squared Net** model. Check out the output of the model below. It's awe-inspiring. U-squared Net is an innovative model structure, that is an nested U-structure which directly removes multi-scale elements stage-by-stage and is aimed at removing the most appealing regions from videos or images. It is among the most popular tasks in the area of. Through this instructional project, you'll be able to be able to understand the structure of Residual-U blocks, which are the basic elements of U-squared nets. The development of Residual-U blocks allows the network to record more context-specific information from the video or image locally as well as globally. In the next step you will observe and build the U-squared Net with PyTorch. As an added benefit of this project that is guided you will be given the opportunity to upload pictures of yourself or people you have met at the end to get portraits created by an already-trained.