video1.0<iframe src="https://www.loom.com/embed/e16fdf1eebbe4f5a836301466ba6af82" frameborder="0" width="1728" height="1296" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>12961728Loomhttps://www.loom.com12961728https://cdn.loom.com/sessions/thumbnails/e16fdf1eebbe4f5a836301466ba6af82-03d1bae61dd260d8.gif143.011In this video, I walk you through the implementation of deep segmentation in a mobile application using a TensorFlow Lite model trained with YOLO. I created a backend API using Flask to process images from the frontend, which allows us to generate polygon masks for segmentation. You'll see how the frontend, built with Flutter, interacts with the backend to display these results. Please take a look at the example I provide to better understand the process.