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Image segmentation is a method used in computer vision to group pixels in an image into semantic areas, which is typically used to locate objects and boundaries. Body segmentation models do the same thing for a person and their twenty-four body parts. This technology can be used for a variety of purposes, including augmented reality, picture editing, and creative effects on photographs and movies, to name a few. The TensorFlow team has recently released two new highly optimized body segmentation models that are accurate and quick as part of their improved body segmentation and posture APIs in TensorFlow.js. Github: https://github.com/tensorflow/tfjs-models/tree/master/pose-detection/src/blazepose_mediapipe Demo: https://storage.googleapis.com/tfjs-models/demos/segmentation/index.html?model=blazepose Tensorflow blog: https://blog.tensorflow.org/2022/01/body-segmentation.html submitted by /u/ai-lover |
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TensorFlow Team Introduce BlazePose GHUM Posture Estimation Model and Selfie Segmentation For Body Segmentation Using MediaPipe and TensorFlow.js
