Exploring SMPLify

Now that we have a broad overview of how to estimate the 3D body shape of a person in a 2D RGB image, let us get a hands-on experience with code. Concretely, we are going to fit a 3D body shape onto two 2D images from the Leeds Sports Pose (LSP) dataset. This dataset contains 2,000 pose-annotated images of mostly sportspeople gathered from Flickr. We will first run through the code and generate these fitted body shapes before we dig deeper into the code. All the code used in this section was adapted from the implementation of the paper titled Keep it SMPL: Automatic Estimation of 3D Human Pose and Shape from a Single Image. We have only adapted it in a way that helps you, the learner, to quickly run the code and visualize the outputs yourself.

This code was originally created by the authors of SMPLify for python2. Therefore, we need to use the same python2 environment we used while exploring the SMPL model. Before we run any code, let us quickly get an overview...