Function get_coord

vis.py:107–148

(root_pose, body_pose, lhand_pose, rhand_pose, jaw_pose, shape, expr, cam_trans, mode='test', zero_global=False, mesh=False)

    return frames

def get_coord(root_pose, body_pose, lhand_pose, rhand_pose, jaw_pose, shape, expr, cam_trans, mode='test', zero_global=False, mesh=False):
    batch_size = root_pose.shape[0]
    zero_pose = torch.zeros((1, 3)).float().cuda().repeat(batch_size, 1)  # eye poses
    if not zero_global:
        output = smplx_layer(betas=shape, body_pose=body_pose, global_orient=root_pose, right_hand_pose=rhand_pose,
                                    left_hand_pose=lhand_pose, jaw_pose=jaw_pose, leye_pose=zero_pose,
                                    reye_pose=zero_pose, expression=expr)
    else:
        raise ValueError
        output = smplx_layer(betas=shape, body_pose=body_pose, global_orient=zero_pose, right_hand_pose=rhand_pose,
                            left_hand_pose=lhand_pose, jaw_pose=zero_pose, leye_pose=zero_pose,
                            reye_pose=zero_pose, expression=expr)

    # camera-centered 3D coordinate
    mesh_cam = output.vertices
    joint_cam = output.joints[:, smpl_x.joint_idx, :]

    # project 3D coordinates to 2D space
    x = (joint_cam[:, :, 0] + cam_trans[:, None, 0]) / (joint_cam[:, :, 2] + cam_trans[:, None, 2] + 1e-4) * \
        focal[0] + princpt[0]
    y = (joint_cam[:, :, 1] + cam_trans[:, None, 1]) / (joint_cam[:, :, 2] + cam_trans[:, None, 2] + 1e-4) * \
        focal[1] + princpt[1]
    x = x / input_body_shape[1] * output_hm_shape[2]
    y = y / input_body_shape[0] * output_hm_shape[1]
    joint_proj = torch.stack((x, y), 2)

    # mesh
    if mesh:
        tx = (mesh_cam[:, :, 0] + cam_trans[:, None, 0]) / (mesh_cam[:, :, 2] + cam_trans[:, None, 2] + 1e-4) * \
            focal[0] + princpt[0]
        ty = (mesh_cam[:, :, 1] + cam_trans[:, None, 1]) / (mesh_cam[:, :, 2] + cam_trans[:, None, 2] + 1e-4) * \
            focal[1] + princpt[1]
        tx = tx / input_body_shape[1] * output_hm_shape[2]
        ty = ty / input_body_shape[0] * output_hm_shape[1]
        mesh_proj = torch.stack((tx, ty), 2)
        root_cam = joint_cam[:, smpl_x.root_joint_idx, None, :]
        joint_cam = joint_cam - root_cam
        render_mesh_cam = mesh_cam + cam_trans[:, None, :]  # for rendering

        return render_mesh_cam
    else:
        return joint_proj

def render(img, mesh, face, cam_param):
    # mesh