code: def silhouette_renderer_from_pinhole_cam(cam, device="cpu"):
      focal_length = torch.tensor([[cam.fx, cam.fy]])
      principal_point = torch.tensor(
          [[cam.width - cam.cx, cam.height - cam.cy]]
      )  # In PyTorch3D, we assume that +X points left, and +Y points up and +Z points out from the image plane.
      image_size = torch.tensor([[cam.height, cam.width]])
      cameras = PerspectiveCameras(
          focal_length=focal_length,
          principal_point=principal_point,
          in_ndc=False,
          image_size=image_size,
          device=device,
      )
      blend_params = BlendParams(sigma=1e-4, gamma=1e-4)
      raster_settings = RasterizationSettings(
          image_size=(cam.height, cam.width),
          blur_radius=np.log(1.0 / 1e-4 - 1.0) * blend_params.sigma,
          faces_per_pixel=100,
      )
      silhouette_renderer = MeshRenderer(
          rasterizer=MeshRasterizer(
              cameras=cameras, raster_settings=raster_settings
          ),
          shader=SoftSilhouetteShader(blend_params=blend_params),
      )
      return silhouette_renderer
  
imports: import sys
  import os
  import argparse
  import numpy
  import torch
  from pytorch3d.structures import Meshes
  from pytorch3d.renderer import RasterizationSettings, MeshRenderer, MeshRasterizer, BlendParams, SoftSilhouetteShader, PerspectiveCameras
  from tqdm import tqdm
  import joblib
  import imageio
  from data_io import neuman_helper
  from utils import debug_utils, utils, ray_utils, render_utils
  from models.smpl import SMPL
  from geometry import pcd_projector
label_desc: Use image node_id 4 for calling a global function with example usage: silhouette_renderer_from_pinhole_cam(cam, device) and returns: silhouette_renderer