Compare the results of rendering

nmr_vs_softras.py

import os
import tqdm
import argparse

import torch
import torch.nn as nn
import torchvision

from skimage.io import imread, imsave

import neural_renderer as nr
import soft_renderer as sr

current_dir = os.path.dirname(os.path.realpath(__file__))
data_dir = os.path.join(current_dir, 'data')


def main():
  parser = argparse.ArgumentParser()
  parser.add_argument('-io', '--filename_obj', type=str, default=os.path.join(data_dir, 'teapot.obj'))
  opts = parser.parse_args()
  
  # load .obj
  vertices, faces = nr.load_obj(opts.filename_obj)
  vertices, faces = vertices[None,:,:], faces[None,:,:]
  
  nmr_renderer  = nr.Renderer(camera_mode='look_at',  perspective=False)
  nmr_renderer.eye = [0, 0, -2.732]
  
  softras_renderer = sr.SoftRenderer(camera_mode='look_at', perspective=False, eye=[0, 0, -2.732])
  
  nmr_images = nmr_renderer(vertices, faces, mode='silhouettes')
  softras_images = softras_renderer(vertices, faces)[:,-1,:,:]
  
  image_1st = torch.cat((nmr_images, softras_images), dim=2)
  image_2nd = torch.cat((softras_images, nmr_images), dim=2)
  torchvision.utils.save_image(torch.cat((image_1st,image_2nd), dim=1), '../logs/my_cat.png')

if __name__=='__main__':
  main()