class_docstr: Pix3D is a large-scale dataset of diverse image-shape pairs with pixel-level 2D-3D alignment.
class_docstr_tok: ["Pix3D","is","a","large-scale","dataset","of","diverse","image-shape","pairs","with","pixel-level","2D-3D","alignment","."]
docstr: Returns SplitGenerators.
docstr_tok: ["Returns","SplitGenerators","."]
code: def _split_generators(self, dl_manager):
      """Returns SplitGenerators."""
  
      pix3d_dir = dl_manager.download_and_extract(
          "http://pix3d.csail.mit.edu/data/pix3d.zip"
      )
  
      return [
          tfds.core.SplitGenerator(
              name=tfds.Split.TRAIN,
              gen_kwargs={
                  "samples_directory": pix3d_dir,
                  "split_file": self.TRAIN_SPLIT_IDX,
              },
          ),
          tfds.core.SplitGenerator(
              name=tfds.Split.TEST,
              gen_kwargs={
                  "samples_directory": pix3d_dir,
                  "split_file": self.TEST_SPLIT_IDX,
              },
          ),
      ]
  
file_path: graphics/tensorflow_graphics/datasets/pix3d/pix3d.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import json
  import os
  import numpy
  import tensorflow
  from tensorflow_datasets import features
  import tensorflow_datasets.public_api
  from tensorflow_graphics.datasets import features
label_desc: Use image node_id 2 for calling the Pix3d obj's underlying member method code with example usage: obj._split_generators(dl_manager) and returns: list