docstr: The setup class method for the basic test case with all default values.
code: def setUpClass(self):
      """
      The setup class method for the basic test case with all default values.
      """
      self.feature = "myimage"
      self.annotations = "myannotations"
      self.pre_trained_model = "darknet-yolo"
      ## Create the model
      self.def_opts = {
          "model": "darknet-yolo",
          "max_iterations": 0,
      }
  
      # Model
      self.sf = _get_data(
          feature=self.feature, annotations=self.annotations
      )
      self.model = tc.object_detector.create(
          self.sf,
          feature=self.feature,
          annotations=self.annotations,
          batch_size=2,
          max_iterations=1,
          model=self.pre_trained_model,
      )
  
      ## Answers
      self.opts = self.def_opts.copy()
      self.opts["max_iterations"] = 1
  
      self.get_ans = {
          "_model": lambda x: True,
          "_class_to_index": lambda x: isinstance(x, dict),
          "_training_time_as_string": lambda x: isinstance(x, str),
          "_grid_shape": lambda x: tuple(x) == (13, 13),
          "model": lambda x: x == self.pre_trained_model,
          "anchors": lambda x: (
              isinstance(x, (list, tuple, np.ndarray))
              and len(x) > 0
              and len(x[0]) == 2
          ),
          "input_image_shape": lambda x: tuple(x) == (3, 416, 416),
          "batch_size": lambda x: x == 2,
          "classes": lambda x: x == sorted(_CLASSES),
          "feature": lambda x: x == self.feature,
          "max_iterations": lambda x: x >= 0,
          "non_maximum_suppression_threshold": lambda x: 0 <= x <= 1,
          "training_time": lambda x: x > 0,
          "training_iterations": lambda x: x > 0,
          "training_epochs": lambda x: x >= 0,
          "num_bounding_boxes": lambda x: x > 0,
          "num_examples": lambda x: x > 0,
          "training_loss": lambda x: x > 0,
          "annotations": lambda x: x == self.annotations,
          "num_classes": lambda x: x == len(_CLASSES),
      }
  
      self.get_ans["annotation_position"] = lambda x: isinstance(x, str)
      self.get_ans["annotation_scale"] = lambda x: isinstance(x, str)
      self.get_ans["annotation_origin"] = lambda x: isinstance(x, str)
      self.get_ans["grid_height"] = lambda x: x > 0
      self.get_ans["grid_width"] = lambda x: x > 0
      self.get_ans["random_seed"] = lambda x: isinstance(x, int)
      self.get_ans["verbose"] = lambda x: True
      del self.get_ans["_model"]
      del self.get_ans["_class_to_index"]
      del self.get_ans["_grid_shape"]
      del self.get_ans["anchors"]
      del self.get_ans["non_maximum_suppression_threshold"]
  
      self.fields_ans = self.get_ans.keys()
  
imports: from __future__ import print_function
  from __future__ import division
  from __future__ import absolute_import
  import unittest
  import pytest
  from .None import util
  import turicreate
  import tempfile
  import numpy
  import platform
  import pytest
  import sys
  import os
  from turicreate.toolkits._main import ToolkitError
  from turicreate.toolkits._internal_utils import _raise_error_if_not_sarray, _mac_ver
  from six import StringIO
label_desc: Use image node_id 1 for calling the ObjectDetectorTest obj's underlying member method code with example usage: obj.setUpClass() without return types