class_docstr: Gaussian heatmap target generator for simple pose.
  Adapted from https://github.com/Microsoft/human-pose-estimation.pytorch
  
  Parameters
  ----------
  num_joints : int
      Number of joints defined by dataset
  image_size : tuple of int
      Image size, as (width, height).
  heatmap_size : tuple of int
      Heatmap size, as (width, height).
  sigma : float
      Gaussian sigma for the heatmap generation.
class_docstr_tok: ["Gaussian","heatmap","target","generator","for","simple","pose",".","Adapted","from","https",":","\/\/github.com\/Microsoft\/human-pose-estimation.pytorch","Parameters","--","--","--","--","--","num_joints",":","int","Number","of","joints","defined","by","dataset","image_size",":","tuple","of","int","Image","size",",","as","(","width",",","height",")",".","heatmap_size",":","tuple","of","int","Heatmap","size",",","as","(","width",",","height",")",".","sigma",":","float","Gaussian","sigma","for","the","heatmap","generation","."]
code: def __init__(self, num_joints, image_size, heatmap_size, sigma=2):
      self._num_joints = num_joints
      self._sigma = sigma
      self._image_size = np.array(image_size)
      self._heatmap_size = np.array(heatmap_size)
      assert self._image_size.shape == (
          2,
      ), "Invalid shape of image_size, expected (2,)"
      assert self._heatmap_size.shape == (
          2,
      ), "Invalid shape of heatmap_size, expected (2,)"
      self._feat_stride = self._image_size / self._heatmap_size
  
imports: import numpy
label_desc: Use image node_id 1 to create a new SimplePoseGaussianTargetGenerator object from inherited base classes: object with example: obj = SimplePoseGaussianTargetGenerator(num_joints, image_size, heatmap_size, sigma)