class_docstr: Basic type for points in an image
class_docstr_tok: ["Basic","type","for","points","in","an","image"]
docstr: Convert an array or a list of points `t` to a `Tensor`
docstr_tok: ["Convert","an","array","or","a","list","of","points","`","t","`","to","a","`","Tensor","`"]
code: def create(cls, t, img_size=None) -> None:
      "Convert an array or a list of points `t` to a `Tensor`"
      return cls(tensor(t).view(-1, 2).float(), img_size=img_size)
  
imports: from __future__ import annotations
  from ..torch_basics import *
  from ..data.all import *
  from PIL import Image
  from matplotlib import patches, patheffects
label_desc: Use image node_id 1 for calling the TensorPoint obj's underlying member method code with example usage: obj.create(cls, t, img_size) and returns: cls