code: def __call__(
      self, uint8_rgb: np.ndarray, threshold: Optional[float]
  ) -> np.ndarray:
      net = torch.from_numpy(uint8_rgb[None]).to(
          self.device, dtype=self.dtype
      )
      net = net.permute(0, 3, 1, 2).contiguous()
      net /= 255.0
      res = self.model(net)[-1]
      if threshold is not None:
          res = res > threshold
      res = res[0, 0].float().cpu().data.numpy()
      return to_uint8(res)
  
imports: import os
  import math
  import torch
  import numpy
  import torch.nn
  import torch.nn.functional
  from typing import Optional
  from cftool.cv import to_uint8
  from ....parameters import OPT
label_desc: Use image node_id 4 for calling the PiDiAPI obj's underlying member method code with example usage: obj.__call__(uint8_rgb, threshold) and returns: to_uint8