code: def show_results(
      model: nn.Module,
      dataset: Dataset,
      detection_threshold: float = 0.25,
      nms_iou_threshold: float = 0.45,
      num_samples: int = 6,
      ncols: int = 3,
      denormalize_fn: Optional[callable] = denormalize_imagenet,
      show: bool = True,
      device: Optional[torch.device] = None,
  ) -> None:
      return base_show_results(
          predict_fn=predict,
          model=model,
          dataset=dataset,
          num_samples=num_samples,
          ncols=ncols,
          denormalize_fn=denormalize_fn,
          show=show,
          detection_threshold=detection_threshold,
          nms_iou_threshold=nms_iou_threshold,
          device=device,
      )
  
file_path: icevision/icevision/models/ultralytics/yolov5/show_results.py
imports: from icevision.imports import *
  from icevision.utils import *
  from icevision.core import *
  from icevision.data import *
  from icevision.models.base_show_results import base_show_results
  from icevision.models.ultralytics.yolov5.dataloaders import build_infer_batch, valid_dl, infer_dl
  from icevision.models.ultralytics.yolov5.prediction import predict, predict_from_dl
  from icevision.models.interpretation import Interpretation
  from icevision.models.interpretation import _move_to_device
  from icevision.core.record_components import LossesRecordComponent
  from yolov5.utils.loss import ComputeLoss
label_desc: Use image node_id 1 for calling a global function with example usage: show_results(model, dataset, detection_threshold, nms_iou_threshold, num_samples, ncols, denormalize_fn, show, device) and returns: base_show_results