code: def __init__(self, root, transforms):
      self.root = root
      self.transforms = transforms
      # load all image files, sorting them to
      # ensure that they are aligned
      self.imgs = list(
          sorted(os.listdir(os.path.join(root, "PNGImages")))
      )
      self.masks = list(
          sorted(os.listdir(os.path.join(root, "PedMasks")))
      )
  
file_path: vision/gallery/others/plot_repurposing_annotations.py
imports: import os
  import numpy
  import torch
  import matplotlib.pyplot
  import torchvision.transforms.functional
  from torchvision.io import read_image
  from torchvision.utils import draw_segmentation_masks
  from torchvision.ops import masks_to_boxes
  from torchvision.utils import draw_bounding_boxes
  from torchvision.models.detection import fasterrcnn_resnet50_fpn, FasterRCNN_ResNet50_FPN_Weights
label_desc: Use image node_id 1 to create a new SegmentationToDetectionDataset object from inherited base classes: torch.utils.data with example: obj = SegmentationToDetectionDataset(root, transforms)