code: def __getitem__(self, idx):
      # Read in PIL image and target in COCO format
      img, target = super(CocoDetection, self).__getitem__(idx)
  
      # Preprocess image and target (converting target to DETR format, resizing + normalization of both image and target)
      image_id = self.ids[idx]
      target = {"image_id": image_id, "annotations": target}
      encoding = self.feature_extractor(
          images=img, annotations=target, return_tensors="pt"
      )
      pixel_values = encoding[
          "pixel_values"
      ].squeeze()  # remove batch dimension
      target = encoding["labels"][0]  # remove batch dimension
  
      return pixel_values, target
  
imports: import os
  import torchvision
label_desc: Use image node_id 2 for calling the CocoDetection obj's underlying member method code with example usage: obj.__getitem__(idx) and returns: pixel_values,  target