code: def inference(
      model,
      im,
      trans_info=None,
      is_slide=False,
      stride=None,
      crop_size=None,
  ):
      """
      Inference for image.
  
      Args:
          model (paddle.nn.Layer): model to get logits of image.
          im (Tensor): the input image.
          trans_info (list): Image shape informating changed process. Default: None.
          is_slide (bool): Whether to infer by sliding window. Default: False.
          crop_size (tuple|list). The size of sliding window, (w, h). It should be probided if is_slide is True.
          stride (tuple|list). The size of stride, (w, h). It should be probided if is_slide is True.
  
      Returns:
          Tensor: If ori_shape is not None, a prediction with shape (1, 1, h, w) is returned.
              If ori_shape is None, a logit with shape (1, num_classes, h, w) is returned.
      """
      if hasattr(model, "data_format") and model.data_format == "NHWC":
          im = im.transpose((0, 2, 3, 1))
      if not is_slide:
          logits = model(im)
          if not isinstance(logits, collections.abc.Sequence):
              raise TypeError(
                  "The type of logits must be one of collections.abc.Sequence, e.g. list, tuple. But received {}".format(
                      type(logits)
                  )
              )
          logit = logits[0]
      else:
          logit = slide_inference(
              model, im, crop_size=crop_size, stride=stride
          )
      if hasattr(model, "data_format") and model.data_format == "NHWC":
          logit = logit.transpose((0, 3, 1, 2))
      if trans_info is not None:
          logit = reverse_transform(logit, trans_info, mode="bilinear")
          pred = paddle.argmax(
              logit, axis=1, keepdim=True, dtype="int32"
          )
          return pred, logit
      else:
          return logit
  
file_path: PaddleSeg/contrib/RSSegBenchmark/c2fnet/core/infer.py
imports: import collections.abc
  from itertools import combinations
  import numpy
  import cv2
  import paddle
  import paddle.nn.functional
label_desc: Use image node_id 5 for calling a global function with example usage: inference(model, im, trans_info, is_slide, stride, crop_size) and returns: pred,  logit, logit