code: def __call__(self, imgs):
      imgs = imgs.transpose(0, 3, 1, 2).astype("float32")
      imgs = (imgs - 127.5) * 0.0078125
      outputs = self.ort_session.run(
          self.output_names, {self.input_name: imgs}
      )
      return outputs[0]
  
imports: import os
  import cv2
  import numpy
  import pandas
  from tqdm import tqdm
  from skimage import transform
  from sklearn.preprocessing import normalize
  from sklearn.metrics import roc_curve, auc
label_desc: Use image node_id 2 for calling the ONNX_model_interf obj's underlying member method code with example usage: obj.__call__(imgs) and returns: outputs