code: def process_image(self, img_path):
      (
          out_cls_pred,
          out_rpn_rois,
          out_bbox_regr,
          dims,
      ) = self.process_image_detailed(img_path)
      labels = out_cls_pred.argmax(axis=1)
      regressed_rois = regress_rois(
          out_rpn_rois, out_bbox_regr, labels, dims
      )
  
      return regressed_rois, out_cls_pred
  
file_path: CNTK/Examples/Image/Detection/FasterRCNN/FasterRCNN_eval.py
imports: import os
  import numpy
  import cntk
  from cntk import input_variable, Axis
  from utils.map_helpers import evaluate_detections
  from utils.plot_helpers import load_resize_and_pad
  from utils.rpn.bbox_transform import regress_rois
  from utils.od_mb_source import ObjectDetectionMinibatchSource
label_desc: Use image node_id 2 for calling the FasterRCNN_Evaluator obj's underlying member method code with example usage: obj.process_image(img_path) and returns: regressed_rois,  out_cls_pred