code: def __init__(self, eval_model, cfg):
      # load model once in constructor and push images through the model in 'process_image()'
      self._img_shape = (
          cfg.NUM_CHANNELS,
          cfg.IMAGE_HEIGHT,
          cfg.IMAGE_WIDTH,
      )
      image_input = input_variable(
          shape=self._img_shape,
          dynamic_axes=[Axis.default_batch_axis()],
          name=cfg["MODEL"].FEATURE_NODE_NAME,
      )
      dims_input = input_variable(
          (1, 6),
          dynamic_axes=[Axis.default_batch_axis()],
          name="dims_input",
      )
      self._eval_model = eval_model(image_input, dims_input)
  
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 1 to create a new FasterRCNN_Evaluator object  with example: obj = FasterRCNN_Evaluator(eval_model, cfg)