code: def test_e2e_detect(
      samples_source, fridge_class_map, model_name, param_groups_len
  ):
      img_path = samples_source / "fridge/odFridgeObjects/images/10.jpg"
      tfms_ = tfms.A.Adapter([A.Resize(384, 384), A.Normalize()])
  
      backbone_fn = getattr(
          models.torchvision.faster_rcnn.backbones, model_name
      )
      backbone = backbone_fn(pretrained=False)
      model = faster_rcnn.model(num_classes=4, backbone=backbone)
  
      pred_dict = faster_rcnn.end2end_detect(
          img_path,
          tfms_,
          model,
          fridge_class_map,
          detection_threshold=1,
      )
      assert len(pred_dict["detection"]["bboxes"]) == 0
  
imports: from icevision.all import *
  from icevision.models.torchvision import faster_rcnn
  import albumentations
  import pytest
label_desc: Use image node_id 1 for calling a global function with example usage: test_e2e_detect(samples_source, fridge_class_map, model_name, param_groups_len) without return types