code: def __init__(self):
      self.cv_module_method = {
          "vgg19_imagenet": "predict_classification",
          "vgg16_imagenet": "predict_classification",
          "vgg13_imagenet": "predict_classification",
          "vgg11_imagenet": "predict_classification",
          "shufflenet_v2_imagenet": "predict_classification",
          "se_resnext50_32x4d_imagenet": "predict_classification",
          "se_resnext101_32x4d_imagenet": "predict_classification",
          "resnet_v2_50_imagenet": "predict_classification",
          "resnet_v2_34_imagenet": "predict_classification",
          "resnet_v2_18_imagenet": "predict_classification",
          "resnet_v2_152_imagenet": "predict_classification",
          "resnet_v2_101_imagenet": "predict_classification",
          "pnasnet_imagenet": "predict_classification",
          "nasnet_imagenet": "predict_classification",
          "mobilenet_v2_imagenet": "predict_classification",
          "googlenet_imagenet": "predict_classification",
          "alexnet_imagenet": "predict_classification",
          "yolov3_coco2017": "predict_object_detection",
          "ultra_light_fast_generic_face_detector_1mb_640": "predict_object_detection",
          "ultra_light_fast_generic_face_detector_1mb_320": "predict_object_detection",
          "ssd_mobilenet_v1_pascal": "predict_object_detection",
          "pyramidbox_face_detection": "predict_object_detection",
          "faster_rcnn_coco2017": "predict_object_detection",
          "cyclegan_cityscapes": "predict_gan",
          "deeplabv3p_xception65_humanseg": "predict_semantic_segmentation",
          "ace2p": "predict_semantic_segmentation",
          "pyramidbox_lite_server_mask": "predict_mask",
          "pyramidbox_lite_mobile_mask": "predict_mask",
      }
      super(CVModuleInfo, self).__init__()
  
imports: import six
  import abc
label_desc: Use image node_id 1 to create a new CVModuleInfo object from inherited base classes: BaseModuleInfo with example: obj = CVModuleInfo()