class_docstr: Label Output tensor with corresponding real labels on specific dataset
  clses is the key in ImgFeature where you want to store all sorted mapped labels
  probs is the key in ImgFeature where you want to store all the sorted probilities for each class
class_docstr_tok: ["Label","Output","tensor","with","corresponding","real","labels","on","specific","dataset","clses","is","the","key","in","ImgFeature","where","you","want","to","store","all","sorted","mapped","labels","probs","is","the","key","in","ImgFeature","where","you","want","to","store","all","the","sorted","probilities","for","each","class"]
code: def __init__(self, label_map, clses, probs, bigdl_type="float"):
      self.value = callZooFunc(
          bigdl_type,
          JavaValue.jvm_class_constructor(self),
          label_map,
          clses,
          probs,
      )
  
file_path: analytics-zoo/pyzoo/zoo/models/image/imageclassification/image_classification.py
imports: from bigdl.transform.vision.image import FeatureTransformer
  from zoo.models.image.common.image_model import ImageModel
  from zoo.feature.image.imageset import *
  from zoo.common.utils import callZooFunc
label_desc: Use image node_id 1 to create a new LabelOutput object from inherited base classes: FeatureTransformer with example: obj = LabelOutput(label_map, clses, probs, bigdl_type)