class_docstr: Visualizer is a transformer to visualize the detection results
  (tensors that encodes label, score, boundingbox)
  You can call image_frame.get_image() to get the visualized results
code: def __init__(
      self, label_map, thresh=0.3, encoding="png", bigdl_type="float"
  ):
      self.value = callZooFunc(
          bigdl_type,
          JavaValue.jvm_class_constructor(self),
          label_map,
          thresh,
          encoding,
      )
  
imports: import sys
  from bigdl.util.common import JavaValue
  from zoo.models.image.common.image_model import ImageModel
  from zoo.common.utils import callZooFunc
  from zoo.feature.image.imageset import *
  from zoo.feature.image.imagePreprocessing import *
label_desc: Use image node_id 1 to create a new Visualizer object from inherited base classes: ImagePreprocessing with example: obj = Visualizer(label_map, thresh, encoding, bigdl_type)