class_docstr: Decode the detection output
  The output of the model prediction is a 1-dim tensor
  The first element of tensor is the number(K) of objects detected,
  followed by [label score x1 y1 x2 y2] X K
  For example, if there are 2 detected objects, then K = 2, the tensor may
  looks like
  ```2, 1, 0.5, 10, 20, 50, 80, 3, 0.3, 20, 10, 40, 70```
  After decoding, it returns a 2-dim tensor, each row represents a detected object
  ```
  1, 0.5, 10, 20, 50, 80
  3, 0.3, 20, 10, 40, 70
  ```
code: def __init__(self, bigdl_type="float"):
      super(DecodeOutput, self).__init__(bigdl_type)
  
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 DecodeOutput object from inherited base classes: ImagePreprocessing with example: obj = DecodeOutput(bigdl_type)