text: __author__ = 'tsungyi'
  
  import pycocotool._mask as _mask
  # Interface for manipulating masks stored in RLE format.
  #
  # RLE is a simple yet efficient format for storing binary masks. RLE
  # first divides a vector (or vectorized image) into a series of piecewise
  # constant regions and then for each piece simply stores the length of
  # that piece. For example, given M=[0 0 1 1 1 0 1] the RLE counts would
  # be [2 3 1 1], or for M=[1 1 1 1 1 1 0] the counts would be [0 6 1]
  # (note that the odd counts are always the numbers of zeros). Instead of
  # storing the counts directly, additional compression is achieved with a
  # variable bitrate representation based on a common scheme called LEB128.
  #
  # Compression is greatest given large piecewise constant regions.
  # Specifically, the size of the RLE is proportional to the number of
  # *boundaries* in M (or for an image the number of boundaries in the y
  # direction). Assuming fairly simple shapes, the RLE representation is
  # O(sqrt(n)) where n is number of pixels in the object. Hence space usage
  # is substantially lower, especially for large simple objects (large n).
  #
  # Many common operations on masks can be computed directly using the RLE
  # (without need for decoding). This includes computations such as area,
  # union, intersection, etc. All of these operations are linear in the
  # size of the RLE, in other words they are O(sqrt(n)) where n is the area
  # of the object. Computing these operations on the original mask is O(n).
  # Thus, using the RLE can result in substantial computational savings.
  #
  # The following API functions are defined:
  #  encode         - Encode binary masks using RLE.
  #  decode         - Decode binary masks encoded via RLE.
  #  merge          - Compute union or intersection of encoded masks.
  #  iou            - Compute intersection over union between masks.
  #  area           - Compute area of encoded masks.
  #  toBbox         - Get bounding boxes surrounding encoded masks.
  #  frPyObjects    - Convert polygon, bbox, and uncompressed RLE to encoded RLE mask.
  #
  # Usage:
  #  Rs     = encode( masks )
  #  masks  = decode( Rs )
  #  R      = merge( Rs, intersect=false )
  #  o      = iou( dt, gt, iscrowd )
  #  a      = area( Rs )
  #  bbs    = toBbox( Rs )
  #  Rs     = frPyObjects( [pyObjects], h, w )
  #
  # In the API the following formats are used:
  #  Rs      - [dict] Run-length encoding of binary masks
  #  R       - dict Run-length encoding of binary mask
  #  masks   - [hxwxn] Binary mask(s) (must have type np.ndarray(dtype=uint8) in column-major order)
  #  iscrowd - [nx1] list of np.ndarray. 1 indicates corresponding gt image has crowd region to ignore
  #  bbs     - [nx4] Bounding box(es) stored as [x y w h]
  #  poly    - Polygon stored as [[x1 y1 x2 y2...],[x1 y1 ...],...] (2D list)
  #  dt,gt   - May be either bounding boxes or encoded masks
  # Both poly and bbs are 0-indexed (bbox=[0 0 1 1] encloses first pixel).
  #
  # Finally, a note about the intersection over union (iou) computation.
  # The standard iou of a ground truth (gt) and detected (dt) object is
  #  iou(gt,dt) = area(intersect(gt,dt)) / area(union(gt,dt))
  # For "crowd" regions, we use a modified criteria. If a gt object is
  # marked as "iscrowd", we allow a dt to match any subregion of the gt.
  # Choosing gt' in the crowd gt that best matches the dt can be done using
  # gt'=intersect(dt,gt). Since by definition union(gt',dt)=dt, computing
  #  iou(gt,dt,iscrowd) = iou(gt',dt) = area(intersect(gt,dt)) / area(dt)
  # For crowd gt regions we use this modified criteria above for the iou.
  #
  # To compile run "python setup.py build_ext --inplace"
  # Please do not contact us for help with compiling.
  #
  # Microsoft COCO Toolbox.      version 2.0
  # Data, paper, and tutorials available at:  http://mscoco.org/
  # Code written by Piotr Dollar and Tsung-Yi Lin, 2015.
  # Licensed under the Simplified BSD License [see coco/license.txt]
  
  iou         = _mask.iou
  merge       = _mask.merge
  frPyObjects = _mask.frPyObjects
  
  def encode(bimask):
      if len(bimask.shape) == 3:
          return _mask.encode(bimask)
      elif len(bimask.shape) == 2:
          h, w = bimask.shape
          return _mask.encode(bimask.reshape((h, w, 1), order='F'))[0]
  
  def decode(rleObjs):
      if type(rleObjs) == list:
          return _mask.decode(rleObjs)
      else:
          return _mask.decode([rleObjs])[:,:,0]
  
  def area(rleObjs):
      if type(rleObjs) == list:
          return _mask.area(rleObjs)
      else:
          return _mask.area([rleObjs])[0]
  
  def toBbox(rleObjs):
      if type(rleObjs) == list:
          return _mask.toBbox(rleObjs)
      else:
          return _mask.toBbox([rleObjs])[0]