合并重叠的边界框，替换为周围的边界框

Question

我正在比较边界框和组合重叠过多的框。我从另一篇文章中使用了此代码：

def non_max_suppression_fast(boxes, overlapThresh):
   # if there are no boxes, return an empty list
   if len(boxes) == 0:
      return []

   # if the bounding boxes integers, convert them to floats --
   # this is important since we'll be doing a bunch of divisions
   if boxes.dtype.kind == "i":
      boxes = boxes.astype("float")
#  
   # initialize the list of picked indexes   
   pick = []

   # grab the coordinates of the bounding boxes
   x1 = boxes[:,0]
   y1 = boxes[:,1]
   x2 = boxes[:,2]
   y2 = boxes[:,3]

   # compute the area of the bounding boxes and sort the bounding
   # boxes by the bottom-right y-coordinate of the bounding box
   area = (x2 - x1 + 1) * (y2 - y1 + 1)
   idxs = np.argsort(y2)

   # keep looping while some indexes still remain in the indexes
   # list
   while len(idxs) > 0:
      # grab the last index in the indexes list and add the
      # index value to the list of picked indexes
      last = len(idxs) - 1
      i = idxs[last]
      pick.append(i)

      # find the largest (x, y) coordinates for the start of
      # the bounding box and the smallest (x, y) coordinates
      # for the end of the bounding box
      xx1 = np.maximum(x1[i], x1[idxs[:last]])
      yy1 = np.maximum(y1[i], y1[idxs[:last]])
      xx2 = np.minimum(x2[i], x2[idxs[:last]])
      yy2 = np.minimum(y2[i], y2[idxs[:last]])

      # compute the width and height of the bounding box
      w = np.maximum(0, xx2 - xx1 + 1)
      h = np.maximum(0, yy2 - yy1 + 1)

      # compute the ratio of overlap
      overlap = (w * h) / area[idxs[:last]]

      # delete all indexes from the index list that have
      idxs = np.delete(idxs, np.concatenate(([last],
         np.where(overlap > overlapThresh)[0])))

   # return only the bounding boxes that were picked using the
   # integer data type
   return boxes[pick].astype("int")

但是此代码不会用与两个重叠框组合在一起的新框一样大的新框替换两个重叠框。它仅删除两个框之一，并保留另一个框。我怎样才能解决这个问题？我不知道如何适当地更改“删除”行。我的想法是创建一个新列表并在其中添加新框，但是我不知道如何更改上面发布的代码。 另一个想法是保留删除行，并用新的边界框的参数替换其余的框参数。我通过以下代码获取新参数：

  xx1 = np.minimum(x1[i], x1[idxs[:last]])
  yy1 = np.minimum(y1[i], y1[idxs[:last]])
  xx2 = np.maximum(x2[i], x2[idxs[:last]])
  yy2 = np.maximum(y2[i], y2[idxs[:last]])

谢谢！