Python 组合重叠矩形，将重叠与两个矩形进行比较，并用边界矩形替换两个矩形

我正在比较边界框和重叠过多的组合框。我在另一篇文章中使用了以下代码：

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")

我有两个问题：这段代码只比较从第一个框到边界框的重叠，这意味着如果我检查大框有多少重叠，百分比要比小框的重叠百分比小得多。我解决了这个问题，用这个替换了重叠功能：

这似乎奏效了

但现在我有另一个问题：如果发现两个重叠的框，代码不会用一个与两个框的外角一样大的新框替换这两个框。它只是删除其中一个框，并保留另一个框，即使它是较小的一个。 我怎样才能解决这个问题？我想用一个更大的边界框替换这些框

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提前谢谢你

您是否将此代码与

findContours

函数一起使用？我使用Canny和findContours的组合：edge=cv.Canny（灰色、thrs1、thrs2、光圈大小=5）…..cnts、=cv.findContours（edge.copy（）、cv.RETR\u外部、cv.CHAIN\u近似简单）

 overlap = np.maximum((w * h) / area[idxs[:last]],(w * h) / area[i])