我正在努力比较边界框和组合重叠太多的框。我从另一篇文章中得到了这段代码:
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:这个代码只比较第一个到边界框的重叠,这意味着如果我检查大框的重叠程度,那么百分比会小于重叠的百分比。小盒子。我用以下方法替换重叠功能解决了这个问题:
overlap = np.maximum((w * h) / area[idxs[:last]],(w * h) / area[i])
这似乎有效。
但现在我还有另一个问题:如果找到两个重叠的框,代码不会用两个框的外角大的新框替换这两个框。它只删除其中一个框并离开另一个框,即使它是较小的框。 我怎么解决这个问题?我想用更大的边框替换那些盒子。
提前谢谢!