给定一个[未旋转的]矩形列表,获取该列表中任何其他矩形未包含的矩形列表的最快方法是什么?
例如:
[{x1:0, y1:0, x2:10, y2:10}, {x1:0, y1:0, x2:11, y2: 11}, {x1:5, y1:100, x2:5, y2:100}]
将返回:
[{x1:0, y1:0, x2:11, y2: 11}, {x1:5, y1:100, x2:5, y2:100}]
答案 0 :(得分:2)
我使用的是Python,我使用的函数将矩形列表作为输入。 像:
[[0,0, 10, 10], [0, 0, 11, 11], [5, 100, 5, 100]]
def non_max_suppression_fast(boxes, overlapThresh=1):
# 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 == 1)[0])))
# return only the bounding boxes that were picked using the
# integer data type
return boxes[pick].astype("int")