如何解决"Use scipy.optimize.linear_sum_assignment instead"

Question

我正在使用python脚本进行检测。我的脚本中有以下行：

import time
import cv2 as cv
import glob
import argparse
import sys
import numpy as np
import os.path
from imutils.video import FPS
from collections import deque
from sklearn.utils.linear_assignment_ import linear_assignment

当我运行脚本时，我有以下几行：

/home/user/.local/lib/python3.6/site-packages/sklearn/utils/linear_assignment_.py:127:
     DeprecationWarning: The linear_assignment function is deprecated in 0.21 and will be removed from 0.23. Use scipy.optimize.linear_sum_assignment instead.
     DeprecationWarning)

请建议我如何解决。

Answer 1

您需要用scipy.optimize.linear_sum_assignment function替换sklearn.utils.linear_assignment_.linear_assignment函数。

区别在于返回格式： linear_assignment()是返回a numpy array 和 linear_sum_assignment() a numpy arrays的元组。您可以通过在数组中转换linear_sum_assignment((的输出并转换它来获得相同的输出。

您的脚本应该看起来像这样：

import time
import cv2 as cv
import glob
import argparse
import sys
import numpy as np
import os.path
from imutils.video import FPS
from collections import deque
from scipy.optimize import linear_sum_assignment
#compute your cost matrix
indices = linear_sum_assignment(cost_matrix)  
indices = np.asarray(indices)
indices = np.transpose(indices)

Answer 2

linear_assignment for linear_sum_assignment

# from sklearn.utils.linear_assignment_ import linear_assignment
from scipy.optimize import linear_sum_assignment
cost = np.array([[4, 1, 3], [2, 0, 5], [3, 2, 2]])
# result = linear_assignment(cost)
result = linear_sum_assignment(cost)
result = np.array(list(zip(*result)))

https://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.linear_sum_assignment.html