np.logical_and(box_w＞1, box_h＞1)作为目标检测无效数据过滤作用

假设有两组numpy数据：aa， bb

aa = np.array([0.3, 1.8, 4.9, 3, 7, 0.6, 0.98])
bb = np.array([3, 0.8, 2.9, 3, 7, 1.6, 1.98])

cc为如下运算结果

cc = np.logical_and(aa>1, bb>1)

得到的结果为：

cc = [False False True True True False False]

将cc得到的结果作为过滤器

aa_cc = aa[cc]
bb_cc = bb[cc]

得到的结果为(将True对应的值筛选出来)：

aa_cc =  [4.9 3.  7. ]
bb_cc =  [2.9 3.  7. ]

相关程序如下：

import numpy as np
aa = np.array([0.3, 1.8, 4.9, 3, 7, 0.6, 0.98])
bb = np.array([3, 0.8, 2.9, 3, 7, 1.6, 1.98])
cc = np.logical_and(aa>1, bb>1)
print("cc = ", cc)

aa_cc = aa[cc]
bb_cc = bb[cc]
print("aa_cc = ", aa_cc)
print("bb_cc = ", bb_cc)