conda install git (mask_rcnn_tf2) bim@bim-PowerEdge-R730:~/project/object_detection/pythons/Mask_RCNN/samples/coco$ (mask_rcnn_tf2) bim@bim-PowerEdge-R730:~/project/object_detection/pythons/Mask_RCNN/samples/coco$ conda install git Solving environment:
# 分类算法 1.KNN from sklearn.neighbors import KNeighborsClassifier 2.朴素贝叶斯 from sklearn.naive_bayes import BernoulliNB # 特征值是二分类 from sklearn.naive_bayes import GaussianNB from sklearn.naive_bayes import MultinomialNB 3.逻辑回归【二分类】 fr
一、深浅copy（*）(相对底层原理)#默认情况下都是浅copy""" #遍历：所有取一遍l1 = [111,222,[333,444]] #所有可以被for循环遍历的类型都可以传给list然后转换成列表l2 = l1.copy()l3 = l1[:]#print(id(l1[0]),id(l1[1]),id(l1[2]))#print(id(l2[0]),id(l2[1]),id(l2[2]))#l1[2][0] = 66
队列与堆栈 队列：先进先出FIFO l=[ ] l.append(11) [11] l.append(22) [11,22] l.append(33) [11,22,33] l.pop(0) 11 l.pop(0) 22 l.pop(0) 33 堆栈: 先进后出LIFO l=[ ] l.append(11) [11] l.append(22) [11,22] l.append(33) [11,22,33] l.pop(-1) 33 l.pop(-1) 22 l.pop(-
一.关系运算 有如下两个集合，pythons是报名python课程的学员名字集合，linuxs是报名linux课程的学员名字集合 pythons={'alex','egon','yuanhao','wupeiqi','gangdan','biubiu'} linuxs={'wupeiqi','oldboy','gangdan&
1、有列表data = ['egon', 73, [1900, 3, 18]]，分别取出列表中的名字，年龄，出生的年，月，日赋值给不同的变量 data = ['egon',73,[1900,3,18]]name = data[0]age = data[1]birth = data[2]year_of_birth = birth[0]month_of_birth = birth[1]day_of_birth = birth[2] 2、用列表
