吴裕雄 python深度学习与实践（3）

import threading, time

def doWaiting():
    print(‘start waiting:‘, time.strftime(‘%S‘))
    time.sleep(3)
    print(‘stop waiting‘, time.strftime(‘%S‘))
thread1 = threading.Thread(target = doWaiting)
thread1.start()
time.sleep(1)  #确保线程thread1已经启动
print(‘start join‘)
thread1.join() #将一直堵塞，直到thread1运行结束。
print(‘end join‘)

原文地址：https://www.cnblogs.com/tszr/p/10352674.html

时间： 2024-11-06 09:38:51

吴裕雄 python深度学习与实践（3）的相关文章

吴裕雄 python深度学习与实践（1）

#coding = utf8 import threading,time count = 0 class MyThread(threading.Thread): def __init__(self,threadName): super(MyThread,self).__init__(name = threadName) def run(self): global count for i in range(100): count = count + 1 time.sleep(0.3) print(

吴裕雄 python深度学习与实践（2）

#coding = utf8 import threading,time,random count = 0 class MyThread (threading.Thread): def __init__(self,lock,threadName): super(MyThread,self).__init__(name = threadName) self.lock = lock def run(self): global count self.lock.acquire() for i in ra

吴裕雄 python深度学习与实践（4）

import numpy,math def softmax(inMatrix): m,n = numpy.shape(inMatrix) outMatrix = numpy.mat(numpy.zeros((m,n))) soft_sum = 0 for idx in range(0,n): outMatrix[0,idx] = math.exp(inMatrix[0,idx]) soft_sum += outMatrix[0,idx] for idx in range(0,n): outMat

吴裕雄 python深度学习与实践（5）

import numpy as np data = np.mat([[1,200,105,3,False], [2,165,80,2,False], [3,184.5,120,2,False], [4,116,70.8,1,False], [5,270,150,4,True]]) row = 0 for line in data: row += 1 print(row) print(data.size) import numpy as np data = np.mat([[1,200,105,3

吴裕雄 python深度学习与实践（6）

from pylab import * import pandas as pd import matplotlib.pyplot as plot import numpy as np filePath = ("G:\\MyLearning\\TensorFlow_deep_learn\\data\\dataTest.csv") dataFile = pd.read_csv(filePath,header=None, prefix="V") summary = dat

吴裕雄 python深度学习与实践（7）

import cv2 import numpy as np img = np.mat(np.zeros((300,300))) cv2.imshow("test",img) cv2.waitKey(0) import cv2 import numpy as np img = np.mat(np.zeros((300,300),dtype=np.uint8)) cv2.imshow("test",img) cv2.waitKey(0) import cv2 impor

吴裕雄 python深度学习与实践（8）

import cv2 import numpy as np img = cv2.imread("G:\\MyLearning\\TensorFlow_deep_learn\\data\\lena.jpg") img_hsv = cv2.cvtColor(img,cv2.COLOR_BGR2HSV) turn_green_hsv = img_hsv.copy() turn_green_hsv[:,:,0] = (turn_green_hsv[:,:,0] - 30 ) % 180 tur

吴裕雄 python深度学习与实践（10）

import tensorflow as tf input1 = tf.constant(1) print(input1) input2 = tf.Variable(2,tf.int32) print(input2) input2 = input1 sess = tf.Session() print(sess.run(input2)) import tensorflow as tf input1 = tf.placeholder(tf.int32) input2 = tf.placeholder

吴裕雄 python深度学习与实践（11）

import numpy as np from matplotlib import pyplot as plt A = np.array([[5],[4]]) C = np.array([[4],[6]]) B = A.T.dot(C) AA = np.linalg.inv(A.T.dot(A)) l=AA.dot(B) P=A.dot(l) x=np.linspace(-2,2,10) x.shape=(1,10) xx=A.dot(x) fig = plt.figure() ax= fig.