登录
首页 » python » python检测鼠标键盘是否按下的程序

python检测鼠标键盘是否按下的程序

于 2023-03-19 发布 文件大小:4.27 kB
0 138
下载积分: 2 下载次数: 1

代码说明:

python 检测鼠标键盘是否按下去,该源码程序调用了user32.dll,在windows下面可以实现极快的鼠标键盘按下检测等各种功能,是开发游戏、辅助程序、其他功能性软件必不可少的部分,建议开一个线程实施检测

下载说明:请别用迅雷下载,失败请重下,重下不扣分!

发表评论

0 个回复

  • Python金融大数据分析.pdf
    关于python在金融领域的应用 并有在计量经济学的具体实例。(The application of Python in the financial field about the application of Python in the financial field)
    2018-01-25 15:59:00下载
    积分:1
  • PYTHON学习领悟
    最近刚刚意识到python的重要性,学习中遇到并总结的经典知识记录在案(Recently, just realizing the importance of Python, the classic knowledge encountered and summarized in the study is recorded)
    2018-10-18 12:16:11下载
    积分:1
  • 车牌识别
    说明:  python+opencv实现车牌识别,通过canny算子边缘检测+颜色识别提取车牌区域(License plate recognition based on Python + opencv)
    2020-04-27 01:10:40下载
    积分:1
  • hucai
    水表图像识别 图像预处理 哈哈就不懂四周(Water Meter Image Recognition)
    2019-06-19 18:27:49下载
    积分:1
  • adaboost
    AdaBoost元算法属于boosting系统融合方法中最流行的一种,说白了就是一种串行训练并且最后加权累加的系统融合方法。 具体的流程是:每一个训练样例都赋予相同的权重,并且权重满足归一化,经过第一个分类器分类之后, 计算第一个分类器的权重alpha值,并且更新每一个训练样例的权重,然后再进行第二个分类器的训练,相同的方法....... 直到错误率为0或者达到指定的训练轮数,其中最后预测的标签计算是各系统*alpha的加权和,然后sign(预测值)。 可以看出,训练流程是串行的,并且训练样例的权重是一直在变化的,分错的样本的权重不断加大,正确的样本的权重不断减小。 AdaBoost元算法是boosting中流行的一种,还有其他的系统融合的方法,比如bagging方法以及随机森林。 对于非均衡样本的处理,一般可以通过欠抽样(undersampling)或者过抽样(oversampling),欠抽样是削减样本的数目, 过抽样是重复的选取某些样本,最好的方法是两种进行结合的方法。 同时可以通过删除离决策边界比较远的样例。 (AdaBoost boosting systems dollar fusion algorithm is the most popular one, it plainly systems integration approach is a serial train and final weighted cumulative. Specific process is: Each training example is given equal weight, and the weights satisfy normalization, after the first classifiers after Calculating a first classifier weights alpha value for each sample and updates right weight training, and then the second classifier training, the same way ....... 0, or until the specified error rate training rounds, wherein the label is the calculation of the final prediction system* alpha weighted and then sign (predicted value). As can be seen, the training process is serial, and weight training examples is always changing, the right of the wrong sample weight continued to increase, the right to correct sample weight decreasing. AdaBoost algorithm is an element, as well as other methods of boosting popular systems integration, such as bagging and random forest method. For )
    2014-07-09 19:24:29下载
    积分:1
  • mpc
    说明:  通过建立车辆运动学模型,使用MPC算法模拟仿真导引车辆达到指定点(Through the establishment of vehicle kinematics model, the MPC algorithm is used to simulate and guide the vehicle to the designated point.)
    2019-05-28 15:59:25下载
    积分:1
  • 1DCNN_Classifier-master
    说明:  tensorflow框架下利用一维卷积神经网络对一维数据的分类(Classification of one dimensional convolution neural network)
    2020-12-05 18:39:23下载
    积分:1
  • Non-linear-FEA
    Non-linear Finite Element Analysis of Solids and Structures英文原版和代码,介绍非线性有限元的方法和技巧。(Non-linear Finite Element Analysis of Solids and Structures English original and code, about the methods and techniques of nonlinear finite element.)
    2014-12-16 10:25:15下载
    积分:1
  • AES-GCM-Python-master
    说明:  gcm python算法 包含aes128 狂欢,(GCM Python algorithm includes AES 128 carnival,)
    2020-11-13 10:06:11下载
    积分:1
  • Deep Learning with Python中英版(含代码)
    说明:  深度学习四大名著:Deep Learning with Python 英文版,中文版,Python源码(Four Masterpieces on deep learning : Deep learning with Python English version,Chinese version, python source code)
    2021-04-16 12:00:42下载
    积分:1
  • 696516资源总数
  • 106457会员总数
  • 15今日下载