Home Backend Development PHP Tutorial 聊天室技术(五) -- 指挥中心_PHP

聊天室技术(五) -- 指挥中心_PHP

Jun 01, 2016 pm 12:34 PM
gt lt name center technology command chatroom

这里是聊天室的指挥中心,所有的指令都要在这里发出

 

1下面是基本的发送表单代码

//下面的2个参数用于验证信息的正确性
print("n");
print("n");
?>

//聊天对象,注意加上 readonly 属性

//上次聊天的发送内容

//发送的表单文本框

2 检查发送内容的js

var dx ='';
function checksay( )
{

//不允许发送空的发言
if(document.inputform.msg.value=='')
{
document.inputform.msg.focus();
return false;
}

//不允许重复发言,内容相同,对象相同
if ((document.inputform.msg.value==document.inputform.message.value)&&(document.inputform.talkto.value==dx))
{
alert('发言不能重复');
document.inputform.msg.focus();
return false;
}

//两次发言内容的间隔不能小于1秒,或者发言字数大于间隔*3
t2=(new Date()).getTime()/1000;
if(((t2-t1)<1)||((t2-t1)*3{
document.inputform.msg.focus();
return false;
}

//更新时间
t1=t2;

document.inputform.showsign.value=1;

//保存上次发言内容
document.inputform.message.value =document.inputform.msg.value;

//清空发言内容
document.inputform.msg.value ='';

//保存发言对象
dx=document.inputform.talkto.value;

//定位焦点
document.inputform.msg.focus();

//返回
return(true);
}

3调用信息发送程序,发布聊天者已经进入的信息
<script> <br>parent.bl.document.open(); <br>parent.bl.document.write("<meta http-equiv='refresh' content='0;url=messagesend.php?name=<? print($name); ?>&&action=enter&&pass=<? print($pass); ?>'>") <br>parent.bl.document.close(); <br></script>

发言由messagesend.php处理完成,注意输出对象为bl,也就是处理发言的框架名称,这样保证发言框架的页面内容的完整

原作者:howtodo
来源:php2000.com

Statement of this Website
The content of this article is voluntarily contributed by netizens, and the copyright belongs to the original author. This site does not assume corresponding legal responsibility. If you find any content suspected of plagiarism or infringement, please contact admin@php.cn

Hot AI Tools

Undresser.AI Undress

Undresser.AI Undress

AI-powered app for creating realistic nude photos

AI Clothes Remover

AI Clothes Remover

Online AI tool for removing clothes from photos.

Undress AI Tool

Undress AI Tool

Undress images for free

Clothoff.io

Clothoff.io

AI clothes remover

Video Face Swap

Video Face Swap

Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Article

Roblox: Bubble Gum Simulator Infinity - How To Get And Use Royal Keys
3 weeks ago By 尊渡假赌尊渡假赌尊渡假赌
Nordhold: Fusion System, Explained
3 weeks ago By 尊渡假赌尊渡假赌尊渡假赌
Mandragora: Whispers Of The Witch Tree - How To Unlock The Grappling Hook
3 weeks ago By 尊渡假赌尊渡假赌尊渡假赌

Hot Tools

Notepad++7.3.1

Notepad++7.3.1

Easy-to-use and free code editor

SublimeText3 Chinese version

SublimeText3 Chinese version

Chinese version, very easy to use

Zend Studio 13.0.1

Zend Studio 13.0.1

Powerful PHP integrated development environment

Dreamweaver CS6

Dreamweaver CS6

Visual web development tools

SublimeText3 Mac version

SublimeText3 Mac version

God-level code editing software (SublimeText3)

Hot Topics

Java Tutorial
1665
14
PHP Tutorial
1269
29
C# Tutorial
1249
24
What are the differences between Huawei GT3 Pro and GT4? What are the differences between Huawei GT3 Pro and GT4? Dec 29, 2023 pm 02:27 PM

Many users will choose the Huawei brand when choosing smart watches. Among them, Huawei GT3pro and GT4 are very popular choices. Many users are curious about the difference between Huawei GT3pro and GT4. Let’s introduce the two to you. . What are the differences between Huawei GT3pro and GT4? 1. Appearance GT4: 46mm and 41mm, the material is glass mirror + stainless steel body + high-resolution fiber back shell. GT3pro: 46.6mm and 42.9mm, the material is sapphire glass + titanium body/ceramic body + ceramic back shell 2. Healthy GT4: Using the latest Huawei Truseen5.5+ algorithm, the results will be more accurate. GT3pro: Added ECG electrocardiogram and blood vessel and safety

The Stable Diffusion 3 paper is finally released, and the architectural details are revealed. Will it help to reproduce Sora? The Stable Diffusion 3 paper is finally released, and the architectural details are revealed. Will it help to reproduce Sora? Mar 06, 2024 pm 05:34 PM

StableDiffusion3’s paper is finally here! This model was released two weeks ago and uses the same DiT (DiffusionTransformer) architecture as Sora. It caused quite a stir once it was released. Compared with the previous version, the quality of the images generated by StableDiffusion3 has been significantly improved. It now supports multi-theme prompts, and the text writing effect has also been improved, and garbled characters no longer appear. StabilityAI pointed out that StableDiffusion3 is a series of models with parameter sizes ranging from 800M to 8B. This parameter range means that the model can be run directly on many portable devices, significantly reducing the use of AI

Have you really mastered coordinate system conversion? Multi-sensor issues that are inseparable from autonomous driving Have you really mastered coordinate system conversion? Multi-sensor issues that are inseparable from autonomous driving Oct 12, 2023 am 11:21 AM

The first pilot and key article mainly introduces several commonly used coordinate systems in autonomous driving technology, and how to complete the correlation and conversion between them, and finally build a unified environment model. The focus here is to understand the conversion from vehicle to camera rigid body (external parameters), camera to image conversion (internal parameters), and image to pixel unit conversion. The conversion from 3D to 2D will have corresponding distortion, translation, etc. Key points: The vehicle coordinate system and the camera body coordinate system need to be rewritten: the plane coordinate system and the pixel coordinate system. Difficulty: image distortion must be considered. Both de-distortion and distortion addition are compensated on the image plane. 2. Introduction There are four vision systems in total. Coordinate system: pixel plane coordinate system (u, v), image coordinate system (x, y), camera coordinate system () and world coordinate system (). There is a relationship between each coordinate system,

DualBEV: significantly surpassing BEVFormer and BEVDet4D, open the book! DualBEV: significantly surpassing BEVFormer and BEVDet4D, open the book! Mar 21, 2024 pm 05:21 PM

This paper explores the problem of accurately detecting objects from different viewing angles (such as perspective and bird's-eye view) in autonomous driving, especially how to effectively transform features from perspective (PV) to bird's-eye view (BEV) space. Transformation is implemented via the Visual Transformation (VT) module. Existing methods are broadly divided into two strategies: 2D to 3D and 3D to 2D conversion. 2D-to-3D methods improve dense 2D features by predicting depth probabilities, but the inherent uncertainty of depth predictions, especially in distant regions, may introduce inaccuracies. While 3D to 2D methods usually use 3D queries to sample 2D features and learn the attention weights of the correspondence between 3D and 2D features through a Transformer, which increases the computational and deployment time.

This article is enough for you to read about autonomous driving and trajectory prediction! This article is enough for you to read about autonomous driving and trajectory prediction! Feb 28, 2024 pm 07:20 PM

Trajectory prediction plays an important role in autonomous driving. Autonomous driving trajectory prediction refers to predicting the future driving trajectory of the vehicle by analyzing various data during the vehicle's driving process. As the core module of autonomous driving, the quality of trajectory prediction is crucial to downstream planning control. The trajectory prediction task has a rich technology stack and requires familiarity with autonomous driving dynamic/static perception, high-precision maps, lane lines, neural network architecture (CNN&GNN&Transformer) skills, etc. It is very difficult to get started! Many fans hope to get started with trajectory prediction as soon as possible and avoid pitfalls. Today I will take stock of some common problems and introductory learning methods for trajectory prediction! Introductory related knowledge 1. Are the preview papers in order? A: Look at the survey first, p

GSLAM | A general SLAM architecture and benchmark GSLAM | A general SLAM architecture and benchmark Oct 20, 2023 am 11:37 AM

Suddenly discovered a 19-year-old paper GSLAM: A General SLAM Framework and Benchmark open source code: https://github.com/zdzhaoyong/GSLAM Go directly to the full text and feel the quality of this work ~ 1 Abstract SLAM technology has achieved many successes recently and attracted many attracted the attention of high-tech companies. However, how to effectively perform benchmarks on speed, robustness, and portability with interfaces to existing or emerging algorithms remains a problem. In this paper, a new SLAM platform called GSLAM is proposed, which not only provides evaluation capabilities but also provides researchers with a useful way to quickly develop their own SLAM systems.

The first multi-view autonomous driving scene video generation world model | DrivingDiffusion: New ideas for BEV data and simulation The first multi-view autonomous driving scene video generation world model | DrivingDiffusion: New ideas for BEV data and simulation Oct 23, 2023 am 11:13 AM

Some of the author’s personal thoughts In the field of autonomous driving, with the development of BEV-based sub-tasks/end-to-end solutions, high-quality multi-view training data and corresponding simulation scene construction have become increasingly important. In response to the pain points of current tasks, "high quality" can be decoupled into three aspects: long-tail scenarios in different dimensions: such as close-range vehicles in obstacle data and precise heading angles during car cutting, as well as lane line data. Scenes such as curves with different curvatures or ramps/mergings/mergings that are difficult to capture. These often rely on large amounts of data collection and complex data mining strategies, which are costly. 3D true value - highly consistent image: Current BEV data acquisition is often affected by errors in sensor installation/calibration, high-precision maps and the reconstruction algorithm itself. this led me to

How to develop Websocket chat room using Go language How to develop Websocket chat room using Go language Dec 14, 2023 pm 01:46 PM

How to use Go language to develop a Websocket chat room. Websocket is a real-time communication protocol that allows two-way communication between the server and the client by establishing a connection. Websocket is a very good choice when developing chat rooms because it enables real-time message exchange and provides efficient performance. This article will introduce how to develop a simple Websocket chat room using Go language and provide some specific code examples. 1. Preparation 1. Install Go

See all articles