


Randomly generate verification codes using addition and subtraction algorithms
This time I will bring you a verification code that randomly generates a verification code using the addition and subtraction algorithm. What are the precautions for randomly generating the verification code using the addition and subtraction algorithm. The following is a practical case, let’s take a look.
This is a demo I found online, and I added part of the code. can use.
It needs to be explained here that when we call this verification code class, it should be used in a separate controller method.
The algorithm of the generated image is generated by code, and then the calculated value is stored in the session.
When verifying, the user’s input value is obtained, and then the value on the server is taken out for comparison.
<?php namespace mobile\components; /** * @author fenghuo * * 改造的加减法验证类 * 使用示例 VerifyCode::get(1,2); * 验证示例 VerifyCode::check($code); */ class VerifyCode { /** * php验证码 */ public static function get($one,$two,$prefix = '', $font_size = 28) { //文件头... ob_get_clean(); header("Content-type: image/png;charset=utf-8;"); //创建真彩色白纸 $width = $font_size*5; $height = $font_size+1; $im = @imagecreatetruecolor($width, $height) or die("建立图像失败"); //获取背景颜色 $background_color = imagecolorallocate($im, 255, 255, 255); //填充背景颜色 imagefill($im, 0, 0, $background_color); //获取边框颜色 $border_color = imagecolorallocate($im, 200, 200, 200); //画矩形,边框颜色200,200,200 imagerectangle($im,0,0,$width - 1, $height - 1,$border_color); //逐行炫耀背景,全屏用1或0 for($i = 2;$i < $height - 2;$i++) { //获取随机淡色 $line_color = imagecolorallocate($im, rand(200,255), rand(200,255), rand(200,255)); //画线 imageline($im, 2, $i, $width - 1, $i, $line_color); } //设置印上去的文字 $firstNum = $one; $secondNum = $two; $actionStr = $firstNum > $secondNum ? '-' : '+'; //获取第1个随机文字 $imstr[0]["s"] = $firstNum; $imstr[0]["x"] = rand(2, 5); $imstr[0]["y"] = rand(1, 4); //获取第2个随机文字 $imstr[1]["s"] = $actionStr; $imstr[1]["x"] = $imstr[0]["x"] + $font_size - 1 + rand(0, 1); $imstr[1]["y"] = rand(1,5); //获取第3个随机文字 $imstr[2]["s"] = $secondNum; $imstr[2]["x"] = $imstr[1]["x"] + $font_size - 1 + rand(0, 1); $imstr[2]["y"] = rand(1, 5); //获取第3个随机文字 $imstr[3]["s"] = '='; $imstr[3]["x"] = $imstr[2]["x"] + $font_size - 1 + rand(0, 1); $imstr[3]["y"] = 3; //获取第3个随机文字 $imstr[4]["s"] = '?'; $imstr[4]["x"] = $imstr[3]["x"] + $font_size - 1 + rand(0, 1); $imstr[4]["y"] = 3; //文字 $text = ''; //写入随机字串 for($i = 0; $i < 5; $i++) { //获取随机较深颜色 $text_color = imagecolorallocate($im, rand(50, 180), rand(50, 180), rand(50, 180)); $text .= $imstr[$i]["s"]; //画文字 imagechar($im, $font_size, $imstr[$i]["x"], $imstr[$i]["y"], $imstr[$i]["s"], $text_color); } session_start(); $_SESSION[$prefix.'verifycode'] = $firstNum > $secondNum ? ($firstNum - $secondNum) : ($firstNum + $secondNum); //显示图片 ImagePng($im); //销毁图片 ImageDestroy($im); } public static function check($code) { if(trim($_SESSION[$prefix.'verifycode']) == trim($code)) { return true; } else { return false; } } }
I believe you have mastered the method after reading the case in this article, and there will be more exciting things. Please pay attention to other related articles on php Chinese website!
Recommended reading:
How to operate format files in php
##Data crawling of Tmall and Taobao products
The above is the detailed content of Randomly generate verification codes using addition and subtraction algorithms. For more information, please follow other related articles on the PHP Chinese website!

Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

AI Hentai Generator
Generate AI Hentai for free.

Hot Article

Hot Tools

Notepad++7.3.1
Easy-to-use and free code editor

SublimeText3 Chinese version
Chinese version, very easy to use

Zend Studio 13.0.1
Powerful PHP integrated development environment

Dreamweaver CS6
Visual web development tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)

Hot Topics



Written above & the author’s personal understanding: At present, in the entire autonomous driving system, the perception module plays a vital role. The autonomous vehicle driving on the road can only obtain accurate perception results through the perception module. The downstream regulation and control module in the autonomous driving system makes timely and correct judgments and behavioral decisions. Currently, cars with autonomous driving functions are usually equipped with a variety of data information sensors including surround-view camera sensors, lidar sensors, and millimeter-wave radar sensors to collect information in different modalities to achieve accurate perception tasks. The BEV perception algorithm based on pure vision is favored by the industry because of its low hardware cost and easy deployment, and its output results can be easily applied to various downstream tasks.

Common challenges faced by machine learning algorithms in C++ include memory management, multi-threading, performance optimization, and maintainability. Solutions include using smart pointers, modern threading libraries, SIMD instructions and third-party libraries, as well as following coding style guidelines and using automation tools. Practical cases show how to use the Eigen library to implement linear regression algorithms, effectively manage memory and use high-performance matrix operations.

The bottom layer of the C++sort function uses merge sort, its complexity is O(nlogn), and provides different sorting algorithm choices, including quick sort, heap sort and stable sort.

The convergence of artificial intelligence (AI) and law enforcement opens up new possibilities for crime prevention and detection. The predictive capabilities of artificial intelligence are widely used in systems such as CrimeGPT (Crime Prediction Technology) to predict criminal activities. This article explores the potential of artificial intelligence in crime prediction, its current applications, the challenges it faces, and the possible ethical implications of the technology. Artificial Intelligence and Crime Prediction: The Basics CrimeGPT uses machine learning algorithms to analyze large data sets, identifying patterns that can predict where and when crimes are likely to occur. These data sets include historical crime statistics, demographic information, economic indicators, weather patterns, and more. By identifying trends that human analysts might miss, artificial intelligence can empower law enforcement agencies

01 Outlook Summary Currently, it is difficult to achieve an appropriate balance between detection efficiency and detection results. We have developed an enhanced YOLOv5 algorithm for target detection in high-resolution optical remote sensing images, using multi-layer feature pyramids, multi-detection head strategies and hybrid attention modules to improve the effect of the target detection network in optical remote sensing images. According to the SIMD data set, the mAP of the new algorithm is 2.2% better than YOLOv5 and 8.48% better than YOLOX, achieving a better balance between detection results and speed. 02 Background & Motivation With the rapid development of remote sensing technology, high-resolution optical remote sensing images have been used to describe many objects on the earth’s surface, including aircraft, cars, buildings, etc. Object detection in the interpretation of remote sensing images

1. Background of the Construction of 58 Portraits Platform First of all, I would like to share with you the background of the construction of the 58 Portrait Platform. 1. The traditional thinking of the traditional profiling platform is no longer enough. Building a user profiling platform relies on data warehouse modeling capabilities to integrate data from multiple business lines to build accurate user portraits; it also requires data mining to understand user behavior, interests and needs, and provide algorithms. side capabilities; finally, it also needs to have data platform capabilities to efficiently store, query and share user profile data and provide profile services. The main difference between a self-built business profiling platform and a middle-office profiling platform is that the self-built profiling platform serves a single business line and can be customized on demand; the mid-office platform serves multiple business lines, has complex modeling, and provides more general capabilities. 2.58 User portraits of the background of Zhongtai portrait construction

Written above & The author’s personal understanding is that in the autonomous driving system, the perception task is a crucial component of the entire autonomous driving system. The main goal of the perception task is to enable autonomous vehicles to understand and perceive surrounding environmental elements, such as vehicles driving on the road, pedestrians on the roadside, obstacles encountered during driving, traffic signs on the road, etc., thereby helping downstream modules Make correct and reasonable decisions and actions. A vehicle with self-driving capabilities is usually equipped with different types of information collection sensors, such as surround-view camera sensors, lidar sensors, millimeter-wave radar sensors, etc., to ensure that the self-driving vehicle can accurately perceive and understand surrounding environment elements. , enabling autonomous vehicles to make correct decisions during autonomous driving. Head

Author | Reviewed by Wang Hao | Chonglou News App is an important way for people to obtain information sources in their daily lives. Around 2010, popular foreign news apps included Zite and Flipboard, while popular domestic news apps were mainly the four major portals. With the popularity of new era news recommendation products represented by Toutiao, news apps have entered a new era. As for technology companies, no matter which one they are, as long as they master the sophisticated news recommendation algorithm technology, they will basically have the initiative and voice at the technical level. Today, let’s take a look at a RecSys2023 Best Long Paper Nomination Award paper—GoingBeyondLocal:GlobalGraph-EnhancedP
