【JS】前端常规(sao)操作之:我用opencvjs识别爬取的乐谱图片二维码位置并覆盖

【JS】前端常规(sao)操作之:我用opencvjs识别爬取的乐谱图片二维码位置并覆盖

【JS】前端常规(sao)操作之:我用opencvjs识别爬取的乐谱图片二维码位置并覆盖

没办法,搞吧!!!!!!

爬数据

分析小程序接口

首先安利一个好用的ios系统免费抓包软件: stream

【JS】前端常规(sao)操作之:我用opencvjs识别爬取的乐谱图片二维码位置并覆盖

【JS】前端常规(sao)操作之:我用opencvjs识别爬取的乐谱图片二维码位置并覆盖

【JS】前端常规(sao)操作之:我用opencvjs识别爬取的乐谱图片二维码位置并覆盖

【JS】前端常规(sao)操作之:我用opencvjs识别爬取的乐谱图片二维码位置并覆盖

【JS】前端常规(sao)操作之:我用opencvjs识别爬取的乐谱图片二维码位置并覆盖

通过分析目标小程序接口发现,有一个接口可以获取单个详情,并且发现每个乐谱的id是自增的,,啧啧!这就好说了啊

上代码

const shell = require('shelljs')

const fs = require('fs')

const getDetil = (id) => {

// 获取curl

let curl = `curl 'https://api.quxuege.com/search/one?id=${id}' -H 'Host: api.quxuege.com' -H 'Accept: */*' -H 'Content-Type: application/x-www-form-urlencoded' -H 'Accept-Encoding: gzip, deflate, br' -H 'Connection: keep-alive' -H 'Cookie: ' -H 'User-Agent: Mozilla/5.0 (iPhone; CPU iPhone OS 14_0 like Mac OS X) AppleWebKit/605.1.15 (KHTML, like Gecko) Mobile/15E148 MicroMessenger/7.0.15(0x17000f31) NetType/WIFI Language/zh_CN' -H 'Referer: https://servicewechat.com/wx21c9c829a9ecfc04/8/page-frame.html' -H 'token: ' -H 'Accept-Language: zh-cn'`

const res = JSON.parse(shell.exec(curl).stdout)

if (res.code === 200) {

const p = res.data

if (p && p.id) {

let t = [p.id, p.title, p.createTime, p.details[0].image]

fs.appendFileSync('sopu.txt', `${t.join(',')}\n`)

}

}

}

for (let i = 101042; i < 199999; i++) {

getDetil(i)

}

id爬到20万左右就没有了,总共爬了9万条数据

【JS】前端常规(sao)操作之:我用opencvjs识别爬取的乐谱图片二维码位置并覆盖

分析数据

【JS】前端常规(sao)操作之:我用opencvjs识别爬取的乐谱图片二维码位置并覆盖

【JS】前端常规(sao)操作之:我用opencvjs识别爬取的乐谱图片二维码位置并覆盖

这样就不能搞一个脚本去固定贴二维码了,!!!

opencvjs识别二维码

引入opencvjs

<script async onload="onOpenCvReady();" type="text/javascript"></script>

<!DOCTYPE html>

<html>

<head>

<meta charset="utf-8">

<title>Hello OpenCV.js</title>

<script async onload="onOpenCvReady();" type="text/javascript"></script>

</head>

<body>

<h2>Hello OpenCV.js</h2>

<p id="status">OpenCV.js is loading...</p>

<div>

<div class="inputoutput">

<img id="imageSrc" alt="No Image" />

<div class="caption">imageSrc <input type="file" id="fileInput" name="file" /></div>

</div>

<div class="inputoutput">

<canvas id="canvasOutput"></canvas>

<div class="caption">canvasOutput</div>

</div>

<div class="inputoutput2">

<canvas id="canvasOutput2"></canvas>

<div class="caption">canvasOutput2</div>

</div>

</div>

<script type="text/javascript">

let imgElement = document.getElementById('imageSrc');

let inputElement = document.getElementById('fileInput');

inputElement.addEventListener('change', (e) => {

imgElement.src = URL.createObjectURL(e.target.files[0]);

}, false);

imgElement.onload = function (e) {

console.log(imgElement);

let src = cv.imread(imgElement);

let src_clone = cv.imread(imgElement);

let dsize = new cv.Size(800, 1000);

// You can try more different parameters

cv.resize(src, src, dsize); cv.resize(src_clone, src_clone, dsize);

let dst = cv.Mat.zeros(src.rows, src.cols, cv.CV_8UC3);

cv.cvtColor(src, src, cv.COLOR_RGBA2GRAY, 0);

let ksize = new cv.Size(1, 1);

// You can try more different parameters

cv.blur(src, src, ksize);

cv.threshold(src, src, 0, 255, cv.THRESH_OTSU);

let contours = new cv.MatVector();

let contours2 = new cv.MatVector();

let hierarchy = new cv.Mat();

// You can try more different parameters

cv.findContours(src, contours, hierarchy, cv.RETR_TREE, cv.CHAIN_APPROX_NONE);

//轮廓筛选

let c = 0, ic = 0, area = 0;

let parentIdx = -1;

for (let i = 0; i < contours.size(); i++) {

//let hier = hierarchy.intPtr(0, i)

// console.log(hierarchy.intPtr(0, i))

if (hierarchy.intPtr(0, i)[2] != -1 && ic == 0) {

parentIdx = i;

ic++;

}

else if (hierarchy.intPtr(0, i)[2] != -1) {

console.log(hierarchy.intPtr(0, i))

ic++;

}

else if (hierarchy.intPtr(0, i)[2] == -1) {

ic = 0;

parentIdx = -1;

}

// if (ic == 2) {

// console.log(parentIdx, i)

// }

//找到定位点信息

if (ic == 2) {

//let cnt = matVec.get(0);

contours2.push_back(contours.get(parentIdx));

ic = 0;

parentIdx = -1;

}

}

console.log(contours2.size());

//填充定位点

for (let i = 0; i < contours.size(); i++) {

let color = new cv.Scalar(255, 0, 0, 255);

cv.drawContours(src_clone, contours, i, color, 1);

}

cv.imshow('canvasOutput', src_clone);

for (let i = 0; i < contours2.size(); i++) {

let color = new cv.Scalar(Math.round(Math.random() * 255), Math.round(Math.random() * 255),

Math.round(Math.random() * 255));

console.log(contours2)

cv.drawContours(dst, contours2, i, color, 1);

}

cv.imshow('canvasOutput2', dst);

src.delete(); src_clone.delete();

dst.delete(); contours.delete(); hierarchy.delete();

};

function onOpenCvReady() {

document.getElementById('status').innerHTML = 'OpenCV.js is ready.';

}

</script>

</body>

</html>

启动

【JS】前端常规(sao)操作之:我用opencvjs识别爬取的乐谱图片二维码位置并覆盖

选择一个乐谱上传

【JS】前端常规(sao)操作之:我用opencvjs识别爬取的乐谱图片二维码位置并覆盖

看到三个回型。说明识别成功

接下来就是下载图片。定位位置。用canvas贴上我们二维码。入库~

好啦~,产品经理的需求就这么愉快的搞定了!

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