503 lines
20 KiB
JavaScript
503 lines
20 KiB
JavaScript
//
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// Shinobi - OpenCV Plugin
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// Copyright (C) 2016-2025 Moe Alam, moeiscool
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//
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// # Donate
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//
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// If you like what I am doing here and want me to continue please consider donating :)
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// PayPal : paypal@m03.ca
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//
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process.on('uncaughtException', function (err) {
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console.error('uncaughtException',err);
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});
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var fs=require('fs');
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var cv=require('opencv4nodejs');
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var exec = require('child_process').exec;
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var moment = require('moment');
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var Canvas = require('canvas');
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var express = require('express');
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const path = require('path');
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var http = require('http'),
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app = express(),
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server = http.createServer(app);
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var config=require('./conf.json');
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if(!config.port){config.port=8080}
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if(!config.hostPort){config.hostPort=8082}
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if(config.systemLog===undefined){config.systemLog=true}
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if(config.cascadesDir===undefined){config.cascadesDir=__dirname+'/cascades/'}
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if(config.alprConfig===undefined){config.alprConfig=__dirname+'/openalpr.conf'}
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s={
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group:{},
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dir:{
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cascades : config.cascadesDir
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},
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isWin:(process.platform==='win32'),
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foundCascades : {
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}
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}
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//default stream folder check
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if(!config.streamDir){
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if(s.isWin===false){
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config.streamDir='/dev/shm'
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}else{
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config.streamDir=config.windowsTempDir
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}
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if(!fs.existsSync(config.streamDir)){
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config.streamDir=__dirname+'/streams/'
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}else{
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config.streamDir+='/streams/'
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}
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}
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s.dir.streams=config.streamDir;
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//streams dir
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if(!fs.existsSync(s.dir.streams)){
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fs.mkdirSync(s.dir.streams);
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}
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//streams dir
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if(!fs.existsSync(s.dir.cascades)){
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fs.mkdirSync(s.dir.cascades);
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}
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s.gid=function(x){
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if(!x){x=10};var t = "";var p = "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789";
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for( var i=0; i < x; i++ )
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t += p.charAt(Math.floor(Math.random() * p.length));
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return t;
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};
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s.findCascades=function(callback){
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var tmp={};
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tmp.foundCascades=[];
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fs.readdir(s.dir.cascades,function(err,files){
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files.forEach(function(cascade,n){
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if(cascade.indexOf('.xml')>-1){
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tmp.foundCascades.push(cascade.replace('.xml',''))
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}
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})
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s.cascadesInDir=tmp.foundCascades;
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callback(tmp.foundCascades)
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})
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}
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s.findCascades(function(){
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//get cascades
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})
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s.detectLicensePlate=function(buffer,d,tx){
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if(!d.mon.detector_lisence_plate_country||d.mon.detector_lisence_plate_country===''){
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d.mon.detector_lisence_plate_country='us'
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}
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d.tmpFile=s.gid(5)+'.jpg'
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if(!fs.existsSync(s.dir.streams)){
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fs.mkdirSync(s.dir.streams);
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}
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d.dir=s.dir.streams+d.ke+'/'
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if(!fs.existsSync(d.dir)){
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fs.mkdirSync(d.dir);
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}
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d.dir=s.dir.streams+d.ke+'/'+d.id+'/'
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if(!fs.existsSync(d.dir)){
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fs.mkdirSync(d.dir);
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}
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fs.writeFile(d.dir+d.tmpFile,buffer,function(err){
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if(err) return s.systemLog(err);
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exec('alpr -j --config '+config.alprConfig+' -c '+d.mon.detector_lisence_plate_country+' '+d.dir+d.tmpFile,{encoding:'utf8'},(err, scan, stderr) => {
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if(err){
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s.systemLog(err);
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}else{
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try{
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scan=JSON.parse(scan.replace('--(!)Loaded CUDA classifier','').trim())
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}catch(err){
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if(!scan||!scan.results){
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return s.systemLog(scan,err);
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}
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}
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if(scan.results.length>0){
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scan.plates=[]
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scan.mats=[]
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scan.results.forEach(function(v){
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v.candidates.forEach(function(g,n){
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if(v.candidates[n].matches_template)
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delete(v.candidates[n].matches_template)
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})
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scan.plates.push({coordinates:v.coordinates,candidates:v.candidates,confidence:v.confidence,plate:v.plate})
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var width = Math.sqrt( Math.pow(v.coordinates[1].x - v.coordinates[0].x, 2) + Math.pow(v.coordinates[1].y - v.coordinates[0].y, 2));
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var height = Math.sqrt( Math.pow(v.coordinates[2].x - v.coordinates[1].x, 2) + Math.pow(v.coordinates[2].y - v.coordinates[1].y, 2))
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scan.mats.push({
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x:v.coordinates[0].x,
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y:v.coordinates[0].y,
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width:width,
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height:height,
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tag:v.plate
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})
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})
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tx({f:'trigger',id:d.id,ke:d.ke,details:{split:true,plug:config.plug,name:'licensePlate',reason:'object',matrices:scan.mats,imgHeight:d.mon.detector_scale_y,imgWidth:d.mon.detector_scale_x,frame:d.base64}})
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}
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}
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exec('rm -rf '+d.dir+d.tmpFile,{encoding:'utf8'})
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})
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})
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}
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s.detectObject=function(buffer,d,tx){
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//detect license plate?
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if(d.mon.detector_lisence_plate==="1"){
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s.detectLicensePlate(buffer,d,tx)
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}
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cv.imdecodeAsync(buffer,(err,im) => {
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if(err){
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console.log(err)
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return
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}
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if (!cv.xmodules.dnn) {
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throw new Error('exiting: opencv4nodejs compiled without dnn module');
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}
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// replace with path where you unzipped inception model
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const inceptionModelPath = __dirname+'/data/inception';
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const modelFile = path.resolve(inceptionModelPath, 'tensorflow_inception_graph.pb');
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const classNamesFile = path.resolve(inceptionModelPath, 'imagenet_comp_graph_label_strings.txt');
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if (!fs.existsSync(modelFile) || !fs.existsSync(classNamesFile)) {
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console.log('could not find inception model');
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console.log('download the model from: https://cdn.shinobi.video/weights/inception5h.zip');
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throw new Error('exiting');
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}
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// read classNames and store them in an array
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const classNames = fs.readFileSync(classNamesFile).toString().split('\n');
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// initialize tensorflow inception model from modelFile
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const net = cv.readNetFromTensorflow(modelFile);
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// inception model works with 224 x 224 images, so we resize
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// our input images and pad the image with white pixels to
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// make the images have the same width and height
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const maxImgDim = 224;
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const white = new cv.Vec(255, 255, 255);
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const imgResized = im.resizeToMax(maxImgDim).padToSquare(white);
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// network accepts blobs as input
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const inputBlob = cv.blobFromImage(imgResized);
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net.setInput(inputBlob);
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// forward pass input through entire network, will return
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// classification result as 1xN Mat with confidences of each class
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const outputBlob = net.forward();
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// find all labels with a minimum confidence
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const minConfidence = 0.05;
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const locations =
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outputBlob
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.threshold(minConfidence, 1, cv.THRESH_BINARY)
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.convertTo(cv.CV_8U)
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.findNonZero();
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// locations.forEach(function(v){
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// console.log(v)
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// })
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const result =
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locations.map(pt => ({
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confidence: parseInt(outputBlob.at(0, pt.x) * 100) / 100,
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className: classNames[pt.x]
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}))
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// sort result by confidence
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.sort((r0, r1) => r1.confidence - r0.confidence)
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.map(res => `${res.className} (${res.confidence})`);
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console.log(result)
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if(result.length > 0) {
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s.cx({
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f:'trigger',
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id:d.id,
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ke:d.ke,
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name:'tensorflow',
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details:{
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plug:'tensorflow',
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name:'tensorflow',
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reason:'object',
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matrices : result
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// confidence:d.average
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},
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imgHeight:d.mon.detector_scale_y,
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imgWidth:d.mon.detector_scale_x
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})
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}
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})
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}
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s.systemLog=function(q,w,e){
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if(!w){w=''}
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if(!e){e=''}
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if(config.systemLog===true){
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return console.log(moment().format(),q,w,e)
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}
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}
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s.blenderRegion=function(d,cord,tx){
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d.width = d.image.width;
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d.height = d.image.height;
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if(!s.group[d.ke][d.id].canvas[cord.name]){
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if(!cord.sensitivity||isNaN(cord.sensitivity)){
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cord.sensitivity=d.mon.detector_sensitivity;
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}
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s.group[d.ke][d.id].canvas[cord.name] = new Canvas(d.width,d.height);
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s.group[d.ke][d.id].canvasContext[cord.name] = s.group[d.ke][d.id].canvas[cord.name].getContext('2d');
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s.group[d.ke][d.id].canvasContext[cord.name].fillStyle = '#000';
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s.group[d.ke][d.id].canvasContext[cord.name].fillRect( 0, 0,d.width,d.height);
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if(cord.points&&cord.points.length>0){
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s.group[d.ke][d.id].canvasContext[cord.name].beginPath();
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for (var b = 0; b < cord.points.length; b++){
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cord.points[b][0]=parseFloat(cord.points[b][0]);
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cord.points[b][1]=parseFloat(cord.points[b][1]);
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if(b===0){
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s.group[d.ke][d.id].canvasContext[cord.name].moveTo(cord.points[b][0],cord.points[b][1]);
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}else{
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s.group[d.ke][d.id].canvasContext[cord.name].lineTo(cord.points[b][0],cord.points[b][1]);
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}
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}
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s.group[d.ke][d.id].canvasContext[cord.name].clip();
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}
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}
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if(!s.group[d.ke][d.id].canvasContext[cord.name]){
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return
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}
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s.group[d.ke][d.id].canvasContext[cord.name].drawImage(d.image, 0, 0, d.width, d.height);
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if(!s.group[d.ke][d.id].blendRegion[cord.name]){
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s.group[d.ke][d.id].blendRegion[cord.name] = new Canvas(d.width, d.height);
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s.group[d.ke][d.id].blendRegionContext[cord.name] = s.group[d.ke][d.id].blendRegion[cord.name].getContext('2d');
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}
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var sourceData = s.group[d.ke][d.id].canvasContext[cord.name].getImageData(0, 0, d.width, d.height);
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// create an image if the previous image doesn<73>t exist
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if (!s.group[d.ke][d.id].lastRegionImageData[cord.name]) s.group[d.ke][d.id].lastRegionImageData[cord.name] = s.group[d.ke][d.id].canvasContext[cord.name].getImageData(0, 0, d.width, d.height);
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// create a ImageData instance to receive the blended result
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var blendedData = s.group[d.ke][d.id].canvasContext[cord.name].createImageData(d.width, d.height);
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// blend the 2 images
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s.differenceAccuracy(blendedData.data,sourceData.data,s.group[d.ke][d.id].lastRegionImageData[cord.name].data);
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// draw the result in a canvas
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s.group[d.ke][d.id].blendRegionContext[cord.name].putImageData(blendedData, 0, 0);
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// store the current webcam image
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s.group[d.ke][d.id].lastRegionImageData[cord.name] = sourceData;
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blendedData = s.group[d.ke][d.id].blendRegionContext[cord.name].getImageData(0, 0, d.width, d.height);
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var i = 0;
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d.average = 0;
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while (i < (blendedData.data.length * 0.25)) {
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d.average += (blendedData.data[i * 4] + blendedData.data[i * 4 + 1] + blendedData.data[i * 4 + 2]);
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++i;
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}
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d.average = (d.average / (blendedData.data.length * 0.25))*10;
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if (d.average > parseFloat(cord.sensitivity)){
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if(d.mon.detector_use_detect_object==="1"&&d.mon.detector_second!=='1'){
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var buffer=s.group[d.ke][d.id].canvas[cord.name].toBuffer();
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s.detectObject(buffer,d,tx)
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}else{
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tx({f:'trigger',id:d.id,ke:d.ke,details:{split:true,plug:config.plug,name:cord.name,reason:'motion',confidence:d.average,frame:d.base64}})
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}
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}
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s.group[d.ke][d.id].canvasContext[cord.name].clearRect(0, 0, d.width, d.height);
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s.group[d.ke][d.id].blendRegionContext[cord.name].clearRect(0, 0, d.width, d.height);
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}
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function blobToBuffer (blob, cb) {
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if (typeof Blob === 'undefined' || !(blob instanceof Blob)) {
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throw new Error('first argument must be a Blob')
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}
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if (typeof cb !== 'function') {
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throw new Error('second argument must be a function')
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}
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var reader = new FileReader()
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function onLoadEnd (e) {
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reader.removeEventListener('loadend', onLoadEnd, false)
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if (e.error) cb(e.error)
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else cb(null, Buffer.from(reader.result))
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}
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reader.addEventListener('loadend', onLoadEnd, false)
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reader.readAsArrayBuffer(blob)
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}
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function fastAbs(value) {
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return (value ^ (value >> 31)) - (value >> 31);
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}
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function threshold(value) {
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return (value > 0x15) ? 0xFF : 0;
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}
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s.differenceAccuracy=function(target, data1, data2) {
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if (data1.length != data2.length) return null;
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var i = 0;
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while (i < (data1.length * 0.25)) {
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var average1 = (data1[4 * i] + data1[4 * i + 1] + data1[4 * i + 2]) / 3;
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var average2 = (data2[4 * i] + data2[4 * i + 1] + data2[4 * i + 2]) / 3;
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var diff = threshold(fastAbs(average1 - average2));
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target[4 * i] = diff;
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target[4 * i + 1] = diff;
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target[4 * i + 2] = diff;
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target[4 * i + 3] = 0xFF;
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++i;
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}
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}
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s.checkAreas=function(d,tx){
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if(!s.group[d.ke][d.id].cords){
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if(!d.mon.cords){d.mon.cords={}}
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s.group[d.ke][d.id].cords=Object.values(d.mon.cords);
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}
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if(d.mon.detector_frame==='1'){
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d.mon.cords.frame={name:'FULL_FRAME',s:d.mon.detector_sensitivity,points:[[0,0],[0,d.image.height],[d.image.width,d.image.height],[d.image.width,0]]};
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s.group[d.ke][d.id].cords.push(d.mon.cords.frame);
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}
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for (var b = 0; b < s.group[d.ke][d.id].cords.length; b++){
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if(!s.group[d.ke][d.id].cords[b]){return}
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s.blenderRegion(d,s.group[d.ke][d.id].cords[b],tx)
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}
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delete(d.image)
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}
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s.MainEventController=function(d,cn,tx){
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switch(d.f){
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case'refreshPlugins':
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s.findCascades(function(cascades){
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s.cx({f:'s.tx',data:{f:'detector_cascade_list',cascades:cascades},to:'GRP_'+d.ke})
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})
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break;
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case'readPlugins':
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s.cx({f:'s.tx',data:{f:'detector_cascade_list',cascades:s.cascadesInDir},to:'GRP_'+d.ke})
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break;
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case'init_plugin_as_host':
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if(!cn){
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console.log('No CN',d)
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return
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}
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if(d.key!==config.key){
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console.log(new Date(),'Plugin Key Mismatch',cn.request.connection.remoteAddress,d)
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cn.emit('init',{ok:false})
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cn.disconnect()
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}else{
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console.log(new Date(),'Plugin Connected to Client',cn.request.connection.remoteAddress)
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cn.emit('init',{ok:true,plug:config.plug,notice:config.notice,type:config.type})
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}
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break;
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case'init_monitor':
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if(s.group[d.ke]&&s.group[d.ke][d.id]){
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s.group[d.ke][d.id].canvas={}
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s.group[d.ke][d.id].canvasContext={}
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s.group[d.ke][d.id].blendRegion={}
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s.group[d.ke][d.id].blendRegionContext={}
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s.group[d.ke][d.id].lastRegionImageData={}
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s.group[d.ke][d.id].numberOfTriggers=0
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delete(s.group[d.ke][d.id].cords)
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delete(s.group[d.ke][d.id].buffer)
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}
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break;
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case'init_aws_push':
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// console.log('init_aws')
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s.group[d.ke][d.id].aws={links:[],complete:0,total:d.total,videos:[],tx:tx}
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break;
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case'frame':
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try{
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if(!s.group[d.ke]){
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s.group[d.ke]={}
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}
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if(!s.group[d.ke][d.id]){
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s.group[d.ke][d.id]={
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canvas:{},
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canvasContext:{},
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lastRegionImageData:{},
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blendRegion:{},
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blendRegionContext:{},
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}
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}
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if(!s.group[d.ke][d.id].buffer){
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s.group[d.ke][d.id].buffer=[d.frame];
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}else{
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s.group[d.ke][d.id].buffer.push(d.frame)
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}
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if(d.frame[d.frame.length-2] === 0xFF && d.frame[d.frame.length-1] === 0xD9){
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s.group[d.ke][d.id].buffer=Buffer.concat(s.group[d.ke][d.id].buffer);
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try{
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d.mon.detector_cascades=JSON.parse(d.mon.detector_cascades)
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}catch(err){
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}
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if(d.mon.detector_frame_save==="1"){
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d.base64=s.group[d.ke][d.id].buffer.toString('base64')
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}
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if(d.mon.detector_second==='1'&&d.objectOnly===true){
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s.detectObject(s.group[d.ke][d.id].buffer,d,tx)
|
||
}else{
|
||
if((d.mon.detector_pam !== '1' && d.mon.detector_use_motion === "1") || d.mon.detector_use_detect_object !== "1"){
|
||
if((typeof d.mon.cords ==='string')&&d.mon.cords.trim()===''){
|
||
d.mon.cords=[]
|
||
}else{
|
||
try{
|
||
d.mon.cords=JSON.parse(d.mon.cords)
|
||
}catch(err){
|
||
// console.log('d.mon.cords',err,d)
|
||
}
|
||
}
|
||
s.group[d.ke][d.id].cords=Object.values(d.mon.cords);
|
||
d.mon.cords=d.mon.cords;
|
||
d.image = new Canvas.Image;
|
||
if(d.mon.detector_scale_x===''||d.mon.detector_scale_y===''){
|
||
s.systemLog('Must set detector image size')
|
||
return
|
||
}else{
|
||
d.image.width=d.mon.detector_scale_x;
|
||
d.image.height=d.mon.detector_scale_y;
|
||
}
|
||
d.width=d.image.width;
|
||
d.height=d.image.height;
|
||
d.image.onload = function() {
|
||
s.checkAreas(d,tx);
|
||
}
|
||
d.image.src = s.group[d.ke][d.id].buffer;
|
||
}else{
|
||
s.detectObject(s.group[d.ke][d.id].buffer,d,tx)
|
||
}
|
||
}
|
||
s.group[d.ke][d.id].buffer=null;
|
||
}
|
||
}catch(err){
|
||
if(err){
|
||
s.systemLog(err)
|
||
delete(s.group[d.ke][d.id].buffer)
|
||
}
|
||
}
|
||
break;
|
||
}
|
||
}
|
||
server.listen(config.hostPort);
|
||
//web pages and plugin api
|
||
app.get('/', function (req, res) {
|
||
res.end('<b>'+config.plug+'</b> for Shinobi is running')
|
||
});
|
||
//Conector to Shinobi
|
||
if(config.mode==='host'){
|
||
//start plugin as host
|
||
var io = require('socket.io')(server);
|
||
io.attach(server);
|
||
s.connectedClients={};
|
||
io.on('connection', function (cn) {
|
||
s.connectedClients[cn.id]={id:cn.id}
|
||
s.connectedClients[cn.id].tx = function(data){
|
||
data.pluginKey=config.key;data.plug=config.plug;
|
||
return io.to(cn.id).emit('ocv',data);
|
||
}
|
||
cn.on('f',function(d){
|
||
s.MainEventController(d,cn,s.connectedClients[cn.id].tx)
|
||
});
|
||
cn.on('disconnect',function(d){
|
||
delete(s.connectedClients[cn.id])
|
||
})
|
||
});
|
||
}else{
|
||
//start plugin as client
|
||
if(!config.host){config.host='localhost'}
|
||
var io = require('socket.io-client')('ws://'+config.host+':'+config.port);//connect to master
|
||
s.cx=function(x){x.pluginKey=config.key;x.plug=config.plug;return io.emit('ocv',x)}
|
||
io.on('connect',function(d){
|
||
s.cx({f:'init',plug:config.plug,notice:config.notice,type:config.type});
|
||
})
|
||
io.on('disconnect',function(d){
|
||
io.connect();
|
||
})
|
||
io.on('f',function(d){
|
||
s.MainEventController(d,null,s.cx)
|
||
})
|
||
}
|