mirror of
https://gitlab.com/Shinobi-Systems/ShinobiCE.git
synced 2025-03-09 15:40:15 +00:00
Coy Cobra
This commit is contained in:
Moe
parent
157bf6feb0
commit
c8b67c57b4
45 changed files with 3076 additions and 144 deletions
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@ -27,6 +27,7 @@ if [ ! -e "./super.json" ]; then
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fi
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echo "Shinobi - Run yum update"
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sudo yum update -y
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sudo yum install make -y
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echo "============="
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echo "Shinobi - Do you want to Install FFMPEG?"
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echo "(y)es or (N)o"
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@ -44,7 +45,7 @@ if [ "$ffmpeginstall" = "y" ] || [ "$ffmpeginstall" = "Y" ]; then
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sudo rpm -Uvh http://li.nux.ro/download/nux/dextop/el7/x86_64/nux-dextop-release-0-1.el7.nux.noarch.rpm
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sudo yum install ffmpeg ffmpeg-devel -y
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else
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sudo npm install ffmpeg-static
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sudo npm install ffmpeg-static@2.2.1
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fi
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fi
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echo "Shinobi - Do you want to Install Node.js?"
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@ -132,7 +133,9 @@ else
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fi
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echo "============="
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echo "Shinobi - Install NPM Libraries"
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sudo npm install
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sudo npm i npm -g
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sudo npm install --unsafe-perm
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sudo npm audit fix --unsafe-perm
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echo "============="
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echo "Shinobi - Install PM2"
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sudo npm install pm2 -g
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29
INSTALL/cuda.sh
Normal file
29
INSTALL/cuda.sh
Normal file
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@ -0,0 +1,29 @@
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#!/bin/sh
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echo "------------------------------------------"
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echo "-- Installing CUDA Toolkit and CUDA DNN --"
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echo "------------------------------------------"
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# Install CUDA Drivers and Toolkit
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wget https://cdn.shinobi.video/installers/cuda-repo-ubuntu1710_9.2.148-1_amd64.deb -O cuda.deb
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sudo dpkg -i cuda.deb
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sudo apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1710/x86_64/7fa2af80.pub
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sudo apt-get update -y
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sudo apt-get -o Dpkg::Options::="--force-overwrite" install cuda -y
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sudo apt-get -o Dpkg::Options::="--force-overwrite" install --fix-broken -y
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# Install CUDA DNN
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wget https://cdn.shinobi.video/installers/libcudnn7_7.2.1.38-1+cuda9.2_amd64.deb -O cuda-dnn.deb
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sudo dpkg -i cuda-dnn.deb
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wget https://cdn.shinobi.video/installers/libcudnn7-dev_7.2.1.38-1+cuda9.2_amd64.deb -O cuda-dnn-dev.deb
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sudo dpkg -i cuda-dnn-dev.deb
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echo "-- Cleaning Up --"
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# Cleanup
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sudo rm cuda.deb
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sudo rm cuda-dnn.deb
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sudo rm cuda-dnn-dev.deb
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echo "------------------------------"
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echo "Reboot is required. Do it now?"
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echo "------------------------------"
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echo "(y)es or (N)o. Default is No."
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read rebootTheMachineHomie
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if [ "$rebootTheMachineHomie" = "y" ] || [ "$rebootTheMachineHomie" = "Y" ]; then
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sudo reboot
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fi
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@ -41,7 +41,9 @@ if ( $mysqlagreeData == "y" ) then
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endif
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echo "============="
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echo "Shinobi - Install NPM Libraries"
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npm install
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npm i npm -g
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npm install --unsafe-perm
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npm audit fix --unsafe-perm
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echo "============="
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echo "Shinobi - Install PM2"
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npm install pm2 -g
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@ -49,7 +49,9 @@ if [ "$mysqlagreeData" = "y" ]; then
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fi
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echo "============="
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echo "Shinobi - Install NPM Libraries"
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sudo npm install
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sudo npm i npm -g
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sudo npm install --unsafe-perm
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sudo npm audit fix --unsafe-perm
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echo "============="
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echo "Shinobi - Install PM2"
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sudo npm install pm2 -g
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@ -1,4 +1,4 @@
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#!/bin/bash
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#!/bin/sh
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# OpenCV CUDA
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if [ $(dpkg-query -W -f='${Status}' git 2>/dev/null | grep -c "ok installed") -eq 0 ]; then
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echo "Installing Git..."
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@ -3,7 +3,6 @@ if [ -e "INSTALL/installed.txt" ]; then
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echo "Starting Shinobi"
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pm2 start camera.js
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pm2 start cron.js
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pm2 logs
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fi
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if [ ! -e "INSTALL/installed.txt" ]; then
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chmod +x INSTALL/now.sh&&INSTALL/now.sh
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@ -147,7 +147,9 @@ fi
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# Install NPM Libraries
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echo "============="
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echo "Shinobi - Install NPM Libraries"
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npm install
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sudo npm i npm -g
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sudo npm install --unsafe-perm
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sudo npm audit fix --unsafe-perm
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echo "============="
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#Install PM2
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@ -31,6 +31,7 @@ if [ "$nodejsinstall" = "y" ] || [ "$nodejsinstall" = "Y" ]; then
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./setup_8.x
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sudo apt install nodejs -y
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fi
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sudo apt install make -y
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echo "============="
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echo "Shinobi - Do you want to Install FFMPEG?"
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echo "(y)es or (N)o"
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@ -62,7 +63,7 @@ if [ "$ffmpeginstall" = "y" ] || [ "$ffmpeginstall" = "Y" ]; then
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echo "============="
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fi
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else
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sudo npm install ffmpeg-static
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sudo npm install ffmpeg-static@2.2.1
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fi
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fi
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echo "============="
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@ -146,7 +147,9 @@ else
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fi
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echo "============="
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echo "Shinobi - Install NPM Libraries"
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sudo npm install
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sudo npm i npm -g
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sudo npm install --unsafe-perm
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sudo npm audit fix --unsafe-perm
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echo "============="
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echo "Shinobi - Install PM2"
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sudo npm install pm2 -g
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213
camera.js
213
camera.js
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@ -816,8 +816,6 @@ s.init=function(x,e,k,fn){
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s.group[e.ke].init={}
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}
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if(!s.group[e.ke].fileBin){s.group[e.ke].fileBin={}};
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if(!s.group[e.ke].sizeChangeQueue){s.group[e.ke].sizeChangeQueue=[]}
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if(!s.group[e.ke].sizePurgeQueue){s.group[e.ke].sizePurgeQueue=[]}
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if(!s.group[e.ke].users){s.group[e.ke].users={}}
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if(!s.group[e.ke].dashcamUsers){s.group[e.ke].dashcamUsers={}}
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if(!e.limit||e.limit===''){e.limit=10000}else{e.limit=parseFloat(e.limit)}
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@ -892,6 +890,65 @@ s.init=function(x,e,k,fn){
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})
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s.group[e.ke].discordBot.login(ar.discordbot_token)
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}
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//disk Used Emitter
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if(!s.group[e.ke].diskUsedEmitter){
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s.group[e.ke].diskUsedEmitter = new events.EventEmitter()
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s.group[e.ke].diskUsedEmitter.on('data',function(currentChange){
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//validate current values
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if(!s.group[e.ke].usedSpace){
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s.group[e.ke].usedSpace=0
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}else{
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s.group[e.ke].usedSpace=parseFloat(s.group[e.ke].usedSpace)
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}
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if(s.group[e.ke].usedSpace<0||isNaN(s.group[e.ke].usedSpace)){
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s.group[e.ke].usedSpace=0
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}
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//change global size value
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s.group[e.ke].usedSpace=s.group[e.ke].usedSpace+currentChange
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//remove value just used from queue
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s.init('diskUsedEmit',e)
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})
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s.group[e.ke].diskPurgedEmitter = new events.EventEmitter()
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s.group[e.ke].diskPurgedEmitter.on('data',function(currentPurge){
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s.init('diskUsedSet',e,currentPurge.filesizeMB)
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if(config.cron.deleteOverMax===true){
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//set queue processor
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var finish=function(){
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s.init('diskUsedEmit',e)
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}
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var deleteVideos = function(){
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//run purge command
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if(s.group[e.ke].usedSpace>(s.group[e.ke].sizeLimit*config.cron.deleteOverMaxOffset)){
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s.sqlQuery('SELECT * FROM Videos WHERE status != 0 AND details NOT LIKE \'%"archived":"1"%\' AND ke=? ORDER BY `time` ASC LIMIT 2',[e.ke],function(err,evs){
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k.del=[];k.ar=[e.ke];
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if(!evs)return console.log(err)
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evs.forEach(function(ev){
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ev.dir=s.video('getDir',ev)+s.formattedTime(ev.time)+'.'+ev.ext;
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k.del.push('(mid=? AND `time`=?)');
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k.ar.push(ev.mid),k.ar.push(ev.time);
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s.file('delete',ev.dir);
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s.init('diskUsedSet',e,-(ev.size/1000000))
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s.tx({f:'video_delete',ff:'over_max',filename:s.formattedTime(ev.time)+'.'+ev.ext,mid:ev.mid,ke:ev.ke,time:ev.time,end:s.formattedTime(new Date,'YYYY-MM-DD HH:mm:ss')},'GRP_'+e.ke);
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});
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if(k.del.length>0){
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k.qu=k.del.join(' OR ');
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s.sqlQuery('DELETE FROM Videos WHERE ke =? AND ('+k.qu+')',k.ar,function(){
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deleteVideos()
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})
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}else{
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finish()
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}
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})
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}else{
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finish()
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}
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}
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deleteVideos()
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}else{
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s.init('diskUsedEmit',e)
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}
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})
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}
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Object.keys(ar).forEach(function(v){
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s.group[e.ke].init[v]=ar[v]
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})
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@ -943,37 +1000,7 @@ s.init=function(x,e,k,fn){
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break;
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case'diskUsedSet':
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//`k` will be used as the value to add or substract
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s.group[e.ke].sizeChangeQueue.push(k)
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if(s.group[e.ke].sizeChanging!==true){
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//lock this function
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s.group[e.ke].sizeChanging=true
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//validate current values
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if(!s.group[e.ke].usedSpace){
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s.group[e.ke].usedSpace=0
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}else{
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s.group[e.ke].usedSpace=parseFloat(s.group[e.ke].usedSpace)
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}
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if(s.group[e.ke].usedSpace<0||isNaN(s.group[e.ke].usedSpace)){
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s.group[e.ke].usedSpace=0
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}
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//set queue processor
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var checkQueue=function(){
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//get first in queue
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var currentChange = s.group[e.ke].sizeChangeQueue[0]
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//change global size value
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s.group[e.ke].usedSpace=s.group[e.ke].usedSpace+currentChange
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//remove value just used from queue
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s.group[e.ke].sizeChangeQueue = s.group[e.ke].sizeChangeQueue.splice(1,s.group[e.ke].sizeChangeQueue.length+10)
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//do next one
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if(s.group[e.ke].sizeChangeQueue.length>0){
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checkQueue()
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}else{
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s.group[e.ke].sizeChanging=false
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s.init('diskUsedEmit',e)
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}
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}
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checkQueue()
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}
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s.group[e.ke].diskUsedEmitter.emit('data',k)
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break;
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case'monitorStatus':
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// s.discordMsg({
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@ -1243,64 +1270,9 @@ s.video=function(x,e,k){
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v.details = details
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})
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break;
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case'diskUseUpdate':
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case'diskUseUpdate'://sizePurgeQueue
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if(s.group[e.ke].init){
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s.init('diskUsedSet',e,e.filesizeMB)
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if(config.cron.deleteOverMax===true){
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//check space
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s.group[e.ke].sizePurgeQueue.push(1)
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if(s.group[e.ke].sizePurging!==true){
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//lock this function
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s.group[e.ke].sizePurging=true
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//set queue processor
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var finish=function(){
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//remove value just used from queue
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s.group[e.ke].sizePurgeQueue = s.group[e.ke].sizePurgeQueue.splice(1,s.group[e.ke].sizePurgeQueue.length+10)
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//do next one
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if(s.group[e.ke].sizePurgeQueue.length>0){
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checkQueue()
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}else{
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s.group[e.ke].sizePurging=false
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s.init('diskUsedEmit',e)
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}
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}
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var checkQueue=function(){
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//get first in queue
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var currentPurge = s.group[e.ke].sizePurgeQueue[0]
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var deleteVideos = function(){
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//run purge command
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if(s.group[e.ke].usedSpace>(s.group[e.ke].sizeLimit*config.cron.deleteOverMaxOffset)){
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s.sqlQuery('SELECT * FROM Videos WHERE status != 0 AND details NOT LIKE \'%"archived":"1"%\' AND ke=? ORDER BY `time` ASC LIMIT 2',[e.ke],function(err,evs){
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k.del=[];k.ar=[e.ke];
|
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if(!evs)return console.log(err)
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evs.forEach(function(ev){
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ev.dir=s.video('getDir',ev)+s.formattedTime(ev.time)+'.'+ev.ext;
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k.del.push('(mid=? AND `time`=?)');
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k.ar.push(ev.mid),k.ar.push(ev.time);
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s.file('delete',ev.dir);
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s.init('diskUsedSet',e,-(ev.size/1000000))
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s.tx({f:'video_delete',ff:'over_max',filename:s.formattedTime(ev.time)+'.'+ev.ext,mid:ev.mid,ke:ev.ke,time:ev.time,end:s.formattedTime(new Date,'YYYY-MM-DD HH:mm:ss')},'GRP_'+e.ke);
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||||
});
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||||
if(k.del.length>0){
|
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k.qu=k.del.join(' OR ');
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s.sqlQuery('DELETE FROM Videos WHERE ke =? AND ('+k.qu+')',k.ar,function(){
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deleteVideos()
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||||
})
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||||
}else{
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||||
finish()
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||||
}
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||||
})
|
||||
}else{
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finish()
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||||
}
|
||||
}
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||||
deleteVideos()
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||||
}
|
||||
checkQueue()
|
||||
}
|
||||
}else{
|
||||
s.init('diskUsedEmit',e)
|
||||
}
|
||||
s.group[e.ke].diskPurgedEmitter.emit('data',k)
|
||||
}
|
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break;
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case'insertCompleted':
|
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|
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@ -1325,16 +1297,16 @@ s.video=function(x,e,k){
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if(k.fileExists===true){
|
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//close video row
|
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k.stat = fs.statSync(k.dir+k.file)
|
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e.filesize = k.stat.size
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e.filesizeMB = parseFloat((e.filesize/1000000).toFixed(2))
|
||||
k.filesize = k.stat.size
|
||||
k.filesizeMB = parseFloat((k.filesize/1000000).toFixed(2))
|
||||
|
||||
e.startTime = new Date(s.nameToTime(k.file))
|
||||
e.endTime = new Date(k.stat.mtime)
|
||||
k.startTime = new Date(s.nameToTime(k.file))
|
||||
k.endTime = new Date(k.stat.mtime)
|
||||
if(config.useUTC === true){
|
||||
fs.rename(k.dir+k.file, k.dir+s.formattedTime(e.startTime)+'.'+e.ext, (err) => {
|
||||
fs.rename(k.dir+k.file, k.dir+s.formattedTime(k.startTime)+'.'+e.ext, (err) => {
|
||||
if (err) return console.error(err);
|
||||
});
|
||||
k.filename = s.formattedTime(e.startTime)+'.'+e.ext
|
||||
k.filename = s.formattedTime(k.startTime)+'.'+e.ext
|
||||
}else{
|
||||
k.filename = k.file
|
||||
}
|
||||
|
|
@ -1351,8 +1323,8 @@ s.video=function(x,e,k){
|
|||
filename:k.filename,
|
||||
d:s.init('noReference',e),
|
||||
filesize:e.filesize,
|
||||
time:s.timeObject(e.startTime).format(),
|
||||
end:s.timeObject(e.endTime).format()
|
||||
time:s.timeObject(k.startTime).format(),
|
||||
end:s.timeObject(k.endTime).format()
|
||||
})
|
||||
})
|
||||
.on('close',function(){
|
||||
|
|
@ -1364,9 +1336,9 @@ s.video=function(x,e,k){
|
|||
ke:e.ke,
|
||||
filename:k.filename,
|
||||
d:s.init('noReference',e),
|
||||
filesize:e.filesize,
|
||||
time:s.timeObject(e.startTime).format(),
|
||||
end:s.timeObject(e.endTime).format()
|
||||
filesize:k.filesize,
|
||||
time:s.timeObject(k.startTime).format(),
|
||||
end:s.timeObject(k.endTime).format()
|
||||
})
|
||||
});
|
||||
}else{
|
||||
|
|
@ -1378,9 +1350,9 @@ s.video=function(x,e,k){
|
|||
filename:k.filename,
|
||||
mid:e.mid,
|
||||
ke:e.ke,
|
||||
time:e.startTime,
|
||||
size:e.filesize,
|
||||
end:e.endTime
|
||||
time:k.startTime,
|
||||
size:k.filesize,
|
||||
end:k.endTime
|
||||
},'GRP_'+e.ke,'video_view');
|
||||
}
|
||||
//cloud auto savers
|
||||
|
|
@ -1431,11 +1403,11 @@ s.video=function(x,e,k){
|
|||
var save = [
|
||||
e.mid,
|
||||
e.ke,
|
||||
e.startTime,
|
||||
k.startTime,
|
||||
0,
|
||||
'{}',
|
||||
e.filesize,
|
||||
e.endTime,
|
||||
k.filesize,
|
||||
k.endTime,
|
||||
data.Location
|
||||
]
|
||||
s.sqlQuery('INSERT INTO `Cloud Videos` (mid,ke,time,status,details,size,end,href) VALUES (?,?,?,?,?,?,?,?)',save)
|
||||
|
|
@ -1450,12 +1422,12 @@ s.video=function(x,e,k){
|
|||
var save = [
|
||||
e.mid,
|
||||
e.ke,
|
||||
e.startTime,
|
||||
k.startTime,
|
||||
e.ext,
|
||||
1,
|
||||
s.s(k.details),
|
||||
e.filesize,
|
||||
e.endTime,
|
||||
k.filesize,
|
||||
k.endTime,
|
||||
]
|
||||
s.sqlQuery('INSERT INTO Videos (mid,ke,time,ext,status,details,size,end) VALUES (?,?,?,?,?,?,?,?)',save)
|
||||
//send new diskUsage values
|
||||
|
|
@ -2113,7 +2085,6 @@ s.ffmpeg = function(e){
|
|||
if(e.details.cust_stream&&e.details.cust_stream!==''){x.cust_stream=' '+e.details.cust_stream}else{x.cust_stream=''}
|
||||
//stream - preset
|
||||
if(e.details.stream_type !== 'h265' && e.details.preset_stream && e.details.preset_stream !== ''){x.preset_stream=' -preset '+e.details.preset_stream;}else{x.preset_stream=''}
|
||||
//stream - quality
|
||||
//hardware acceleration
|
||||
if(e.details.accelerator && e.details.accelerator==='1' && e.isStreamer === false){
|
||||
if(e.details.hwaccel&&e.details.hwaccel!==''){
|
||||
|
|
@ -2283,6 +2254,9 @@ s.ffmpeg = function(e){
|
|||
}
|
||||
if(!e.details.detector_buffer_acodec||e.details.detector_buffer_acodec===''||e.details.detector_buffer_acodec==='auto'){
|
||||
switch(e.type){
|
||||
case'mjpeg':case'jpeg':case'socket':
|
||||
e.details.detector_buffer_acodec = 'no'
|
||||
break;
|
||||
case'h264':case'hls':case'mp4':
|
||||
e.details.detector_buffer_acodec = 'copy'
|
||||
break;
|
||||
|
|
@ -2424,7 +2398,7 @@ s.file=function(x,e){
|
|||
s.event = function(x,e,cn){
|
||||
switch(x){
|
||||
case'trigger':
|
||||
var d=e;
|
||||
var d = e;
|
||||
var filter = {
|
||||
halt : false,
|
||||
addToMotionCounter : true,
|
||||
|
|
@ -3693,18 +3667,6 @@ s.camera=function(x,e,cn,tx){
|
|||
s.group[e.ke].mon[e.id].emitter.emit('data',d);
|
||||
}
|
||||
break;
|
||||
// case'pam':
|
||||
// s.group[e.ke].mon[e.id].p2pStream = new P2P();
|
||||
// s.group[e.ke].mon[e.id].spawn.stdout.pipe(s.group[e.ke].mon[e.id].p2pStream)
|
||||
// s.group[e.ke].mon[e.id].p2pStream.on('pam',function(d){
|
||||
// resetStreamCheck()
|
||||
// s.tx({f:'pam_frame',ke:e.ke,id:e.id,imageData:{
|
||||
// data : d.pixels,
|
||||
// height : d.height,
|
||||
// width : d.width
|
||||
// }},'MON_STREAM_'+e.id);
|
||||
// })
|
||||
// break;
|
||||
case'b64':case undefined:case null:case'':
|
||||
var buffer
|
||||
e.frame_to_stream=function(d){
|
||||
|
|
@ -3978,6 +3940,7 @@ s.pluginInitiatorSuccess=function(mode,d,cn){
|
|||
s.api[d.plug]={pluginEngine:d.plug,permissions:{},details:{},ip:'0.0.0.0'};
|
||||
}
|
||||
s.pluginInitiatorFail=function(mode,d,cn){
|
||||
if(s.connectedPlugins[d.plug])s.connectedPlugins[d.plug].plugged=false
|
||||
if(mode==='client'){
|
||||
//is in client mode (camera.js is client)
|
||||
cn.disconnect()
|
||||
|
|
@ -4050,7 +4013,7 @@ var tx;
|
|||
}
|
||||
}
|
||||
})
|
||||
//unique Base64 socket stream
|
||||
//unique h265 socket stream
|
||||
cn.on('h265',function(d){
|
||||
if(!s.group[d.ke]||!s.group[d.ke].mon||!s.group[d.ke].mon[d.id]){
|
||||
cn.disconnect();return;
|
||||
|
|
|
|||
|
|
@ -20,10 +20,5 @@
|
|||
"cron":{
|
||||
"key":"change_this_to_something_very_random__just_anything_other_than_this"
|
||||
},
|
||||
"pluginKeys":{
|
||||
"Motion":"change_this_to_something_very_random____make_sure_to_match__/plugins/motion/conf.json",
|
||||
"OpenCV":"change_this_to_something_very_random____make_sure_to_match__/plugins/opencv/conf.json",
|
||||
"OpenALPR":"SomeOpenALPRkeySoPeopleDontMessWithYourShinobi",
|
||||
"PythonYolo":"SomeOpenALPRkeySoPeopleDontMessWithYourShinobi"
|
||||
}
|
||||
"pluginKeys":{}
|
||||
}
|
||||
2
plugins/dnnCoco/.gitignore
vendored
Normal file
2
plugins/dnnCoco/.gitignore
vendored
Normal file
|
|
@ -0,0 +1,2 @@
|
|||
conf.json
|
||||
data
|
||||
19
plugins/dnnCoco/INSTALL.sh
Normal file
19
plugins/dnnCoco/INSTALL.sh
Normal file
|
|
@ -0,0 +1,19 @@
|
|||
#!/bin/bash
|
||||
mkdir data
|
||||
chmod -R 777 data
|
||||
wget https://cdn.shinobi.video/weights/dnnCocoData.zip -O dnnCocoData.zip
|
||||
unzip dnnCocoData.zip -d data
|
||||
if [ $(dpkg-query -W -f='${Status}' opencv_version 2>/dev/null | grep -c "ok installed") -eq 0 ]; then
|
||||
echo "Shinobi - Do ypu want to let the `opencv4nodejs` npm package install OpenCV? "
|
||||
echo "Only do this if you do not have OpenCV already or will not use a GPU (Hardware Acceleration)."
|
||||
echo "(y)es or (N)o"
|
||||
read nodejsinstall
|
||||
if [ "$nodejsinstall" = "y" ] || [ "$nodejsinstall" = "Y" ]; then
|
||||
export OPENCV4NODEJS_DISABLE_AUTOBUILD=0
|
||||
else
|
||||
export OPENCV4NODEJS_DISABLE_AUTOBUILD=1
|
||||
fi
|
||||
else
|
||||
export OPENCV4NODEJS_DISABLE_AUTOBUILD=1
|
||||
fi
|
||||
npm install opencv4nodejs moment express canvas@1.6 --unsafe-perm
|
||||
9
plugins/dnnCoco/conf.sample.json
Normal file
9
plugins/dnnCoco/conf.sample.json
Normal file
|
|
@ -0,0 +1,9 @@
|
|||
{
|
||||
"plug":"Coco",
|
||||
"host":"localhost",
|
||||
"port":8080,
|
||||
"hostPort":8082,
|
||||
"key":"change_this_to_something_very_random____make_sure_to_match__/plugins/opencv/conf.json",
|
||||
"mode":"client",
|
||||
"type":"detector"
|
||||
}
|
||||
83
plugins/dnnCoco/dnnCocoClassNames.js
Normal file
83
plugins/dnnCoco/dnnCocoClassNames.js
Normal file
|
|
@ -0,0 +1,83 @@
|
|||
module.exports = [
|
||||
'background',
|
||||
'person',
|
||||
'bicycle',
|
||||
'car',
|
||||
'motorcycle',
|
||||
'airplane',
|
||||
'bus',
|
||||
'train',
|
||||
'truck',
|
||||
'boat',
|
||||
'traffic light',
|
||||
'fire hydrant',
|
||||
'stop sign',
|
||||
'parking meter',
|
||||
'bench',
|
||||
'bird',
|
||||
'cat',
|
||||
'dog',
|
||||
'horse',
|
||||
'sheep',
|
||||
'cow',
|
||||
'elephant',
|
||||
'bear',
|
||||
'zebra',
|
||||
'giraffe',
|
||||
'backpack',
|
||||
'umbrella',
|
||||
'handbag',
|
||||
'tie',
|
||||
'suitcase',
|
||||
'frisbee',
|
||||
'skis',
|
||||
'snowboard',
|
||||
'sports ball',
|
||||
'kite',
|
||||
'baseball bat',
|
||||
'baseball glove',
|
||||
'skateboard',
|
||||
'surfboard',
|
||||
'tennis racket',
|
||||
'bottle',
|
||||
'wine glass',
|
||||
'cup',
|
||||
'fork',
|
||||
'knife',
|
||||
'spoon',
|
||||
'bowl',
|
||||
'banana',
|
||||
'apple',
|
||||
'sandwich',
|
||||
'orange',
|
||||
'broccoli',
|
||||
'carrot',
|
||||
'hot dog',
|
||||
'pizza',
|
||||
'donut',
|
||||
'cake',
|
||||
'chair',
|
||||
'couch',
|
||||
'potted plant',
|
||||
'bed',
|
||||
'dining table',
|
||||
'toilet',
|
||||
'tv',
|
||||
'laptop',
|
||||
'mouse',
|
||||
'remote',
|
||||
'keyboard',
|
||||
'cell phone',
|
||||
'microwave',
|
||||
'oven',
|
||||
'toaster',
|
||||
'sink',
|
||||
'refrigerator',
|
||||
'book',
|
||||
'clock',
|
||||
'vase',
|
||||
'scissors',
|
||||
'teddy bear',
|
||||
'hair drier',
|
||||
'toothbrush'
|
||||
];
|
||||
94
plugins/dnnCoco/openalpr.conf
Normal file
94
plugins/dnnCoco/openalpr.conf
Normal file
|
|
@ -0,0 +1,94 @@
|
|||
|
||||
; Specify the path to the runtime data directory
|
||||
runtime_dir = ${CMAKE_INSTALL_PREFIX}/share/openalpr/runtime_data
|
||||
|
||||
|
||||
ocr_img_size_percent = 1.33333333
|
||||
state_id_img_size_percent = 2.0
|
||||
|
||||
; Calibrating your camera improves detection accuracy in cases where vehicle plates are captured at a steep angle
|
||||
; Use the openalpr-utils-calibrate utility to calibrate your fixed camera to adjust for an angle
|
||||
; Once done, update the prewarp config with the values obtained from the tool
|
||||
prewarp =
|
||||
|
||||
; detection will ignore plates that are too large. This is a good efficiency technique to use if the
|
||||
; plates are going to be a fixed distance away from the camera (e.g., you will never see plates that fill
|
||||
; up the entire image
|
||||
max_plate_width_percent = 100
|
||||
max_plate_height_percent = 100
|
||||
|
||||
; detection_iteration_increase is the percentage that the LBP frame increases each iteration.
|
||||
; It must be greater than 1.0. A value of 1.01 means increase by 1%, 1.10 increases it by 10% each time.
|
||||
; So a 1% increase would be ~10x slower than 10% to process, but it has a higher chance of landing
|
||||
; directly on the plate and getting a strong detection
|
||||
detection_iteration_increase = 1.1
|
||||
|
||||
; The minimum detection strength determines how sure the detection algorithm must be before signaling that
|
||||
; a plate region exists. Technically this corresponds to LBP nearest neighbors (e.g., how many detections
|
||||
; are clustered around the same area). For example, 2 = very lenient, 9 = very strict.
|
||||
detection_strictness = 3
|
||||
|
||||
; The detection doesn't necessarily need an extremely high resolution image in order to detect plates
|
||||
; Using a smaller input image should still find the plates and will do it faster
|
||||
; Tweaking the max_detection_input values will resize the input image if it is larger than these sizes
|
||||
; max_detection_input_width/height are specified in pixels
|
||||
max_detection_input_width = 1280
|
||||
max_detection_input_height = 720
|
||||
|
||||
; detector is the technique used to find license plate regions in an image. Value can be set to
|
||||
; lbpcpu - default LBP-based detector uses the system CPU
|
||||
; lbpgpu - LBP-based detector that uses Nvidia GPU to increase recognition speed.
|
||||
; lbpopencl - LBP-based detector that uses OpenCL GPU to increase recognition speed. Requires OpenCV 3.0
|
||||
; morphcpu - Experimental detector that detects white rectangles in an image. Does not require training.
|
||||
detector = lbpgpu
|
||||
|
||||
; If set to true, all results must match a postprocess text pattern if a pattern is available.
|
||||
; If not, the result is disqualified.
|
||||
must_match_pattern = 0
|
||||
|
||||
; Bypasses plate detection. If this is set to 1, the library assumes that each region provided is a likely plate area.
|
||||
skip_detection = 0
|
||||
|
||||
; Specifies the full path to an image file that constrains the detection area. Only the plate regions allowed through the mask
|
||||
; will be analyzed. The mask image must match the resolution of your image to be analyzed. The mask is black and white.
|
||||
; Black areas will be ignored, white areas will be searched. An empty value means no mask (scan the entire image)
|
||||
detection_mask_image =
|
||||
|
||||
; OpenALPR can scan the same image multiple times with different randomization. Setting this to a value larger than
|
||||
; 1 may increase accuracy, but will increase processing time linearly (e.g., analysis_count = 3 is 3x slower)
|
||||
analysis_count = 1
|
||||
|
||||
; OpenALPR detects high-contrast plate crops and uses an alternative edge detection technique. Setting this to 0.0
|
||||
; would classify ALL images as high-contrast, setting it to 1.0 would classify no images as high-contrast.
|
||||
contrast_detection_threshold = 0.3
|
||||
|
||||
max_plate_angle_degrees = 15
|
||||
|
||||
ocr_min_font_point = 6
|
||||
|
||||
; Minimum OCR confidence percent to consider.
|
||||
postprocess_min_confidence = 65
|
||||
|
||||
; Any OCR character lower than this will also add an equally likely
|
||||
; chance that the character is incorrect and will be skipped. Value is a confidence percent
|
||||
postprocess_confidence_skip_level = 80
|
||||
|
||||
|
||||
debug_general = 0
|
||||
debug_timing = 0
|
||||
debug_detector = 0
|
||||
debug_prewarp = 0
|
||||
debug_state_id = 0
|
||||
debug_plate_lines = 0
|
||||
debug_plate_corners = 0
|
||||
debug_char_segment = 0
|
||||
debug_char_analysis = 0
|
||||
debug_color_filter = 0
|
||||
debug_ocr = 0
|
||||
debug_postprocess = 0
|
||||
debug_show_images = 0
|
||||
debug_pause_on_frame = 0
|
||||
|
||||
|
||||
|
||||
|
||||
525
plugins/dnnCoco/shinobi-coco.js
Normal file
525
plugins/dnnCoco/shinobi-coco.js
Normal file
|
|
@ -0,0 +1,525 @@
|
|||
//
|
||||
// Shinobi - OpenCV Plugin
|
||||
// Copyright (C) 2016-2025 Moe Alam, moeiscool
|
||||
//
|
||||
// # Donate
|
||||
//
|
||||
// If you like what I am doing here and want me to continue please consider donating :)
|
||||
// PayPal : paypal@m03.ca
|
||||
//
|
||||
process.on('uncaughtException', function (err) {
|
||||
console.error('uncaughtException',err);
|
||||
});
|
||||
var fs=require('fs');
|
||||
var cv=require('opencv4nodejs');
|
||||
var exec = require('child_process').exec;
|
||||
var moment = require('moment');
|
||||
var Canvas = require('canvas');
|
||||
var express = require('express');
|
||||
const path = require('path');
|
||||
var http = require('http'),
|
||||
app = express(),
|
||||
server = http.createServer(app);
|
||||
var config=require('./conf.json');
|
||||
if(!config.port){config.port=8080}
|
||||
if(!config.hostPort){config.hostPort=8082}
|
||||
if(config.systemLog===undefined){config.systemLog=true}
|
||||
if(config.cascadesDir===undefined){config.cascadesDir=__dirname+'/cascades/'}
|
||||
if(config.alprConfig===undefined){config.alprConfig=__dirname+'/openalpr.conf'}
|
||||
|
||||
|
||||
const classNames = require(__dirname+'/dnnCocoClassNames.js');
|
||||
const extractResults = function (outputBlob, imgDimensions) {
|
||||
return Array(outputBlob.rows).fill(0)
|
||||
.map((res, i) => {
|
||||
const classLabel = outputBlob.at(i, 1);
|
||||
const confidence = outputBlob.at(i, 2);
|
||||
const bottomLeft = new cv.Point(
|
||||
outputBlob.at(i, 3) * imgDimensions.cols,
|
||||
outputBlob.at(i, 6) * imgDimensions.rows
|
||||
);
|
||||
const topRight = new cv.Point(
|
||||
outputBlob.at(i, 5) * imgDimensions.cols,
|
||||
outputBlob.at(i, 4) * imgDimensions.rows
|
||||
);
|
||||
const rect = new cv.Rect(
|
||||
bottomLeft.x,
|
||||
topRight.y,
|
||||
topRight.x - bottomLeft.x,
|
||||
bottomLeft.y - topRight.y
|
||||
);
|
||||
|
||||
return ({
|
||||
classLabel,
|
||||
confidence,
|
||||
rect
|
||||
});
|
||||
});
|
||||
};
|
||||
// replace with path where you unzipped inception model
|
||||
const ssdcocoModelPath = __dirname+'/data';
|
||||
|
||||
const prototxt = path.resolve(ssdcocoModelPath, 'deploy.prototxt');
|
||||
const modelFile = path.resolve(ssdcocoModelPath, 'VGG_coco_SSD_300x300_iter_400000.caffemodel');
|
||||
|
||||
if (!fs.existsSync(prototxt) || !fs.existsSync(modelFile)) {
|
||||
console.log('could not find ssdcoco model');
|
||||
console.log('download the model from: https://cdn.shinobi.video/weights/dnnCocoData.zip');
|
||||
throw new Error('exiting: could not find ssdcoco model');
|
||||
}
|
||||
|
||||
// initialize ssdcoco model from prototxt and modelFile
|
||||
const net = cv.readNetFromCaffe(prototxt, modelFile);
|
||||
|
||||
function classifyImg(img) {
|
||||
// ssdcoco model works with 300 x 300 images
|
||||
const imgResized = img.resize(300, 300);
|
||||
|
||||
// network accepts blobs as input
|
||||
const inputBlob = cv.blobFromImage(imgResized);
|
||||
net.setInput(inputBlob);
|
||||
|
||||
// forward pass input through entire network, will return
|
||||
// classification result as 1x1xNxM Mat
|
||||
let outputBlob = net.forward();
|
||||
// extract NxM Mat
|
||||
outputBlob = outputBlob.flattenFloat(outputBlob.sizes[2], outputBlob.sizes[3]);
|
||||
|
||||
return extractResults(outputBlob, img)
|
||||
.map(r => Object.assign({}, r.rect, { confidence : r.confidence, tag: classNames[r.classLabel] }));
|
||||
}
|
||||
|
||||
const makeDrawClassDetections = predictions => (drawImg, className, getColor, thickness = 2) => {
|
||||
predictions
|
||||
.filter(p => classNames[p.classLabel] === className)
|
||||
.forEach(p => console.log(p));
|
||||
};
|
||||
|
||||
|
||||
s={
|
||||
group:{},
|
||||
dir:{
|
||||
cascades : config.cascadesDir
|
||||
},
|
||||
isWin:(process.platform==='win32'),
|
||||
foundCascades : {
|
||||
|
||||
}
|
||||
}
|
||||
//default stream folder check
|
||||
if(!config.streamDir){
|
||||
if(s.isWin===false){
|
||||
config.streamDir='/dev/shm'
|
||||
}else{
|
||||
config.streamDir=config.windowsTempDir
|
||||
}
|
||||
if(!fs.existsSync(config.streamDir)){
|
||||
config.streamDir=__dirname+'/streams/'
|
||||
}else{
|
||||
config.streamDir+='/streams/'
|
||||
}
|
||||
}
|
||||
s.dir.streams=config.streamDir;
|
||||
//streams dir
|
||||
if(!fs.existsSync(s.dir.streams)){
|
||||
fs.mkdirSync(s.dir.streams);
|
||||
}
|
||||
//streams dir
|
||||
if(!fs.existsSync(s.dir.cascades)){
|
||||
fs.mkdirSync(s.dir.cascades);
|
||||
}
|
||||
s.gid=function(x){
|
||||
if(!x){x=10};var t = "";var p = "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789";
|
||||
for( var i=0; i < x; i++ )
|
||||
t += p.charAt(Math.floor(Math.random() * p.length));
|
||||
return t;
|
||||
};
|
||||
s.findCascades=function(callback){
|
||||
var tmp={};
|
||||
tmp.foundCascades=[];
|
||||
fs.readdir(s.dir.cascades,function(err,files){
|
||||
files.forEach(function(cascade,n){
|
||||
if(cascade.indexOf('.xml')>-1){
|
||||
tmp.foundCascades.push(cascade.replace('.xml',''))
|
||||
}
|
||||
})
|
||||
s.cascadesInDir=tmp.foundCascades;
|
||||
callback(tmp.foundCascades)
|
||||
})
|
||||
}
|
||||
s.findCascades(function(){
|
||||
//get cascades
|
||||
})
|
||||
s.detectLicensePlate=function(buffer,d,tx){
|
||||
if(!d.mon.detector_lisence_plate_country||d.mon.detector_lisence_plate_country===''){
|
||||
d.mon.detector_lisence_plate_country='us'
|
||||
}
|
||||
d.tmpFile=s.gid(5)+'.jpg'
|
||||
if(!fs.existsSync(s.dir.streams)){
|
||||
fs.mkdirSync(s.dir.streams);
|
||||
}
|
||||
d.dir=s.dir.streams+d.ke+'/'
|
||||
if(!fs.existsSync(d.dir)){
|
||||
fs.mkdirSync(d.dir);
|
||||
}
|
||||
d.dir=s.dir.streams+d.ke+'/'+d.id+'/'
|
||||
if(!fs.existsSync(d.dir)){
|
||||
fs.mkdirSync(d.dir);
|
||||
}
|
||||
fs.writeFile(d.dir+d.tmpFile,buffer,function(err){
|
||||
if(err) return s.systemLog(err);
|
||||
exec('alpr -j --config '+config.alprConfig+' -c '+d.mon.detector_lisence_plate_country+' '+d.dir+d.tmpFile,{encoding:'utf8'},(err, scan, stderr) => {
|
||||
if(err){
|
||||
s.systemLog(err);
|
||||
}else{
|
||||
try{
|
||||
scan=JSON.parse(scan.replace('--(!)Loaded CUDA classifier','').trim())
|
||||
}catch(err){
|
||||
if(!scan||!scan.results){
|
||||
return s.systemLog(scan,err);
|
||||
}
|
||||
}
|
||||
if(scan.results.length>0){
|
||||
scan.plates=[]
|
||||
scan.mats=[]
|
||||
scan.results.forEach(function(v){
|
||||
v.candidates.forEach(function(g,n){
|
||||
if(v.candidates[n].matches_template)
|
||||
delete(v.candidates[n].matches_template)
|
||||
})
|
||||
scan.plates.push({coordinates:v.coordinates,candidates:v.candidates,confidence:v.confidence,plate:v.plate})
|
||||
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));
|
||||
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))
|
||||
scan.mats.push({
|
||||
x:v.coordinates[0].x,
|
||||
y:v.coordinates[0].y,
|
||||
width:width,
|
||||
height:height,
|
||||
tag:v.plate
|
||||
})
|
||||
})
|
||||
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}})
|
||||
}
|
||||
}
|
||||
exec('rm -rf '+d.dir+d.tmpFile,{encoding:'utf8'})
|
||||
})
|
||||
})
|
||||
}
|
||||
s.detectObject=function(buffer,d,tx){
|
||||
//detect license plate?
|
||||
if(d.mon.detector_lisence_plate==="1"){
|
||||
s.detectLicensePlate(buffer,d,tx)
|
||||
}
|
||||
cv.imdecodeAsync(buffer,(err,im) => {
|
||||
if(err){
|
||||
console.log(err)
|
||||
return
|
||||
}
|
||||
|
||||
if (!cv.xmodules.dnn) {
|
||||
throw new Error('exiting: opencv4nodejs compiled without dnn module');
|
||||
}
|
||||
|
||||
|
||||
const minConfidence = 0.5;
|
||||
|
||||
const predictions = classifyImg(im).filter(res => res.confidence > minConfidence);
|
||||
// console.log(predictions)
|
||||
if(predictions.length > 0) {
|
||||
s.cx({
|
||||
f:'trigger',
|
||||
id:d.id,
|
||||
ke:d.ke,
|
||||
name:'coco',
|
||||
details:{
|
||||
plug:'coco',
|
||||
name:'coco',
|
||||
reason:'object',
|
||||
matrices : predictions
|
||||
// confidence:d.average
|
||||
},
|
||||
imgHeight:d.mon.detector_scale_y,
|
||||
imgWidth:d.mon.detector_scale_x
|
||||
})
|
||||
}
|
||||
})
|
||||
}
|
||||
s.systemLog=function(q,w,e){
|
||||
if(!w){w=''}
|
||||
if(!e){e=''}
|
||||
if(config.systemLog===true){
|
||||
return console.log(moment().format(),q,w,e)
|
||||
}
|
||||
}
|
||||
|
||||
s.blenderRegion=function(d,cord,tx){
|
||||
d.width = d.image.width;
|
||||
d.height = d.image.height;
|
||||
if(!s.group[d.ke][d.id].canvas[cord.name]){
|
||||
if(!cord.sensitivity||isNaN(cord.sensitivity)){
|
||||
cord.sensitivity=d.mon.detector_sensitivity;
|
||||
}
|
||||
s.group[d.ke][d.id].canvas[cord.name] = new Canvas(d.width,d.height);
|
||||
s.group[d.ke][d.id].canvasContext[cord.name] = s.group[d.ke][d.id].canvas[cord.name].getContext('2d');
|
||||
s.group[d.ke][d.id].canvasContext[cord.name].fillStyle = '#000';
|
||||
s.group[d.ke][d.id].canvasContext[cord.name].fillRect( 0, 0,d.width,d.height);
|
||||
if(cord.points&&cord.points.length>0){
|
||||
s.group[d.ke][d.id].canvasContext[cord.name].beginPath();
|
||||
for (var b = 0; b < cord.points.length; b++){
|
||||
cord.points[b][0]=parseFloat(cord.points[b][0]);
|
||||
cord.points[b][1]=parseFloat(cord.points[b][1]);
|
||||
if(b===0){
|
||||
s.group[d.ke][d.id].canvasContext[cord.name].moveTo(cord.points[b][0],cord.points[b][1]);
|
||||
}else{
|
||||
s.group[d.ke][d.id].canvasContext[cord.name].lineTo(cord.points[b][0],cord.points[b][1]);
|
||||
}
|
||||
}
|
||||
s.group[d.ke][d.id].canvasContext[cord.name].clip();
|
||||
}
|
||||
}
|
||||
if(!s.group[d.ke][d.id].canvasContext[cord.name]){
|
||||
return
|
||||
}
|
||||
s.group[d.ke][d.id].canvasContext[cord.name].drawImage(d.image, 0, 0, d.width, d.height);
|
||||
if(!s.group[d.ke][d.id].blendRegion[cord.name]){
|
||||
s.group[d.ke][d.id].blendRegion[cord.name] = new Canvas(d.width, d.height);
|
||||
s.group[d.ke][d.id].blendRegionContext[cord.name] = s.group[d.ke][d.id].blendRegion[cord.name].getContext('2d');
|
||||
}
|
||||
var sourceData = s.group[d.ke][d.id].canvasContext[cord.name].getImageData(0, 0, d.width, d.height);
|
||||
// create an image if the previous image doesn<73>t exist
|
||||
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);
|
||||
// create a ImageData instance to receive the blended result
|
||||
var blendedData = s.group[d.ke][d.id].canvasContext[cord.name].createImageData(d.width, d.height);
|
||||
// blend the 2 images
|
||||
s.differenceAccuracy(blendedData.data,sourceData.data,s.group[d.ke][d.id].lastRegionImageData[cord.name].data);
|
||||
// draw the result in a canvas
|
||||
s.group[d.ke][d.id].blendRegionContext[cord.name].putImageData(blendedData, 0, 0);
|
||||
// store the current webcam image
|
||||
s.group[d.ke][d.id].lastRegionImageData[cord.name] = sourceData;
|
||||
blendedData = s.group[d.ke][d.id].blendRegionContext[cord.name].getImageData(0, 0, d.width, d.height);
|
||||
var i = 0;
|
||||
d.average = 0;
|
||||
while (i < (blendedData.data.length * 0.25)) {
|
||||
d.average += (blendedData.data[i * 4] + blendedData.data[i * 4 + 1] + blendedData.data[i * 4 + 2]);
|
||||
++i;
|
||||
}
|
||||
d.average = (d.average / (blendedData.data.length * 0.25))*10;
|
||||
if (d.average > parseFloat(cord.sensitivity)){
|
||||
if(d.mon.detector_use_detect_object==="1"&&d.mon.detector_second!=='1'){
|
||||
var buffer=s.group[d.ke][d.id].canvas[cord.name].toBuffer();
|
||||
s.detectObject(buffer,d,tx)
|
||||
}else{
|
||||
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}})
|
||||
}
|
||||
}
|
||||
s.group[d.ke][d.id].canvasContext[cord.name].clearRect(0, 0, d.width, d.height);
|
||||
s.group[d.ke][d.id].blendRegionContext[cord.name].clearRect(0, 0, d.width, d.height);
|
||||
}
|
||||
function blobToBuffer (blob, cb) {
|
||||
if (typeof Blob === 'undefined' || !(blob instanceof Blob)) {
|
||||
throw new Error('first argument must be a Blob')
|
||||
}
|
||||
if (typeof cb !== 'function') {
|
||||
throw new Error('second argument must be a function')
|
||||
}
|
||||
|
||||
var reader = new FileReader()
|
||||
|
||||
function onLoadEnd (e) {
|
||||
reader.removeEventListener('loadend', onLoadEnd, false)
|
||||
if (e.error) cb(e.error)
|
||||
else cb(null, Buffer.from(reader.result))
|
||||
}
|
||||
|
||||
reader.addEventListener('loadend', onLoadEnd, false)
|
||||
reader.readAsArrayBuffer(blob)
|
||||
}
|
||||
function fastAbs(value) {
|
||||
return (value ^ (value >> 31)) - (value >> 31);
|
||||
}
|
||||
|
||||
function threshold(value) {
|
||||
return (value > 0x15) ? 0xFF : 0;
|
||||
}
|
||||
s.differenceAccuracy=function(target, data1, data2) {
|
||||
if (data1.length != data2.length) return null;
|
||||
var i = 0;
|
||||
while (i < (data1.length * 0.25)) {
|
||||
var average1 = (data1[4 * i] + data1[4 * i + 1] + data1[4 * i + 2]) / 3;
|
||||
var average2 = (data2[4 * i] + data2[4 * i + 1] + data2[4 * i + 2]) / 3;
|
||||
var diff = threshold(fastAbs(average1 - average2));
|
||||
target[4 * i] = diff;
|
||||
target[4 * i + 1] = diff;
|
||||
target[4 * i + 2] = diff;
|
||||
target[4 * i + 3] = 0xFF;
|
||||
++i;
|
||||
}
|
||||
}
|
||||
s.checkAreas=function(d,tx){
|
||||
if(!s.group[d.ke][d.id].cords){
|
||||
if(!d.mon.cords){d.mon.cords={}}
|
||||
s.group[d.ke][d.id].cords=Object.values(d.mon.cords);
|
||||
}
|
||||
if(d.mon.detector_frame==='1'){
|
||||
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]]};
|
||||
s.group[d.ke][d.id].cords.push(d.mon.cords.frame);
|
||||
}
|
||||
for (var b = 0; b < s.group[d.ke][d.id].cords.length; b++){
|
||||
if(!s.group[d.ke][d.id].cords[b]){return}
|
||||
s.blenderRegion(d,s.group[d.ke][d.id].cords[b],tx)
|
||||
}
|
||||
delete(d.image)
|
||||
}
|
||||
|
||||
s.MainEventController=function(d,cn,tx){
|
||||
switch(d.f){
|
||||
case'refreshPlugins':
|
||||
s.findCascades(function(cascades){
|
||||
s.cx({f:'s.tx',data:{f:'detector_cascade_list',cascades:cascades},to:'GRP_'+d.ke})
|
||||
})
|
||||
break;
|
||||
case'readPlugins':
|
||||
s.cx({f:'s.tx',data:{f:'detector_cascade_list',cascades:s.cascadesInDir},to:'GRP_'+d.ke})
|
||||
break;
|
||||
case'init_plugin_as_host':
|
||||
if(!cn){
|
||||
console.log('No CN',d)
|
||||
return
|
||||
}
|
||||
if(d.key!==config.key){
|
||||
console.log(new Date(),'Plugin Key Mismatch',cn.request.connection.remoteAddress,d)
|
||||
cn.emit('init',{ok:false})
|
||||
cn.disconnect()
|
||||
}else{
|
||||
console.log(new Date(),'Plugin Connected to Client',cn.request.connection.remoteAddress)
|
||||
cn.emit('init',{ok:true,plug:config.plug,notice:config.notice,type:config.type})
|
||||
}
|
||||
break;
|
||||
case'init_monitor':
|
||||
if(s.group[d.ke]&&s.group[d.ke][d.id]){
|
||||
s.group[d.ke][d.id].canvas={}
|
||||
s.group[d.ke][d.id].canvasContext={}
|
||||
s.group[d.ke][d.id].blendRegion={}
|
||||
s.group[d.ke][d.id].blendRegionContext={}
|
||||
s.group[d.ke][d.id].lastRegionImageData={}
|
||||
s.group[d.ke][d.id].numberOfTriggers=0
|
||||
delete(s.group[d.ke][d.id].cords)
|
||||
delete(s.group[d.ke][d.id].buffer)
|
||||
}
|
||||
break;
|
||||
case'init_aws_push':
|
||||
// console.log('init_aws')
|
||||
s.group[d.ke][d.id].aws={links:[],complete:0,total:d.total,videos:[],tx:tx}
|
||||
break;
|
||||
case'frame':
|
||||
try{
|
||||
if(!s.group[d.ke]){
|
||||
s.group[d.ke]={}
|
||||
}
|
||||
if(!s.group[d.ke][d.id]){
|
||||
s.group[d.ke][d.id]={
|
||||
canvas:{},
|
||||
canvasContext:{},
|
||||
lastRegionImageData:{},
|
||||
blendRegion:{},
|
||||
blendRegionContext:{},
|
||||
}
|
||||
}
|
||||
if(!s.group[d.ke][d.id].buffer){
|
||||
s.group[d.ke][d.id].buffer=[d.frame];
|
||||
}else{
|
||||
s.group[d.ke][d.id].buffer.push(d.frame)
|
||||
}
|
||||
if(d.frame[d.frame.length-2] === 0xFF && d.frame[d.frame.length-1] === 0xD9){
|
||||
s.group[d.ke][d.id].buffer=Buffer.concat(s.group[d.ke][d.id].buffer);
|
||||
try{
|
||||
d.mon.detector_cascades=JSON.parse(d.mon.detector_cascades)
|
||||
}catch(err){
|
||||
|
||||
}
|
||||
if(d.mon.detector_frame_save==="1"){
|
||||
d.base64=s.group[d.ke][d.id].buffer.toString('base64')
|
||||
}
|
||||
if(d.mon.detector_second==='1'&&d.objectOnly===true){
|
||||
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)
|
||||
})
|
||||
}
|
||||
|
|
@ -34,13 +34,13 @@ nano plugins/openalpr/conf.json
|
|||
Start the plugin.
|
||||
|
||||
```
|
||||
node plugins/openalpr/shinobi-motion.js
|
||||
node plugins/openalpr/shinobi-openalpr.js
|
||||
```
|
||||
|
||||
Or to daemonize with PM2.
|
||||
|
||||
```
|
||||
pm2 start plugins/openalpr/shinobi-motion.js
|
||||
pm2 start plugins/openalpr/shinobi-openalpr.js
|
||||
```
|
||||
|
||||
Doing this will reveal options in the monitor configuration. Shinobi does not need to be restarted when a plugin is initiated or stopped.
|
||||
|
|
|
|||
3
plugins/python-dlib/.gitignore
vendored
Normal file
3
plugins/python-dlib/.gitignore
vendored
Normal file
|
|
@ -0,0 +1,3 @@
|
|||
conf.json
|
||||
faces
|
||||
data
|
||||
66
plugins/python-dlib/INSTALL.sh
Normal file
66
plugins/python-dlib/INSTALL.sh
Normal file
|
|
@ -0,0 +1,66 @@
|
|||
#!/bin/bash
|
||||
echo "-----------------------------------------------"
|
||||
echo "-- Installing Python Dlib Plugin for Shinobi --"
|
||||
echo "-----------------------------------------------"
|
||||
echo "-----------------------------------"
|
||||
if [ ! -e "./conf.json" ]; then
|
||||
echo "Creating conf.json"
|
||||
sudo cp conf.sample.json conf.json
|
||||
else
|
||||
echo "conf.json already exists..."
|
||||
fi
|
||||
echo "-----------------------------------"
|
||||
sudo apt update -y
|
||||
echo "Installing python3"
|
||||
sudo apt install python3 python3-dev python3-pip -y
|
||||
echo "-----------------------------------"
|
||||
sudo add-apt-repository ppa:ubuntu-toolchain-r/test -y
|
||||
sudo apt update
|
||||
sudo apt-get install gcc-6 g++-6 -y && sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-6 60 --slave /usr/bin/g++ g++ /usr/bin/g++-6
|
||||
echo "-----------------------------------"
|
||||
if ! [ -x "$(command -v nvidia-smi)" ]; then
|
||||
echo "You need to install NVIDIA Drivers to use this."
|
||||
echo "inside the Shinobi directory run the following :"
|
||||
echo "sh INSTALL/cuda9-part1.sh"
|
||||
exit 1
|
||||
else
|
||||
echo "NVIDIA Drivers found..."
|
||||
echo "$(nvidia-smi |grep 'Driver Version')"
|
||||
fi
|
||||
echo "-----------------------------------"
|
||||
if [ ! -d "/usr/local/cuda" ]; then
|
||||
echo "You need to install CUDA Toolkit to use this."
|
||||
echo "inside the Shinobi directory run the following :"
|
||||
echo "sh INSTALL/cuda9-part2-after-reboot.sh"
|
||||
exit 1
|
||||
else
|
||||
echo "CUDA Toolkit found..."
|
||||
fi
|
||||
echo "-----------------------------------"
|
||||
if ! [ -x "$(command -v opencv_version)" ]; then
|
||||
echo "You need to install OpenCV with CUDA first."
|
||||
echo "inside the Shinobi directory run the following :"
|
||||
echo "sh INSTALL/opencv-cuda.sh"
|
||||
exit 1
|
||||
else
|
||||
echo "OpenCV found... : $(opencv_version)"
|
||||
fi
|
||||
echo "-----------------------------------"
|
||||
echo "Getting new pip..."
|
||||
pip3 install --upgrade pip
|
||||
pip install --user --upgrade pip
|
||||
echo "Smoking pips..."
|
||||
pip3 install flask_socketio
|
||||
pip3 install flask
|
||||
pip3 install numpy
|
||||
pip3 install gevent gevent-websocket
|
||||
export PATH=/usr/local/cuda/bin:$PATH
|
||||
echo "Installing Dlib..."
|
||||
cd /opt
|
||||
git clone https://github.com/davisking/dlib.git dlib
|
||||
cd dlib
|
||||
cmake -DCUDA_CUDART_LIBRARY=/usr/local/cuda/lib64/libcudart.so
|
||||
make install
|
||||
pip3 install dlib
|
||||
echo "Start the plugin with pm2 like so :"
|
||||
echo "pm2 start shinobi-python-dlib.js"
|
||||
72
plugins/python-dlib/README.md
Normal file
72
plugins/python-dlib/README.md
Normal file
|
|
@ -0,0 +1,72 @@
|
|||
# Python DLIB
|
||||
|
||||
> This plugin requires the use of port `7990` by default. You can specify a different port by adding `pythonPort` to your plugin's conf.json.
|
||||
|
||||
**Ubuntu and Debian only**
|
||||
|
||||
Go to the Shinobi directory. **/home/Shinobi** is the default directory.
|
||||
|
||||
```
|
||||
cd /home/Shinobi/plugins/python-dlib
|
||||
```
|
||||
|
||||
Copy the config file.
|
||||
|
||||
```
|
||||
sh INSTALL.sh
|
||||
```
|
||||
|
||||
Start the plugin.
|
||||
|
||||
```
|
||||
pm2 start shinobi-python-dlib.js
|
||||
```
|
||||
|
||||
Doing this will reveal options in the monitor configuration. Shinobi does not need to be restarted when a plugin is initiated or stopped.
|
||||
|
||||
## Run the plugin as a Host
|
||||
> The main app (Shinobi) will be the client and the plugin will be the host. The purpose of allowing this method is so that you can use one plugin for multiple Shinobi instances. Allowing you to easily manage connections without starting multiple processes.
|
||||
|
||||
Edit your plugins configuration file. Set the `hostPort` **to be different** than the `listening port for camera.js`.
|
||||
|
||||
```
|
||||
nano conf.json
|
||||
```
|
||||
|
||||
Here is a sample of a Host configuration for the plugin.
|
||||
- `plug` is the name of the plugin corresponding in the main configuration file.
|
||||
- `https` choose if you want to use SSL or not. Default is `false`.
|
||||
- `hostPort` can be any available port number. **Don't make this the same port number as Shinobi.** Default is `8082`.
|
||||
- `type` tells the main application (Shinobi) what kind of plugin it is. In this case it is a detector.
|
||||
|
||||
```
|
||||
{
|
||||
"plug":"PythonDlib",
|
||||
"hostPort":8082,
|
||||
"key":"SomeOpenALPRkeySoPeopleDontMessWithYourShinobi",
|
||||
"mode":"host",
|
||||
"type":"detector"
|
||||
}
|
||||
```
|
||||
|
||||
Now modify the **main configuration file** located in the main directory of Shinobi. *Where you currently should be.*
|
||||
|
||||
```
|
||||
nano conf.json
|
||||
```
|
||||
|
||||
Add the `plugins` array if you don't already have it. Add the following *object inside the array*.
|
||||
|
||||
```
|
||||
"plugins":[
|
||||
{
|
||||
"id" : "PythonDlib",
|
||||
"https" : false,
|
||||
"host" : "localhost",
|
||||
"port" : 8082,
|
||||
"key" : "SomeOpenALPRkeySoPeopleDontMessWithYourShinobi",
|
||||
"mode" : "host",
|
||||
"type" : "detector"
|
||||
}
|
||||
],
|
||||
```
|
||||
1
plugins/python-dlib/bootPy.sh
Normal file
1
plugins/python-dlib/bootPy.sh
Normal file
|
|
@ -0,0 +1 @@
|
|||
python3 -u $@
|
||||
10
plugins/python-dlib/conf.sample.json
Normal file
10
plugins/python-dlib/conf.sample.json
Normal file
|
|
@ -0,0 +1,10 @@
|
|||
{
|
||||
"plug":"PythonDlib",
|
||||
"host":"localhost",
|
||||
"port":8080,
|
||||
"pythonPort":7990,
|
||||
"hostPort":8082,
|
||||
"key":"SomeOpenALPRkeySoPeopleDontMessWithYourShinobi",
|
||||
"mode":"client",
|
||||
"type":"detector"
|
||||
}
|
||||
18
plugins/python-dlib/package.json
Normal file
18
plugins/python-dlib/package.json
Normal file
|
|
@ -0,0 +1,18 @@
|
|||
{
|
||||
"name": "shinobi-python-dlib",
|
||||
"version": "1.0.0",
|
||||
"description": "DLIB plugin for Shinobi that uses Python functions for detection.",
|
||||
"main": "shinobi-python-dlib.js",
|
||||
"dependencies": {
|
||||
"socket.io-client": "^1.7.4",
|
||||
"express": "^4.16.2",
|
||||
"moment": "^2.19.2",
|
||||
"socket.io": "^2.0.4"
|
||||
},
|
||||
"devDependencies": {},
|
||||
"scripts": {
|
||||
"test": "echo \"Error: no test specified\" && exit 1"
|
||||
},
|
||||
"author": "Moe Alam",
|
||||
"license": "ISC"
|
||||
}
|
||||
113
plugins/python-dlib/pumpkin.py
Normal file
113
plugins/python-dlib/pumpkin.py
Normal file
|
|
@ -0,0 +1,113 @@
|
|||
from flask import Flask, request, jsonify, render_template
|
||||
from flask_socketio import SocketIO, emit
|
||||
from PIL import Image
|
||||
import face_recognition
|
||||
import cv2
|
||||
import os
|
||||
import json
|
||||
import numpy as np
|
||||
import sys
|
||||
|
||||
dirname = sys.argv[1]
|
||||
|
||||
try:
|
||||
with open("{}/conf.json".format(dirname)) as json_file:
|
||||
config = json.load(json_file)
|
||||
httpPort = config['pythonPort']
|
||||
try:
|
||||
httpPort
|
||||
except NameError:
|
||||
httpPort = 7990
|
||||
except Exception as e:
|
||||
print("conf.json not found.")
|
||||
httpPort = 7990
|
||||
|
||||
# Load Flask
|
||||
app = Flask("DLIB for Shinobi (Pumpkin Pie)")
|
||||
socketio = SocketIO(app)
|
||||
# Silence Flask
|
||||
# import logging
|
||||
# log = logging.getLogger('werkzeug')
|
||||
# log.setLevel(logging.ERROR)
|
||||
|
||||
#check for faces dir
|
||||
facesDir = "{}/faces/".format(dirname)
|
||||
if not os.path.exists(facesDir):
|
||||
os.makedirs(facesDir)
|
||||
|
||||
# load faces
|
||||
included_extensions = ['jpg','jpeg', 'bmp', 'png', 'gif']
|
||||
file_names = [fn for fn in os.listdir(facesDir)
|
||||
if any(fn.endswith(ext) for ext in included_extensions)]
|
||||
known_faces = []
|
||||
face_locations = []
|
||||
face_encodings = []
|
||||
face_names = []
|
||||
|
||||
for faceFile in file_names:
|
||||
face = face_recognition.load_image_file(facesDir+faceFile)
|
||||
face_encoding = face_recognition.face_encodings(face)[0]
|
||||
known_faces.append(face_encoding)
|
||||
|
||||
# detection function
|
||||
def spark(filepath):
|
||||
try:
|
||||
filepath
|
||||
except NameError:
|
||||
return "File path not found."
|
||||
img = cv2.imread(filepath)
|
||||
returnData = []
|
||||
frame = img[:, :, ::-1]
|
||||
|
||||
# Find all the faces and face encodings in the current frame of video
|
||||
face_locations = face_recognition.face_locations(frame)
|
||||
face_encodings = face_recognition.face_encodings(frame, face_locations)
|
||||
face_names = []
|
||||
for (top, right, bottom, left), face_encoding in zip(face_locations, face_encodings):
|
||||
# See if the face is a match for the known face(s)
|
||||
matrix = {}
|
||||
matrix["coordinates"] = [
|
||||
{"x" : left, "y" : top},
|
||||
{"x" : right, "y" : top},
|
||||
{"x" : right, "y" : bottom},
|
||||
{"x" : left, "y" : bottom}
|
||||
]
|
||||
(left, top), (right, bottom)
|
||||
match = face_recognition.compare_faces(known_faces, face_encoding, tolerance=0.50)
|
||||
if True in match:
|
||||
first_match_index = match.index(True)
|
||||
name = file_names[first_match_index]
|
||||
matrix["tag"] = name
|
||||
returnData.append(matrix)
|
||||
return returnData
|
||||
|
||||
# bake the image data by a file path
|
||||
# POST body contains the "img" variable. The value should be to a local image path.
|
||||
# Example : /dev/shm/streams/[GROUP_KEY]/[MONITOR_ID]/s.jpg
|
||||
@app.route('/', methods=['GET'])
|
||||
def index():
|
||||
return "Pumpkin.py is running. This web interface should NEVER be accessible remotely. The Node.js plugin that runs this script should only be allowed accessible remotely."
|
||||
|
||||
# bake the image data by a file path
|
||||
# POST body contains the "img" variable. The value should be to a local image path.
|
||||
# Example : /dev/shm/streams/[GROUP_KEY]/[MONITOR_ID]/s.jpg
|
||||
@app.route('/post', methods=['POST'])
|
||||
def post():
|
||||
filepath = request.form['img']
|
||||
return jsonify(spark(filepath))
|
||||
|
||||
# bake the image data by a file path
|
||||
# GET string contains the "img" variable. The value should be to a local image path.
|
||||
# Example : /dev/shm/streams/[GROUP_KEY]/[MONITOR_ID]/s.jpg
|
||||
@app.route('/get', methods=['GET'])
|
||||
def get():
|
||||
filepath = request.args.get('img')
|
||||
return jsonify(spark(filepath))
|
||||
|
||||
@socketio.on('f')
|
||||
def receiveMessage(message):
|
||||
emit('f',{'id':message.get("id"),'data':spark(message.get("path"))})
|
||||
|
||||
# quick-and-dirty start
|
||||
if __name__ == '__main__':
|
||||
socketio.run(app, port=httpPort)
|
||||
292
plugins/python-dlib/shinobi-python-dlib.js
Normal file
292
plugins/python-dlib/shinobi-python-dlib.js
Normal file
|
|
@ -0,0 +1,292 @@
|
|||
//
|
||||
// Shinobi - Python DLIB Plugin
|
||||
// Copyright (C) 2016-2025 Moe Alam, moeiscool
|
||||
//
|
||||
// # Donate
|
||||
//
|
||||
// If you like what I am doing here and want me to continue please consider donating :)
|
||||
// PayPal : paypal@m03.ca
|
||||
//
|
||||
process.on('uncaughtException', function (err) {
|
||||
console.error('uncaughtException',err);
|
||||
});
|
||||
//main vars
|
||||
var fs=require('fs');
|
||||
var exec = require('child_process').exec;
|
||||
var spawn = require('child_process').spawn;
|
||||
var moment = require('moment');
|
||||
var http = require('http');
|
||||
var express = require('express');
|
||||
var socketIoClient = require('socket.io-client');
|
||||
var config = require('./conf.json');
|
||||
var http = require('http'),
|
||||
app = express(),
|
||||
server = http.createServer(app);
|
||||
s={
|
||||
group:{},
|
||||
dir:{},
|
||||
isWin:(process.platform==='win32'),
|
||||
s:function(json){return JSON.stringify(json,null,3)}
|
||||
}
|
||||
s.checkCorrectPathEnding=function(x){
|
||||
var length=x.length
|
||||
if(x.charAt(length-1)!=='/'){
|
||||
x=x+'/'
|
||||
}
|
||||
return x.replace('__DIR__',__dirname)
|
||||
}
|
||||
s.debugLog = function(){
|
||||
if(config.debugLog === true){
|
||||
console.log(new Date(),arguments)
|
||||
if(config.debugLogVerbose === true){
|
||||
console.log(new Error())
|
||||
}
|
||||
}
|
||||
}
|
||||
if(!config.port){config.port=8080}
|
||||
if(!config.pythonScript){config.pythonScript=__dirname+'/pumpkin.py'}
|
||||
if(!config.pythonPort){config.pythonPort=7990}
|
||||
if(!config.hostPort){config.hostPort=8082}
|
||||
if(config.systemLog===undefined){config.systemLog=true}
|
||||
//default stream folder check
|
||||
if(!config.streamDir){
|
||||
if(s.isWin===false){
|
||||
config.streamDir='/dev/shm'
|
||||
}else{
|
||||
config.streamDir=config.windowsTempDir
|
||||
}
|
||||
if(!fs.existsSync(config.streamDir)){
|
||||
config.streamDir=__dirname+'/streams/'
|
||||
}else{
|
||||
config.streamDir+='/streams/'
|
||||
}
|
||||
}
|
||||
s.dir.streams=config.streamDir;
|
||||
//streams dir
|
||||
if(!fs.existsSync(s.dir.streams)){
|
||||
fs.mkdirSync(s.dir.streams);
|
||||
}
|
||||
s.gid=function(x){
|
||||
if(!x){x=10};var t = "";var p = "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789";
|
||||
for( var i=0; i < x; i++ )
|
||||
t += p.charAt(Math.floor(Math.random() * p.length));
|
||||
return t;
|
||||
};
|
||||
s.getRequest = function(url,callback){
|
||||
return http.get(url, function(res){
|
||||
var body = '';
|
||||
res.on('data', function(chunk){
|
||||
body += chunk;
|
||||
});
|
||||
res.on('end',function(){
|
||||
try{body = JSON.parse(body)}catch(err){}
|
||||
callback(body)
|
||||
});
|
||||
}).on('error', function(e){
|
||||
// s.systemLog("Get Snapshot Error", e);
|
||||
});
|
||||
}
|
||||
s.multiplerHeight = 1
|
||||
s.multiplerWidth = 1
|
||||
s.detectObject=function(buffer,d,tx){
|
||||
d.tmpFile=s.gid(5)+'.jpg'
|
||||
if(!fs.existsSync(s.dir.streams)){
|
||||
fs.mkdirSync(s.dir.streams);
|
||||
}
|
||||
d.dir=s.dir.streams+d.ke+'/'
|
||||
if(!fs.existsSync(d.dir)){
|
||||
fs.mkdirSync(d.dir);
|
||||
}
|
||||
d.dir=s.dir.streams+d.ke+'/'+d.id+'/'
|
||||
if(!fs.existsSync(d.dir)){
|
||||
fs.mkdirSync(d.dir);
|
||||
}
|
||||
fs.writeFile(d.dir+d.tmpFile,buffer,function(err){
|
||||
if(err) return s.systemLog(err);
|
||||
if(s.isPythonRunning === false){
|
||||
return console.log('Python Script is not Running.')
|
||||
}
|
||||
var callbackId = s.gid(10)
|
||||
s.group[d.ke][d.id].sendToPython({path:d.dir+d.tmpFile,id:callbackId},function(data){
|
||||
console.log('returned',data)
|
||||
if(data.length > 0){
|
||||
var mats=[]
|
||||
data.forEach(function(v){
|
||||
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));
|
||||
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))
|
||||
mats.push({
|
||||
x:v.coordinates[0].x,
|
||||
y:v.coordinates[0].y,
|
||||
width: width,
|
||||
height: height,
|
||||
confidence:v.confidence,
|
||||
tag:v.tag
|
||||
})
|
||||
})
|
||||
tx({
|
||||
f:'trigger',
|
||||
id:d.id,
|
||||
ke:d.ke,
|
||||
details:{
|
||||
plug:config.plug,
|
||||
name:'dlib',
|
||||
reason:'object',
|
||||
matrices:mats,
|
||||
imgHeight:d.mon.detector_scale_y,
|
||||
imgWidth:d.mon.detector_scale_x
|
||||
}
|
||||
})
|
||||
}
|
||||
delete(s.callbacks[callbackId])
|
||||
exec('rm -rf '+d.dir+d.tmpFile,{encoding:'utf8'})
|
||||
})
|
||||
})
|
||||
}
|
||||
s.systemLog=function(q,w,e){
|
||||
if(w===undefined){return}
|
||||
if(!w){w=''}
|
||||
if(!e){e=''}
|
||||
if(config.systemLog===true){
|
||||
return console.log(moment().format(),q,w,e)
|
||||
}
|
||||
}
|
||||
s.MainEventController=function(d,cn,tx){
|
||||
switch(d.f){
|
||||
case'init_plugin_as_host':
|
||||
if(!cn){
|
||||
console.log('No CN',d)
|
||||
return
|
||||
}
|
||||
if(d.key!==config.key){
|
||||
console.log(new Date(),'Plugin Key Mismatch',cn.request.connection.remoteAddress,d)
|
||||
cn.emit('init',{ok:false})
|
||||
cn.disconnect()
|
||||
}else{
|
||||
console.log(new Date(),'Plugin Connected to Client',cn.request.connection.remoteAddress)
|
||||
cn.emit('init',{ok:true,plug:config.plug,notice:config.notice,type:config.type})
|
||||
}
|
||||
break;
|
||||
case'init_monitor':
|
||||
if(s.group[d.ke]&&s.group[d.ke][d.id]){
|
||||
delete(s.group[d.ke][d.id].buffer)
|
||||
}
|
||||
break;
|
||||
case'frame':
|
||||
try{
|
||||
if(!s.group[d.ke]){
|
||||
s.group[d.ke]={}
|
||||
}
|
||||
if(!s.group[d.ke][d.id]){
|
||||
s.group[d.ke][d.id]={
|
||||
sendToPython : s.createCameraBridgeToPython(d.ke+d.id)
|
||||
}
|
||||
}
|
||||
if(!s.group[d.ke][d.id].buffer){
|
||||
s.group[d.ke][d.id].buffer=[d.frame];
|
||||
}else{
|
||||
s.group[d.ke][d.id].buffer.push(d.frame)
|
||||
}
|
||||
if(d.frame[d.frame.length-2] === 0xFF && d.frame[d.frame.length-1] === 0xD9){
|
||||
s.detectObject(Buffer.concat(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 = socketIoClient('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)
|
||||
})
|
||||
}
|
||||
|
||||
//Start Python Controller
|
||||
s.callbacks = {}
|
||||
s.createCameraBridgeToPython = function(uniqueId){
|
||||
var pythonIo = socketIoClient('ws://localhost:'+config.pythonPort,{transports : ['websocket']});
|
||||
var sendToPython = function(data,callback){
|
||||
s.callbacks[data.id] = callback
|
||||
pythonIo.emit('f',data)
|
||||
}
|
||||
pythonIo.on('connect',function(d){
|
||||
s.debugLog(uniqueId+' is Connected from Python')
|
||||
})
|
||||
pythonIo.on('disconnect',function(d){
|
||||
s.debugLog(uniqueId+' is Disconnected from Python')
|
||||
setTimeout(function(){
|
||||
pythonIo.connect();
|
||||
s.debugLog(uniqueId+' is Attempting to Reconect to Python')
|
||||
},3000)
|
||||
})
|
||||
pythonIo.on('f',function(d){
|
||||
if(s.callbacks[d.id]){
|
||||
s.callbacks[d.id](d.data)
|
||||
delete(s.callbacks[d.id])
|
||||
}
|
||||
})
|
||||
return sendToPython
|
||||
}
|
||||
|
||||
|
||||
//Start Python Daemon
|
||||
process.env.PYTHONUNBUFFERED = 1;
|
||||
s.createPythonProcess = function(){
|
||||
s.isPythonRunning = false
|
||||
s.pythonScript = spawn('sh',[__dirname+'/bootPy.sh',config.pythonScript,__dirname]);
|
||||
var onStdErr = function(data){
|
||||
s.debugLog(data.toString())
|
||||
}
|
||||
var onStdOut = function(data){
|
||||
s.debugLog(data.toString())
|
||||
}
|
||||
setTimeout(function(){
|
||||
s.isPythonRunning = true
|
||||
},5000)
|
||||
s.pythonScript.stderr.on('data',onStdErr);
|
||||
|
||||
s.pythonScript.stdout.on('data',onStdOut);
|
||||
|
||||
s.pythonScript.on('close', function () {
|
||||
s.debugLog('Python CLOSED')
|
||||
});
|
||||
}
|
||||
s.createPythonProcess()
|
||||
5
plugins/python-yolo/.gitignore
vendored
Normal file
5
plugins/python-yolo/.gitignore
vendored
Normal file
|
|
@ -0,0 +1,5 @@
|
|||
conf.json
|
||||
cascades
|
||||
cfg
|
||||
weights
|
||||
data
|
||||
109
plugins/python-yolo/INSTALL.sh
Normal file
109
plugins/python-yolo/INSTALL.sh
Normal file
|
|
@ -0,0 +1,109 @@
|
|||
#!/bin/bash
|
||||
echo "-----------------------------------------------"
|
||||
echo "-- Installing Python Yolo Plugin for Shinobi --"
|
||||
echo "-----------------------------------------------"
|
||||
echo "-----------------------------------"
|
||||
if [ ! -d "weights" ]; then
|
||||
echo "Downloading yolov3 weights..."
|
||||
mkdir weights
|
||||
wget -O weights/yolov3.weights https://pjreddie.com/media/files/yolov3.weights
|
||||
else
|
||||
echo "yolov3 weights found..."
|
||||
fi
|
||||
echo "-----------------------------------"
|
||||
if [ ! -d "cfg" ]; then
|
||||
echo "Downloading yolov3 cfg"
|
||||
mkdir cfg
|
||||
wget -O cfg/coco.data https://raw.githubusercontent.com/pjreddie/darknet/master/cfg/coco.data
|
||||
wget -O cfg/yolov3.cfg https://raw.githubusercontent.com/pjreddie/darknet/master/cfg/yolov3.cfg
|
||||
else
|
||||
echo "yolov3 cfg found..."
|
||||
fi
|
||||
echo "-----------------------------------"
|
||||
if [ ! -d "data" ]; then
|
||||
echo "Downloading yolov3 data"
|
||||
mkdir data
|
||||
wget -O data/coco.names https://raw.githubusercontent.com/pjreddie/darknet/master/data/coco.names
|
||||
else
|
||||
echo "yolov3 data found..."
|
||||
fi
|
||||
echo "-----------------------------------"
|
||||
if [ ! -e "./conf.json" ]; then
|
||||
echo "Creating conf.json"
|
||||
sudo cp conf.sample.json conf.json
|
||||
else
|
||||
echo "conf.json already exists..."
|
||||
fi
|
||||
echo "-----------------------------------"
|
||||
sudo apt update -y
|
||||
sudo apt-get install libxml2-dev libxslt-dev libxslt1-dev zlib1g-dev -y
|
||||
echo "Installing python3"
|
||||
sudo apt install python3 python3-dev python3-pip -y
|
||||
sudo apt install python3-lxml libxml2-dev -y
|
||||
echo "-----------------------------------"
|
||||
if ! [ -x "$(command -v gcc-6)" ]; then
|
||||
echo "Installing gcc-6 and g++-6"
|
||||
sudo add-apt-repository ppa:ubuntu-toolchain-r/test -y
|
||||
sudo apt-get install gcc-6 g++-6 -y && sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-6 60 --slave /usr/bin/g++ g++ /usr/bin/g++-6
|
||||
else
|
||||
echo "gcc-6 and g++-6 found..."
|
||||
fi
|
||||
echo "-----------------------------------"
|
||||
if ! [ -x "$(command -v nvidia-smi)" ]; then
|
||||
echo "You need to install NVIDIA Drivers to use this."
|
||||
echo "inside the Shinobi directory run the following :"
|
||||
echo "sh INSTALL/cuda9-part1.sh"
|
||||
exit 1
|
||||
else
|
||||
echo "NVIDIA Drivers found..."
|
||||
echo "$(nvidia-smi |grep 'Driver Version')"
|
||||
fi
|
||||
echo "-----------------------------------"
|
||||
if [ ! -d "/usr/local/cuda" ]; then
|
||||
echo "You need to install CUDA Toolkit to use this."
|
||||
echo "inside the Shinobi directory run the following :"
|
||||
echo "sh INSTALL/cuda9-part2-after-reboot.sh"
|
||||
exit 1
|
||||
else
|
||||
echo "CUDA Toolkit found..."
|
||||
fi
|
||||
echo "-----------------------------------"
|
||||
if ! [ -x "$(command -v opencv_version)" ]; then
|
||||
echo "You need to install OpenCV with CUDA first."
|
||||
echo "inside the Shinobi directory run the following :"
|
||||
echo "sh INSTALL/opencv-cuda.sh"
|
||||
exit 1
|
||||
else
|
||||
echo "OpenCV found... : $(opencv_version)"
|
||||
fi
|
||||
echo "-----------------------------------"
|
||||
echo "Getting new pip..."
|
||||
pip3 install --upgrade pip
|
||||
pip install --user --upgrade pip
|
||||
echo "Smoking pips..."
|
||||
pip3 install flask_socketio
|
||||
pip3 install flask
|
||||
pip3 install numpy
|
||||
pip3 install gevent gevent-websocket
|
||||
export PATH=/usr/local/cuda/bin:$PATH
|
||||
pip3 install lxml
|
||||
pip3 install numpy
|
||||
pip3 install cython
|
||||
echo "Installing Darknet..."
|
||||
cd /opt
|
||||
git clone https://github.com/pjreddie/darknet.git darknet
|
||||
cd darknet
|
||||
make
|
||||
cd ..
|
||||
echo "Installing YOLO3-4-Py"
|
||||
echo "Learn more about this wrapper here : https://github.com/madhawav/YOLO3-4-Py"
|
||||
git clone https://github.com/madhawav/YOLO3-4-Py.git YOLO3-4-Py
|
||||
cd YOLO3-4-Py
|
||||
export GPU=1
|
||||
export OPENCV=1
|
||||
pip3 install .
|
||||
apt remove libpython-all-dev python-all python-all-dev python-asn1crypto python-cffi-backend python-crypto python-cryptography python-dbus python-enum34 python-gi python-idna python-ipaddress python-keyring python-keyrings.alt python-pkg-resources python-secretstorage python-setuptools python-six python-wheel python-xdg -y
|
||||
echo "Done Installing Darknet..."
|
||||
export PATH=/opt/darknet:$PATH
|
||||
echo "Start the plugin with pm2 like so :"
|
||||
echo "pm2 start shinobi-python-yolo.js"
|
||||
72
plugins/python-yolo/README.md
Normal file
72
plugins/python-yolo/README.md
Normal file
|
|
@ -0,0 +1,72 @@
|
|||
# Python Yolo
|
||||
|
||||
> This plugin requires the use of port `7990` by default. You can specify a different port by adding `pythonPort` to your plugin's conf.json.
|
||||
|
||||
**Ubuntu and Debian only**
|
||||
|
||||
Go to the Shinobi directory. **/home/Shinobi** is the default directory.
|
||||
|
||||
```
|
||||
cd /home/Shinobi/plugins/python-yolo
|
||||
```
|
||||
|
||||
Copy the config file.
|
||||
|
||||
```
|
||||
sh INSTALL.sh
|
||||
```
|
||||
|
||||
Start the plugin.
|
||||
|
||||
```
|
||||
pm2 start shinobi-python-yolo.js
|
||||
```
|
||||
|
||||
Doing this will reveal options in the monitor configuration. Shinobi does not need to be restarted when a plugin is initiated or stopped.
|
||||
|
||||
## Run the plugin as a Host
|
||||
> The main app (Shinobi) will be the client and the plugin will be the host. The purpose of allowing this method is so that you can use one plugin for multiple Shinobi instances. Allowing you to easily manage connections without starting multiple processes.
|
||||
|
||||
Edit your plugins configuration file. Set the `hostPort` **to be different** than the `listening port for camera.js`.
|
||||
|
||||
```
|
||||
nano conf.json
|
||||
```
|
||||
|
||||
Here is a sample of a Host configuration for the plugin.
|
||||
- `plug` is the name of the plugin corresponding in the main configuration file.
|
||||
- `https` choose if you want to use SSL or not. Default is `false`.
|
||||
- `hostPort` can be any available port number. **Don't make this the same port number as Shinobi.** Default is `8082`.
|
||||
- `type` tells the main application (Shinobi) what kind of plugin it is. In this case it is a detector.
|
||||
|
||||
```
|
||||
{
|
||||
"plug":"PythonYolo",
|
||||
"hostPort":8082,
|
||||
"key":"SomeOpenALPRkeySoPeopleDontMessWithYourShinobi",
|
||||
"mode":"host",
|
||||
"type":"detector"
|
||||
}
|
||||
```
|
||||
|
||||
Now modify the **main configuration file** located in the main directory of Shinobi. *Where you currently should be.*
|
||||
|
||||
```
|
||||
nano conf.json
|
||||
```
|
||||
|
||||
Add the `plugins` array if you don't already have it. Add the following *object inside the array*.
|
||||
|
||||
```
|
||||
"plugins":[
|
||||
{
|
||||
"id" : "PythonYolo",
|
||||
"https" : false,
|
||||
"host" : "localhost",
|
||||
"port" : 8082,
|
||||
"key" : "SomeOpenALPRkeySoPeopleDontMessWithYourShinobi",
|
||||
"mode" : "host",
|
||||
"type" : "detector"
|
||||
}
|
||||
],
|
||||
```
|
||||
1
plugins/python-yolo/bootPy.sh
Normal file
1
plugins/python-yolo/bootPy.sh
Normal file
|
|
@ -0,0 +1 @@
|
|||
python3 -u $@
|
||||
10
plugins/python-yolo/conf.sample.json
Normal file
10
plugins/python-yolo/conf.sample.json
Normal file
|
|
@ -0,0 +1,10 @@
|
|||
{
|
||||
"plug":"PythonYolo",
|
||||
"host":"localhost",
|
||||
"port":8080,
|
||||
"pythonPort":7990,
|
||||
"hostPort":8082,
|
||||
"key":"SomeOpenALPRkeySoPeopleDontMessWithYourShinobi",
|
||||
"mode":"client",
|
||||
"type":"detector"
|
||||
}
|
||||
14
plugins/python-yolo/download-weights.sh
Normal file
14
plugins/python-yolo/download-weights.sh
Normal file
|
|
@ -0,0 +1,14 @@
|
|||
#!/usr/bin/env bash
|
||||
|
||||
echo "Downloading config files..."
|
||||
|
||||
mkdir cfg
|
||||
wget -O cfg/coco.data https://raw.githubusercontent.com/pjreddie/darknet/master/cfg/coco.data
|
||||
wget -O cfg/yolov3.cfg https://raw.githubusercontent.com/pjreddie/darknet/master/cfg/yolov3.cfg
|
||||
|
||||
mkdir data
|
||||
wget -O data/coco.names https://raw.githubusercontent.com/pjreddie/darknet/master/data/coco.names
|
||||
|
||||
echo "Downloading yolov3 weights"
|
||||
mkdir weights
|
||||
wget -O weights/yolov3.weights https://pjreddie.com/media/files/yolov3.weights
|
||||
18
plugins/python-yolo/package.json
Normal file
18
plugins/python-yolo/package.json
Normal file
|
|
@ -0,0 +1,18 @@
|
|||
{
|
||||
"name": "shinobi-python-yolo",
|
||||
"version": "1.0.0",
|
||||
"description": "YOLOv3 plugin for Shinobi that uses Python functions for detection.",
|
||||
"main": "shinobi-python-yolo.js",
|
||||
"dependencies": {
|
||||
"socket.io-client": "^1.7.4",
|
||||
"express": "^4.16.2",
|
||||
"moment": "^2.19.2",
|
||||
"socket.io": "^2.0.4"
|
||||
},
|
||||
"devDependencies": {},
|
||||
"scripts": {
|
||||
"test": "echo \"Error: no test specified\" && exit 1"
|
||||
},
|
||||
"author": "Moe Alam",
|
||||
"license": "ISC"
|
||||
}
|
||||
103
plugins/python-yolo/pumpkin.py
Normal file
103
plugins/python-yolo/pumpkin.py
Normal file
|
|
@ -0,0 +1,103 @@
|
|||
from flask import Flask, request, jsonify, render_template
|
||||
from flask_socketio import SocketIO, emit
|
||||
from pydarknet import Detector, Image
|
||||
import cv2
|
||||
import os
|
||||
import json
|
||||
import numpy as np
|
||||
import sys
|
||||
|
||||
dirname = sys.argv[1]
|
||||
|
||||
try:
|
||||
with open("{}/conf.json".format(dirname)) as json_file:
|
||||
config = json.load(json_file)
|
||||
httpPort = config['pythonPort']
|
||||
try:
|
||||
httpPort
|
||||
except NameError:
|
||||
httpPort = 7990
|
||||
except Exception as e:
|
||||
print("conf.json not found.")
|
||||
httpPort = 7990
|
||||
|
||||
# Load Flask
|
||||
app = Flask("YOLOv3 for Shinobi (Pumpkin Pie)")
|
||||
socketio = SocketIO(app)
|
||||
# Silence Flask
|
||||
import logging
|
||||
log = logging.getLogger('werkzeug')
|
||||
log.setLevel(logging.ERROR)
|
||||
|
||||
# Load Darknet
|
||||
net = Detector(bytes("{}/cfg/yolov3.cfg".format(dirname), encoding="utf-8"), bytes("{}/weights/yolov3.weights".format(dirname), encoding="utf-8"), 0, bytes("{}/cfg/coco.data".format(dirname),encoding="utf-8"))
|
||||
|
||||
def spark(filepath):
|
||||
try:
|
||||
filepath
|
||||
except NameError:
|
||||
return "File path not found."
|
||||
img = cv2.imread(filepath)
|
||||
|
||||
img2 = Image(img)
|
||||
|
||||
# r = net.classify(img2)
|
||||
results = net.detect(img2)
|
||||
returnData = '[]'
|
||||
try:
|
||||
new_list = []
|
||||
for item in results:
|
||||
sub_list = {}
|
||||
i = 0
|
||||
for sub_item in item:
|
||||
if i == 0:
|
||||
key = 'tag'
|
||||
sub_list[key] = sub_item.decode('utf-8')
|
||||
if i == 1:
|
||||
key = 'confidence'
|
||||
sub_list[key] = sub_item
|
||||
if i == 2:
|
||||
key = 'points'
|
||||
points_list = []
|
||||
for points_item in sub_item:
|
||||
points_list.append(points_item)
|
||||
sub_list[key] = points_list
|
||||
i += 1
|
||||
new_list.append(sub_list)
|
||||
returnData = new_list
|
||||
# returnData = json.dumps(results)
|
||||
except Exception as e:
|
||||
returnData = ',\n'.join(map(str, results))
|
||||
|
||||
return returnData
|
||||
|
||||
# bake the image data by a file path
|
||||
# POST body contains the "img" variable. The value should be to a local image path.
|
||||
# Example : /dev/shm/streams/[GROUP_KEY]/[MONITOR_ID]/s.jpg
|
||||
@app.route('/', methods=['GET'])
|
||||
def index():
|
||||
return "Pumpkin.py is running. This web interface should NEVER be accessible remotely. The Node.js plugin that runs this script should only be allowed accessible remotely."
|
||||
|
||||
# bake the image data by a file path
|
||||
# POST body contains the "img" variable. The value should be to a local image path.
|
||||
# Example : /dev/shm/streams/[GROUP_KEY]/[MONITOR_ID]/s.jpg
|
||||
@app.route('/post', methods=['POST'])
|
||||
def post():
|
||||
filepath = request.form['img']
|
||||
return jsonify(spark(filepath))
|
||||
|
||||
# bake the image data by a file path
|
||||
# GET string contains the "img" variable. The value should be to a local image path.
|
||||
# Example : /dev/shm/streams/[GROUP_KEY]/[MONITOR_ID]/s.jpg
|
||||
@app.route('/get', methods=['GET'])
|
||||
def get():
|
||||
filepath = request.args.get('img')
|
||||
return jsonify(spark(filepath))
|
||||
|
||||
@socketio.on('f')
|
||||
def receiveMessage(message):
|
||||
emit('f',{'id':message.get("id"),'data':spark(message.get("path"))})
|
||||
|
||||
# quick-and-dirty start
|
||||
if __name__ == '__main__':
|
||||
socketio.run(app, port=httpPort)
|
||||
296
plugins/python-yolo/shinobi-python-yolo.js
Normal file
296
plugins/python-yolo/shinobi-python-yolo.js
Normal file
|
|
@ -0,0 +1,296 @@
|
|||
//
|
||||
// Shinobi - Python YOLOv3 Plugin
|
||||
// Copyright (C) 2016-2025 Moe Alam, moeiscool
|
||||
//
|
||||
// # Donate
|
||||
//
|
||||
// If you like what I am doing here and want me to continue please consider donating :)
|
||||
// PayPal : paypal@m03.ca
|
||||
//
|
||||
process.on('uncaughtException', function (err) {
|
||||
console.error('uncaughtException',err);
|
||||
});
|
||||
//main vars
|
||||
var fs=require('fs');
|
||||
var exec = require('child_process').exec;
|
||||
var spawn = require('child_process').spawn;
|
||||
var moment = require('moment');
|
||||
var http = require('http');
|
||||
var express = require('express');
|
||||
var socketIoClient = require('socket.io-client');
|
||||
var config = require('./conf.json');
|
||||
var http = require('http'),
|
||||
app = express(),
|
||||
server = http.createServer(app);
|
||||
s={
|
||||
group:{},
|
||||
dir:{},
|
||||
isWin:(process.platform==='win32'),
|
||||
s:function(json){return JSON.stringify(json,null,3)}
|
||||
}
|
||||
s.checkCorrectPathEnding=function(x){
|
||||
var length=x.length
|
||||
if(x.charAt(length-1)!=='/'){
|
||||
x=x+'/'
|
||||
}
|
||||
return x.replace('__DIR__',__dirname)
|
||||
}
|
||||
s.debugLog = function(){
|
||||
if(config.debugLog === true){
|
||||
console.log(new Date(),arguments)
|
||||
if(config.debugLogVerbose === true){
|
||||
console.log(new Error())
|
||||
}
|
||||
}
|
||||
}
|
||||
if(!config.port){config.port=8080}
|
||||
if(!config.pythonScript){config.pythonScript=__dirname+'/pumpkin.py'}
|
||||
if(!config.pythonPort){config.pythonPort=7990}
|
||||
if(!config.hostPort){config.hostPort=8082}
|
||||
if(config.systemLog===undefined){config.systemLog=true}
|
||||
if(config.alprConfig===undefined){config.alprConfig=__dirname+'/openalpr.conf'}
|
||||
//default stream folder check
|
||||
if(!config.streamDir){
|
||||
if(s.isWin===false){
|
||||
config.streamDir='/dev/shm'
|
||||
}else{
|
||||
config.streamDir=config.windowsTempDir
|
||||
}
|
||||
if(!fs.existsSync(config.streamDir)){
|
||||
config.streamDir=__dirname+'/streams/'
|
||||
}else{
|
||||
config.streamDir+='/streams/'
|
||||
}
|
||||
}
|
||||
s.dir.streams=config.streamDir;
|
||||
//streams dir
|
||||
if(!fs.existsSync(s.dir.streams)){
|
||||
fs.mkdirSync(s.dir.streams);
|
||||
}
|
||||
s.gid=function(x){
|
||||
if(!x){x=10};var t = "";var p = "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789";
|
||||
for( var i=0; i < x; i++ )
|
||||
t += p.charAt(Math.floor(Math.random() * p.length));
|
||||
return t;
|
||||
};
|
||||
s.getRequest = function(url,callback){
|
||||
return http.get(url, function(res){
|
||||
var body = '';
|
||||
res.on('data', function(chunk){
|
||||
body += chunk;
|
||||
});
|
||||
res.on('end',function(){
|
||||
try{body = JSON.parse(body)}catch(err){}
|
||||
callback(body)
|
||||
});
|
||||
}).on('error', function(e){
|
||||
// s.systemLog("Get Snapshot Error", e);
|
||||
});
|
||||
}
|
||||
s.multiplerHeight = 0.75
|
||||
s.multiplerWidth = 0.96
|
||||
s.detectObject=function(buffer,d,tx){
|
||||
d.tmpFile=s.gid(5)+'.jpg'
|
||||
if(!fs.existsSync(s.dir.streams)){
|
||||
fs.mkdirSync(s.dir.streams);
|
||||
}
|
||||
d.dir=s.dir.streams+d.ke+'/'
|
||||
if(!fs.existsSync(d.dir)){
|
||||
fs.mkdirSync(d.dir);
|
||||
}
|
||||
d.dir=s.dir.streams+d.ke+'/'+d.id+'/'
|
||||
if(!fs.existsSync(d.dir)){
|
||||
fs.mkdirSync(d.dir);
|
||||
}
|
||||
fs.writeFile(d.dir+d.tmpFile,buffer,function(err){
|
||||
if(err) return s.systemLog(err);
|
||||
if(s.isPythonRunning === false){
|
||||
return console.log('Python Script is not Running.')
|
||||
}
|
||||
var callbackId = s.gid(10)
|
||||
s.group[d.ke][d.id].sendToPython({path:d.dir+d.tmpFile,id:callbackId},function(data){
|
||||
if(data.length > 0){
|
||||
var mats=[]
|
||||
data.forEach(function(v){
|
||||
mats.push({
|
||||
x:v.points[0] * s.multiplerWidth,
|
||||
y:v.points[1] * s.multiplerHeight,
|
||||
width:v.points[2],
|
||||
height:v.points[3],
|
||||
confidence:v.confidence,
|
||||
tag:v.tag
|
||||
})
|
||||
})
|
||||
tx({
|
||||
f:'trigger',
|
||||
id:d.id,
|
||||
ke:d.ke,
|
||||
details:{
|
||||
plug:config.plug,
|
||||
name:'yolo',
|
||||
reason:'object',
|
||||
matrices:mats,
|
||||
imgHeight:d.mon.detector_scale_y,
|
||||
imgWidth:d.mon.detector_scale_x
|
||||
}
|
||||
})
|
||||
}
|
||||
delete(s.callbacks[callbackId])
|
||||
exec('rm -rf '+d.dir+d.tmpFile,{encoding:'utf8'})
|
||||
})
|
||||
})
|
||||
}
|
||||
s.systemLog=function(q,w,e){
|
||||
if(w===undefined){return}
|
||||
if(!w){w=''}
|
||||
if(!e){e=''}
|
||||
if(config.systemLog===true){
|
||||
return console.log(moment().format(),q,w,e)
|
||||
}
|
||||
}
|
||||
s.MainEventController=function(d,cn,tx){
|
||||
switch(d.f){
|
||||
case'init_plugin_as_host':
|
||||
if(!cn){
|
||||
console.log('No CN',d)
|
||||
return
|
||||
}
|
||||
if(d.key!==config.key){
|
||||
console.log(new Date(),'Plugin Key Mismatch',cn.request.connection.remoteAddress,d)
|
||||
cn.emit('init',{ok:false})
|
||||
cn.disconnect()
|
||||
}else{
|
||||
console.log(new Date(),'Plugin Connected to Client',cn.request.connection.remoteAddress)
|
||||
cn.emit('init',{ok:true,plug:config.plug,notice:config.notice,type:config.type})
|
||||
}
|
||||
break;
|
||||
case'init_monitor':
|
||||
if(s.group[d.ke]&&s.group[d.ke][d.id]){
|
||||
delete(s.group[d.ke][d.id].buffer)
|
||||
}
|
||||
break;
|
||||
case'frame':
|
||||
try{
|
||||
if(!s.group[d.ke]){
|
||||
s.group[d.ke]={}
|
||||
}
|
||||
if(!s.group[d.ke][d.id]){
|
||||
s.group[d.ke][d.id]={
|
||||
sendToPython : s.createCameraBridgeToPython(d.ke+d.id)
|
||||
}
|
||||
}
|
||||
if(!s.group[d.ke][d.id].buffer){
|
||||
s.group[d.ke][d.id].buffer=[d.frame];
|
||||
}else{
|
||||
s.group[d.ke][d.id].buffer.push(d.frame)
|
||||
}
|
||||
if(d.frame[d.frame.length-2] === 0xFF && d.frame[d.frame.length-1] === 0xD9){
|
||||
s.detectObject(Buffer.concat(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 = socketIoClient('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)
|
||||
})
|
||||
}
|
||||
|
||||
//Start Python Controller
|
||||
s.callbacks = {}
|
||||
s.createCameraBridgeToPython = function(uniqueId){
|
||||
var pythonIo = socketIoClient('ws://localhost:'+config.pythonPort,{transports : ['websocket']});
|
||||
var sendToPython = function(data,callback){
|
||||
s.callbacks[data.id] = callback
|
||||
pythonIo.emit('f',data)
|
||||
}
|
||||
pythonIo.on('connect',function(d){
|
||||
s.debugLog(uniqueId+' is Connected from Python')
|
||||
})
|
||||
pythonIo.on('disconnect',function(d){
|
||||
s.debugLog(uniqueId+' is Disconnected from Python')
|
||||
setTimeout(function(){
|
||||
pythonIo.connect();
|
||||
s.debugLog(uniqueId+' is Attempting to Reconect to Python')
|
||||
},3000)
|
||||
})
|
||||
pythonIo.on('f',function(d){
|
||||
if(s.callbacks[d.id]){
|
||||
s.callbacks[d.id](d.data)
|
||||
delete(s.callbacks[d.id])
|
||||
}
|
||||
})
|
||||
return sendToPython
|
||||
}
|
||||
|
||||
|
||||
//Start Python Daemon
|
||||
process.env.PYTHONUNBUFFERED = 1;
|
||||
s.createPythonProcess = function(){
|
||||
s.isPythonRunning = false
|
||||
s.pythonScript = spawn('sh',[__dirname+'/bootPy.sh',config.pythonScript,__dirname]);
|
||||
var onStdErr = function (data) {
|
||||
s.debugLog('Python ERR')
|
||||
data = data.toString()
|
||||
s.debugLog(data)
|
||||
if(data.indexOf('Done!') > -1){
|
||||
console.log('PYTHON READY')
|
||||
s.isPythonRunning = true
|
||||
onStdErr = function(data){
|
||||
s.debugLog(data.toString())
|
||||
}
|
||||
}
|
||||
}
|
||||
s.pythonScript.stderr.on('data',onStdErr);
|
||||
|
||||
s.pythonScript.stdout.on('data', function (data) {
|
||||
s.debugLog('Python OUT')
|
||||
s.debugLog(data.toString())
|
||||
});
|
||||
|
||||
s.pythonScript.on('close', function () {
|
||||
s.debugLog('Python CLOSED')
|
||||
});
|
||||
}
|
||||
s.createPythonProcess()
|
||||
2
plugins/tensorflow/.gitignore
vendored
Normal file
2
plugins/tensorflow/.gitignore
vendored
Normal file
|
|
@ -0,0 +1,2 @@
|
|||
conf.json
|
||||
cascades
|
||||
20
plugins/tensorflow/INSTALL.sh
Normal file
20
plugins/tensorflow/INSTALL.sh
Normal file
|
|
@ -0,0 +1,20 @@
|
|||
#!/bin/bash
|
||||
mkdir data
|
||||
mkdir data/inception
|
||||
chmod -R 777 data
|
||||
wget https://cdn.shinobi.video/weights/inception5h.zip -O inception5h.zip
|
||||
unzip inception5h.zip -d data/inception
|
||||
if [ $(dpkg-query -W -f='${Status}' opencv_version 2>/dev/null | grep -c "ok installed") -eq 0 ]; then
|
||||
echo "Shinobi - Do ypu want to let the `opencv4nodejs` npm package install OpenCV? "
|
||||
echo "Only do this if you do not have OpenCV already or will not use a GPU (Hardware Acceleration)."
|
||||
echo "(y)es or (N)o"
|
||||
read nodejsinstall
|
||||
if [ "$nodejsinstall" = "y" ] || [ "$nodejsinstall" = "Y" ]; then
|
||||
export OPENCV4NODEJS_DISABLE_AUTOBUILD=0
|
||||
else
|
||||
export OPENCV4NODEJS_DISABLE_AUTOBUILD=1
|
||||
fi
|
||||
else
|
||||
export OPENCV4NODEJS_DISABLE_AUTOBUILD=1
|
||||
fi
|
||||
npm install opencv4nodejs moment express canvas@1.6 --unsafe-perm
|
||||
9
plugins/tensorflow/conf.sample.json
Normal file
9
plugins/tensorflow/conf.sample.json
Normal file
|
|
@ -0,0 +1,9 @@
|
|||
{
|
||||
"plug":"Tensorflow",
|
||||
"host":"localhost",
|
||||
"port":8080,
|
||||
"hostPort":8082,
|
||||
"key":"change_this_to_something_very_random____make_sure_to_match__/plugins/opencv/conf.json",
|
||||
"mode":"client",
|
||||
"type":"detector"
|
||||
}
|
||||
94
plugins/tensorflow/openalpr.conf
Normal file
94
plugins/tensorflow/openalpr.conf
Normal file
|
|
@ -0,0 +1,94 @@
|
|||
|
||||
; Specify the path to the runtime data directory
|
||||
runtime_dir = ${CMAKE_INSTALL_PREFIX}/share/openalpr/runtime_data
|
||||
|
||||
|
||||
ocr_img_size_percent = 1.33333333
|
||||
state_id_img_size_percent = 2.0
|
||||
|
||||
; Calibrating your camera improves detection accuracy in cases where vehicle plates are captured at a steep angle
|
||||
; Use the openalpr-utils-calibrate utility to calibrate your fixed camera to adjust for an angle
|
||||
; Once done, update the prewarp config with the values obtained from the tool
|
||||
prewarp =
|
||||
|
||||
; detection will ignore plates that are too large. This is a good efficiency technique to use if the
|
||||
; plates are going to be a fixed distance away from the camera (e.g., you will never see plates that fill
|
||||
; up the entire image
|
||||
max_plate_width_percent = 100
|
||||
max_plate_height_percent = 100
|
||||
|
||||
; detection_iteration_increase is the percentage that the LBP frame increases each iteration.
|
||||
; It must be greater than 1.0. A value of 1.01 means increase by 1%, 1.10 increases it by 10% each time.
|
||||
; So a 1% increase would be ~10x slower than 10% to process, but it has a higher chance of landing
|
||||
; directly on the plate and getting a strong detection
|
||||
detection_iteration_increase = 1.1
|
||||
|
||||
; The minimum detection strength determines how sure the detection algorithm must be before signaling that
|
||||
; a plate region exists. Technically this corresponds to LBP nearest neighbors (e.g., how many detections
|
||||
; are clustered around the same area). For example, 2 = very lenient, 9 = very strict.
|
||||
detection_strictness = 3
|
||||
|
||||
; The detection doesn't necessarily need an extremely high resolution image in order to detect plates
|
||||
; Using a smaller input image should still find the plates and will do it faster
|
||||
; Tweaking the max_detection_input values will resize the input image if it is larger than these sizes
|
||||
; max_detection_input_width/height are specified in pixels
|
||||
max_detection_input_width = 1280
|
||||
max_detection_input_height = 720
|
||||
|
||||
; detector is the technique used to find license plate regions in an image. Value can be set to
|
||||
; lbpcpu - default LBP-based detector uses the system CPU
|
||||
; lbpgpu - LBP-based detector that uses Nvidia GPU to increase recognition speed.
|
||||
; lbpopencl - LBP-based detector that uses OpenCL GPU to increase recognition speed. Requires OpenCV 3.0
|
||||
; morphcpu - Experimental detector that detects white rectangles in an image. Does not require training.
|
||||
detector = lbpgpu
|
||||
|
||||
; If set to true, all results must match a postprocess text pattern if a pattern is available.
|
||||
; If not, the result is disqualified.
|
||||
must_match_pattern = 0
|
||||
|
||||
; Bypasses plate detection. If this is set to 1, the library assumes that each region provided is a likely plate area.
|
||||
skip_detection = 0
|
||||
|
||||
; Specifies the full path to an image file that constrains the detection area. Only the plate regions allowed through the mask
|
||||
; will be analyzed. The mask image must match the resolution of your image to be analyzed. The mask is black and white.
|
||||
; Black areas will be ignored, white areas will be searched. An empty value means no mask (scan the entire image)
|
||||
detection_mask_image =
|
||||
|
||||
; OpenALPR can scan the same image multiple times with different randomization. Setting this to a value larger than
|
||||
; 1 may increase accuracy, but will increase processing time linearly (e.g., analysis_count = 3 is 3x slower)
|
||||
analysis_count = 1
|
||||
|
||||
; OpenALPR detects high-contrast plate crops and uses an alternative edge detection technique. Setting this to 0.0
|
||||
; would classify ALL images as high-contrast, setting it to 1.0 would classify no images as high-contrast.
|
||||
contrast_detection_threshold = 0.3
|
||||
|
||||
max_plate_angle_degrees = 15
|
||||
|
||||
ocr_min_font_point = 6
|
||||
|
||||
; Minimum OCR confidence percent to consider.
|
||||
postprocess_min_confidence = 65
|
||||
|
||||
; Any OCR character lower than this will also add an equally likely
|
||||
; chance that the character is incorrect and will be skipped. Value is a confidence percent
|
||||
postprocess_confidence_skip_level = 80
|
||||
|
||||
|
||||
debug_general = 0
|
||||
debug_timing = 0
|
||||
debug_detector = 0
|
||||
debug_prewarp = 0
|
||||
debug_state_id = 0
|
||||
debug_plate_lines = 0
|
||||
debug_plate_corners = 0
|
||||
debug_char_segment = 0
|
||||
debug_char_analysis = 0
|
||||
debug_color_filter = 0
|
||||
debug_ocr = 0
|
||||
debug_postprocess = 0
|
||||
debug_show_images = 0
|
||||
debug_pause_on_frame = 0
|
||||
|
||||
|
||||
|
||||
|
||||
502
plugins/tensorflow/shinobi-tensorflow.js
Normal file
502
plugins/tensorflow/shinobi-tensorflow.js
Normal file
|
|
@ -0,0 +1,502 @@
|
|||
//
|
||||
// Shinobi - OpenCV Plugin
|
||||
// Copyright (C) 2016-2025 Moe Alam, moeiscool
|
||||
//
|
||||
// # Donate
|
||||
//
|
||||
// If you like what I am doing here and want me to continue please consider donating :)
|
||||
// PayPal : paypal@m03.ca
|
||||
//
|
||||
process.on('uncaughtException', function (err) {
|
||||
console.error('uncaughtException',err);
|
||||
});
|
||||
var fs=require('fs');
|
||||
var cv=require('opencv4nodejs');
|
||||
var exec = require('child_process').exec;
|
||||
var moment = require('moment');
|
||||
var Canvas = require('canvas');
|
||||
var express = require('express');
|
||||
const path = require('path');
|
||||
var http = require('http'),
|
||||
app = express(),
|
||||
server = http.createServer(app);
|
||||
var config=require('./conf.json');
|
||||
if(!config.port){config.port=8080}
|
||||
if(!config.hostPort){config.hostPort=8082}
|
||||
if(config.systemLog===undefined){config.systemLog=true}
|
||||
if(config.cascadesDir===undefined){config.cascadesDir=__dirname+'/cascades/'}
|
||||
if(config.alprConfig===undefined){config.alprConfig=__dirname+'/openalpr.conf'}
|
||||
s={
|
||||
group:{},
|
||||
dir:{
|
||||
cascades : config.cascadesDir
|
||||
},
|
||||
isWin:(process.platform==='win32'),
|
||||
foundCascades : {
|
||||
|
||||
}
|
||||
}
|
||||
//default stream folder check
|
||||
if(!config.streamDir){
|
||||
if(s.isWin===false){
|
||||
config.streamDir='/dev/shm'
|
||||
}else{
|
||||
config.streamDir=config.windowsTempDir
|
||||
}
|
||||
if(!fs.existsSync(config.streamDir)){
|
||||
config.streamDir=__dirname+'/streams/'
|
||||
}else{
|
||||
config.streamDir+='/streams/'
|
||||
}
|
||||
}
|
||||
s.dir.streams=config.streamDir;
|
||||
//streams dir
|
||||
if(!fs.existsSync(s.dir.streams)){
|
||||
fs.mkdirSync(s.dir.streams);
|
||||
}
|
||||
//streams dir
|
||||
if(!fs.existsSync(s.dir.cascades)){
|
||||
fs.mkdirSync(s.dir.cascades);
|
||||
}
|
||||
s.gid=function(x){
|
||||
if(!x){x=10};var t = "";var p = "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789";
|
||||
for( var i=0; i < x; i++ )
|
||||
t += p.charAt(Math.floor(Math.random() * p.length));
|
||||
return t;
|
||||
};
|
||||
s.findCascades=function(callback){
|
||||
var tmp={};
|
||||
tmp.foundCascades=[];
|
||||
fs.readdir(s.dir.cascades,function(err,files){
|
||||
files.forEach(function(cascade,n){
|
||||
if(cascade.indexOf('.xml')>-1){
|
||||
tmp.foundCascades.push(cascade.replace('.xml',''))
|
||||
}
|
||||
})
|
||||
s.cascadesInDir=tmp.foundCascades;
|
||||
callback(tmp.foundCascades)
|
||||
})
|
||||
}
|
||||
s.findCascades(function(){
|
||||
//get cascades
|
||||
})
|
||||
s.detectLicensePlate=function(buffer,d,tx){
|
||||
if(!d.mon.detector_lisence_plate_country||d.mon.detector_lisence_plate_country===''){
|
||||
d.mon.detector_lisence_plate_country='us'
|
||||
}
|
||||
d.tmpFile=s.gid(5)+'.jpg'
|
||||
if(!fs.existsSync(s.dir.streams)){
|
||||
fs.mkdirSync(s.dir.streams);
|
||||
}
|
||||
d.dir=s.dir.streams+d.ke+'/'
|
||||
if(!fs.existsSync(d.dir)){
|
||||
fs.mkdirSync(d.dir);
|
||||
}
|
||||
d.dir=s.dir.streams+d.ke+'/'+d.id+'/'
|
||||
if(!fs.existsSync(d.dir)){
|
||||
fs.mkdirSync(d.dir);
|
||||
}
|
||||
fs.writeFile(d.dir+d.tmpFile,buffer,function(err){
|
||||
if(err) return s.systemLog(err);
|
||||
exec('alpr -j --config '+config.alprConfig+' -c '+d.mon.detector_lisence_plate_country+' '+d.dir+d.tmpFile,{encoding:'utf8'},(err, scan, stderr) => {
|
||||
if(err){
|
||||
s.systemLog(err);
|
||||
}else{
|
||||
try{
|
||||
scan=JSON.parse(scan.replace('--(!)Loaded CUDA classifier','').trim())
|
||||
}catch(err){
|
||||
if(!scan||!scan.results){
|
||||
return s.systemLog(scan,err);
|
||||
}
|
||||
}
|
||||
if(scan.results.length>0){
|
||||
scan.plates=[]
|
||||
scan.mats=[]
|
||||
scan.results.forEach(function(v){
|
||||
v.candidates.forEach(function(g,n){
|
||||
if(v.candidates[n].matches_template)
|
||||
delete(v.candidates[n].matches_template)
|
||||
})
|
||||
scan.plates.push({coordinates:v.coordinates,candidates:v.candidates,confidence:v.confidence,plate:v.plate})
|
||||
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));
|
||||
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))
|
||||
scan.mats.push({
|
||||
x:v.coordinates[0].x,
|
||||
y:v.coordinates[0].y,
|
||||
width:width,
|
||||
height:height,
|
||||
tag:v.plate
|
||||
})
|
||||
})
|
||||
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}})
|
||||
}
|
||||
}
|
||||
exec('rm -rf '+d.dir+d.tmpFile,{encoding:'utf8'})
|
||||
})
|
||||
})
|
||||
}
|
||||
s.detectObject=function(buffer,d,tx){
|
||||
//detect license plate?
|
||||
if(d.mon.detector_lisence_plate==="1"){
|
||||
s.detectLicensePlate(buffer,d,tx)
|
||||
}
|
||||
cv.imdecodeAsync(buffer,(err,im) => {
|
||||
if(err){
|
||||
console.log(err)
|
||||
return
|
||||
}
|
||||
|
||||
if (!cv.xmodules.dnn) {
|
||||
throw new Error('exiting: opencv4nodejs compiled without dnn module');
|
||||
}
|
||||
|
||||
// replace with path where you unzipped inception model
|
||||
const inceptionModelPath = __dirname+'/data/inception';
|
||||
|
||||
|
||||
const modelFile = path.resolve(inceptionModelPath, 'tensorflow_inception_graph.pb');
|
||||
const classNamesFile = path.resolve(inceptionModelPath, 'imagenet_comp_graph_label_strings.txt');
|
||||
if (!fs.existsSync(modelFile) || !fs.existsSync(classNamesFile)) {
|
||||
console.log('could not find inception model');
|
||||
console.log('download the model from: https://cdn.shinobi.video/weights/inception5h.zip');
|
||||
throw new Error('exiting');
|
||||
}
|
||||
|
||||
// read classNames and store them in an array
|
||||
const classNames = fs.readFileSync(classNamesFile).toString().split('\n');
|
||||
|
||||
// initialize tensorflow inception model from modelFile
|
||||
const net = cv.readNetFromTensorflow(modelFile);
|
||||
|
||||
// inception model works with 224 x 224 images, so we resize
|
||||
// our input images and pad the image with white pixels to
|
||||
// make the images have the same width and height
|
||||
const maxImgDim = 224;
|
||||
const white = new cv.Vec(255, 255, 255);
|
||||
const imgResized = im.resizeToMax(maxImgDim).padToSquare(white);
|
||||
|
||||
// network accepts blobs as input
|
||||
const inputBlob = cv.blobFromImage(imgResized);
|
||||
net.setInput(inputBlob);
|
||||
|
||||
// forward pass input through entire network, will return
|
||||
// classification result as 1xN Mat with confidences of each class
|
||||
const outputBlob = net.forward();
|
||||
|
||||
// find all labels with a minimum confidence
|
||||
const minConfidence = 0.05;
|
||||
const locations =
|
||||
outputBlob
|
||||
.threshold(minConfidence, 1, cv.THRESH_BINARY)
|
||||
.convertTo(cv.CV_8U)
|
||||
.findNonZero();
|
||||
// locations.forEach(function(v){
|
||||
// console.log(v)
|
||||
// })
|
||||
const result =
|
||||
locations.map(pt => ({
|
||||
confidence: parseInt(outputBlob.at(0, pt.x) * 100) / 100,
|
||||
className: classNames[pt.x]
|
||||
}))
|
||||
// sort result by confidence
|
||||
.sort((r0, r1) => r1.confidence - r0.confidence)
|
||||
.map(res => `${res.className} (${res.confidence})`);
|
||||
console.log(result)
|
||||
if(result.length > 0) {
|
||||
s.cx({
|
||||
f:'trigger',
|
||||
id:d.id,
|
||||
ke:d.ke,
|
||||
name:'tensorflow',
|
||||
details:{
|
||||
plug:'tensorflow',
|
||||
name:'tensorflow',
|
||||
reason:'object',
|
||||
matrices : result
|
||||
// confidence:d.average
|
||||
},
|
||||
imgHeight:d.mon.detector_scale_y,
|
||||
imgWidth:d.mon.detector_scale_x
|
||||
})
|
||||
}
|
||||
})
|
||||
}
|
||||
s.systemLog=function(q,w,e){
|
||||
if(!w){w=''}
|
||||
if(!e){e=''}
|
||||
if(config.systemLog===true){
|
||||
return console.log(moment().format(),q,w,e)
|
||||
}
|
||||
}
|
||||
|
||||
s.blenderRegion=function(d,cord,tx){
|
||||
d.width = d.image.width;
|
||||
d.height = d.image.height;
|
||||
if(!s.group[d.ke][d.id].canvas[cord.name]){
|
||||
if(!cord.sensitivity||isNaN(cord.sensitivity)){
|
||||
cord.sensitivity=d.mon.detector_sensitivity;
|
||||
}
|
||||
s.group[d.ke][d.id].canvas[cord.name] = new Canvas(d.width,d.height);
|
||||
s.group[d.ke][d.id].canvasContext[cord.name] = s.group[d.ke][d.id].canvas[cord.name].getContext('2d');
|
||||
s.group[d.ke][d.id].canvasContext[cord.name].fillStyle = '#000';
|
||||
s.group[d.ke][d.id].canvasContext[cord.name].fillRect( 0, 0,d.width,d.height);
|
||||
if(cord.points&&cord.points.length>0){
|
||||
s.group[d.ke][d.id].canvasContext[cord.name].beginPath();
|
||||
for (var b = 0; b < cord.points.length; b++){
|
||||
cord.points[b][0]=parseFloat(cord.points[b][0]);
|
||||
cord.points[b][1]=parseFloat(cord.points[b][1]);
|
||||
if(b===0){
|
||||
s.group[d.ke][d.id].canvasContext[cord.name].moveTo(cord.points[b][0],cord.points[b][1]);
|
||||
}else{
|
||||
s.group[d.ke][d.id].canvasContext[cord.name].lineTo(cord.points[b][0],cord.points[b][1]);
|
||||
}
|
||||
}
|
||||
s.group[d.ke][d.id].canvasContext[cord.name].clip();
|
||||
}
|
||||
}
|
||||
if(!s.group[d.ke][d.id].canvasContext[cord.name]){
|
||||
return
|
||||
}
|
||||
s.group[d.ke][d.id].canvasContext[cord.name].drawImage(d.image, 0, 0, d.width, d.height);
|
||||
if(!s.group[d.ke][d.id].blendRegion[cord.name]){
|
||||
s.group[d.ke][d.id].blendRegion[cord.name] = new Canvas(d.width, d.height);
|
||||
s.group[d.ke][d.id].blendRegionContext[cord.name] = s.group[d.ke][d.id].blendRegion[cord.name].getContext('2d');
|
||||
}
|
||||
var sourceData = s.group[d.ke][d.id].canvasContext[cord.name].getImageData(0, 0, d.width, d.height);
|
||||
// create an image if the previous image doesn<73>t exist
|
||||
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);
|
||||
// create a ImageData instance to receive the blended result
|
||||
var blendedData = s.group[d.ke][d.id].canvasContext[cord.name].createImageData(d.width, d.height);
|
||||
// blend the 2 images
|
||||
s.differenceAccuracy(blendedData.data,sourceData.data,s.group[d.ke][d.id].lastRegionImageData[cord.name].data);
|
||||
// draw the result in a canvas
|
||||
s.group[d.ke][d.id].blendRegionContext[cord.name].putImageData(blendedData, 0, 0);
|
||||
// store the current webcam image
|
||||
s.group[d.ke][d.id].lastRegionImageData[cord.name] = sourceData;
|
||||
blendedData = s.group[d.ke][d.id].blendRegionContext[cord.name].getImageData(0, 0, d.width, d.height);
|
||||
var i = 0;
|
||||
d.average = 0;
|
||||
while (i < (blendedData.data.length * 0.25)) {
|
||||
d.average += (blendedData.data[i * 4] + blendedData.data[i * 4 + 1] + blendedData.data[i * 4 + 2]);
|
||||
++i;
|
||||
}
|
||||
d.average = (d.average / (blendedData.data.length * 0.25))*10;
|
||||
if (d.average > parseFloat(cord.sensitivity)){
|
||||
if(d.mon.detector_use_detect_object==="1"&&d.mon.detector_second!=='1'){
|
||||
var buffer=s.group[d.ke][d.id].canvas[cord.name].toBuffer();
|
||||
s.detectObject(buffer,d,tx)
|
||||
}else{
|
||||
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}})
|
||||
}
|
||||
}
|
||||
s.group[d.ke][d.id].canvasContext[cord.name].clearRect(0, 0, d.width, d.height);
|
||||
s.group[d.ke][d.id].blendRegionContext[cord.name].clearRect(0, 0, d.width, d.height);
|
||||
}
|
||||
function blobToBuffer (blob, cb) {
|
||||
if (typeof Blob === 'undefined' || !(blob instanceof Blob)) {
|
||||
throw new Error('first argument must be a Blob')
|
||||
}
|
||||
if (typeof cb !== 'function') {
|
||||
throw new Error('second argument must be a function')
|
||||
}
|
||||
|
||||
var reader = new FileReader()
|
||||
|
||||
function onLoadEnd (e) {
|
||||
reader.removeEventListener('loadend', onLoadEnd, false)
|
||||
if (e.error) cb(e.error)
|
||||
else cb(null, Buffer.from(reader.result))
|
||||
}
|
||||
|
||||
reader.addEventListener('loadend', onLoadEnd, false)
|
||||
reader.readAsArrayBuffer(blob)
|
||||
}
|
||||
function fastAbs(value) {
|
||||
return (value ^ (value >> 31)) - (value >> 31);
|
||||
}
|
||||
|
||||
function threshold(value) {
|
||||
return (value > 0x15) ? 0xFF : 0;
|
||||
}
|
||||
s.differenceAccuracy=function(target, data1, data2) {
|
||||
if (data1.length != data2.length) return null;
|
||||
var i = 0;
|
||||
while (i < (data1.length * 0.25)) {
|
||||
var average1 = (data1[4 * i] + data1[4 * i + 1] + data1[4 * i + 2]) / 3;
|
||||
var average2 = (data2[4 * i] + data2[4 * i + 1] + data2[4 * i + 2]) / 3;
|
||||
var diff = threshold(fastAbs(average1 - average2));
|
||||
target[4 * i] = diff;
|
||||
target[4 * i + 1] = diff;
|
||||
target[4 * i + 2] = diff;
|
||||
target[4 * i + 3] = 0xFF;
|
||||
++i;
|
||||
}
|
||||
}
|
||||
s.checkAreas=function(d,tx){
|
||||
if(!s.group[d.ke][d.id].cords){
|
||||
if(!d.mon.cords){d.mon.cords={}}
|
||||
s.group[d.ke][d.id].cords=Object.values(d.mon.cords);
|
||||
}
|
||||
if(d.mon.detector_frame==='1'){
|
||||
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]]};
|
||||
s.group[d.ke][d.id].cords.push(d.mon.cords.frame);
|
||||
}
|
||||
for (var b = 0; b < s.group[d.ke][d.id].cords.length; b++){
|
||||
if(!s.group[d.ke][d.id].cords[b]){return}
|
||||
s.blenderRegion(d,s.group[d.ke][d.id].cords[b],tx)
|
||||
}
|
||||
delete(d.image)
|
||||
}
|
||||
|
||||
s.MainEventController=function(d,cn,tx){
|
||||
switch(d.f){
|
||||
case'refreshPlugins':
|
||||
s.findCascades(function(cascades){
|
||||
s.cx({f:'s.tx',data:{f:'detector_cascade_list',cascades:cascades},to:'GRP_'+d.ke})
|
||||
})
|
||||
break;
|
||||
case'readPlugins':
|
||||
s.cx({f:'s.tx',data:{f:'detector_cascade_list',cascades:s.cascadesInDir},to:'GRP_'+d.ke})
|
||||
break;
|
||||
case'init_plugin_as_host':
|
||||
if(!cn){
|
||||
console.log('No CN',d)
|
||||
return
|
||||
}
|
||||
if(d.key!==config.key){
|
||||
console.log(new Date(),'Plugin Key Mismatch',cn.request.connection.remoteAddress,d)
|
||||
cn.emit('init',{ok:false})
|
||||
cn.disconnect()
|
||||
}else{
|
||||
console.log(new Date(),'Plugin Connected to Client',cn.request.connection.remoteAddress)
|
||||
cn.emit('init',{ok:true,plug:config.plug,notice:config.notice,type:config.type})
|
||||
}
|
||||
break;
|
||||
case'init_monitor':
|
||||
if(s.group[d.ke]&&s.group[d.ke][d.id]){
|
||||
s.group[d.ke][d.id].canvas={}
|
||||
s.group[d.ke][d.id].canvasContext={}
|
||||
s.group[d.ke][d.id].blendRegion={}
|
||||
s.group[d.ke][d.id].blendRegionContext={}
|
||||
s.group[d.ke][d.id].lastRegionImageData={}
|
||||
s.group[d.ke][d.id].numberOfTriggers=0
|
||||
delete(s.group[d.ke][d.id].cords)
|
||||
delete(s.group[d.ke][d.id].buffer)
|
||||
}
|
||||
break;
|
||||
case'init_aws_push':
|
||||
// console.log('init_aws')
|
||||
s.group[d.ke][d.id].aws={links:[],complete:0,total:d.total,videos:[],tx:tx}
|
||||
break;
|
||||
case'frame':
|
||||
try{
|
||||
if(!s.group[d.ke]){
|
||||
s.group[d.ke]={}
|
||||
}
|
||||
if(!s.group[d.ke][d.id]){
|
||||
s.group[d.ke][d.id]={
|
||||
canvas:{},
|
||||
canvasContext:{},
|
||||
lastRegionImageData:{},
|
||||
blendRegion:{},
|
||||
blendRegionContext:{},
|
||||
}
|
||||
}
|
||||
if(!s.group[d.ke][d.id].buffer){
|
||||
s.group[d.ke][d.id].buffer=[d.frame];
|
||||
}else{
|
||||
s.group[d.ke][d.id].buffer.push(d.frame)
|
||||
}
|
||||
if(d.frame[d.frame.length-2] === 0xFF && d.frame[d.frame.length-1] === 0xD9){
|
||||
s.group[d.ke][d.id].buffer=Buffer.concat(s.group[d.ke][d.id].buffer);
|
||||
try{
|
||||
d.mon.detector_cascades=JSON.parse(d.mon.detector_cascades)
|
||||
}catch(err){
|
||||
|
||||
}
|
||||
if(d.mon.detector_frame_save==="1"){
|
||||
d.base64=s.group[d.ke][d.id].buffer.toString('base64')
|
||||
}
|
||||
if(d.mon.detector_second==='1'&&d.objectOnly===true){
|
||||
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)
|
||||
})
|
||||
}
|
||||
119
web/libs/css/slick.css
Normal file
119
web/libs/css/slick.css
Normal file
|
|
@ -0,0 +1,119 @@
|
|||
/* Slider */
|
||||
.slick-slider
|
||||
{
|
||||
position: relative;
|
||||
|
||||
display: block;
|
||||
box-sizing: border-box;
|
||||
|
||||
-webkit-user-select: none;
|
||||
-moz-user-select: none;
|
||||
-ms-user-select: none;
|
||||
user-select: none;
|
||||
|
||||
-webkit-touch-callout: none;
|
||||
-khtml-user-select: none;
|
||||
-ms-touch-action: pan-y;
|
||||
touch-action: pan-y;
|
||||
-webkit-tap-highlight-color: transparent;
|
||||
}
|
||||
|
||||
.slick-list
|
||||
{
|
||||
position: relative;
|
||||
|
||||
display: block;
|
||||
overflow: hidden;
|
||||
|
||||
margin: 0;
|
||||
padding: 0;
|
||||
}
|
||||
.slick-list:focus
|
||||
{
|
||||
outline: none;
|
||||
}
|
||||
.slick-list.dragging
|
||||
{
|
||||
cursor: pointer;
|
||||
cursor: hand;
|
||||
}
|
||||
|
||||
.slick-slider .slick-track,
|
||||
.slick-slider .slick-list
|
||||
{
|
||||
-webkit-transform: translate3d(0, 0, 0);
|
||||
-moz-transform: translate3d(0, 0, 0);
|
||||
-ms-transform: translate3d(0, 0, 0);
|
||||
-o-transform: translate3d(0, 0, 0);
|
||||
transform: translate3d(0, 0, 0);
|
||||
}
|
||||
|
||||
.slick-track
|
||||
{
|
||||
position: relative;
|
||||
top: 0;
|
||||
left: 0;
|
||||
|
||||
display: block;
|
||||
margin-left: auto;
|
||||
margin-right: auto;
|
||||
}
|
||||
.slick-track:before,
|
||||
.slick-track:after
|
||||
{
|
||||
display: table;
|
||||
|
||||
content: '';
|
||||
}
|
||||
.slick-track:after
|
||||
{
|
||||
clear: both;
|
||||
}
|
||||
.slick-loading .slick-track
|
||||
{
|
||||
visibility: hidden;
|
||||
}
|
||||
|
||||
.slick-slide
|
||||
{
|
||||
display: none;
|
||||
float: left;
|
||||
|
||||
height: 100%;
|
||||
min-height: 1px;
|
||||
}
|
||||
[dir='rtl'] .slick-slide
|
||||
{
|
||||
float: right;
|
||||
}
|
||||
.slick-slide img
|
||||
{
|
||||
display: block;
|
||||
}
|
||||
.slick-slide.slick-loading img
|
||||
{
|
||||
display: none;
|
||||
}
|
||||
.slick-slide.dragging img
|
||||
{
|
||||
pointer-events: none;
|
||||
}
|
||||
.slick-initialized .slick-slide
|
||||
{
|
||||
display: block;
|
||||
}
|
||||
.slick-loading .slick-slide
|
||||
{
|
||||
visibility: hidden;
|
||||
}
|
||||
.slick-vertical .slick-slide
|
||||
{
|
||||
display: block;
|
||||
|
||||
height: auto;
|
||||
|
||||
border: 1px solid transparent;
|
||||
}
|
||||
.slick-arrow.slick-hidden {
|
||||
display: none;
|
||||
}
|
||||
1
web/libs/js/libde265.min.js
vendored
Normal file
1
web/libs/js/libde265.min.js
vendored
Normal file
File diff suppressed because one or more lines are too long
1
web/libs/js/slick.min.js
vendored
Normal file
1
web/libs/js/slick.min.js
vendored
Normal file
File diff suppressed because one or more lines are too long
100
web/libs/less/slick.less
Normal file
100
web/libs/less/slick.less
Normal file
|
|
@ -0,0 +1,100 @@
|
|||
/* Slider */
|
||||
|
||||
.slick-slider {
|
||||
position: relative;
|
||||
display: block;
|
||||
box-sizing: border-box;
|
||||
-webkit-touch-callout: none;
|
||||
-webkit-user-select: none;
|
||||
-khtml-user-select: none;
|
||||
-moz-user-select: none;
|
||||
-ms-user-select: none;
|
||||
user-select: none;
|
||||
-ms-touch-action: pan-y;
|
||||
touch-action: pan-y;
|
||||
-webkit-tap-highlight-color: transparent;
|
||||
}
|
||||
.slick-list {
|
||||
position: relative;
|
||||
overflow: hidden;
|
||||
display: block;
|
||||
margin: 0;
|
||||
padding: 0;
|
||||
|
||||
&:focus {
|
||||
outline: none;
|
||||
}
|
||||
|
||||
&.dragging {
|
||||
cursor: pointer;
|
||||
cursor: hand;
|
||||
}
|
||||
}
|
||||
.slick-slider .slick-track,
|
||||
.slick-slider .slick-list {
|
||||
-webkit-transform: translate3d(0, 0, 0);
|
||||
-moz-transform: translate3d(0, 0, 0);
|
||||
-ms-transform: translate3d(0, 0, 0);
|
||||
-o-transform: translate3d(0, 0, 0);
|
||||
transform: translate3d(0, 0, 0);
|
||||
}
|
||||
|
||||
.slick-track {
|
||||
position: relative;
|
||||
left: 0;
|
||||
top: 0;
|
||||
display: block;
|
||||
margin-left: auto;
|
||||
margin-right: auto;
|
||||
|
||||
&:before,
|
||||
&:after {
|
||||
content: "";
|
||||
display: table;
|
||||
}
|
||||
|
||||
&:after {
|
||||
clear: both;
|
||||
}
|
||||
|
||||
.slick-loading & {
|
||||
visibility: hidden;
|
||||
}
|
||||
}
|
||||
.slick-slide {
|
||||
float: left;
|
||||
height: 100%;
|
||||
min-height: 1px;
|
||||
[dir="rtl"] & {
|
||||
float: right;
|
||||
}
|
||||
img {
|
||||
display: block;
|
||||
}
|
||||
&.slick-loading img {
|
||||
display: none;
|
||||
}
|
||||
|
||||
display: none;
|
||||
|
||||
&.dragging img {
|
||||
pointer-events: none;
|
||||
}
|
||||
|
||||
.slick-initialized & {
|
||||
display: block;
|
||||
}
|
||||
|
||||
.slick-loading & {
|
||||
visibility: hidden;
|
||||
}
|
||||
|
||||
.slick-vertical & {
|
||||
display: block;
|
||||
height: auto;
|
||||
border: 1px solid transparent;
|
||||
}
|
||||
}
|
||||
.slick-arrow.slick-hidden {
|
||||
display: none;
|
||||
}
|
||||
100
web/libs/scss/slick.scss
Normal file
100
web/libs/scss/slick.scss
Normal file
|
|
@ -0,0 +1,100 @@
|
|||
/* Slider */
|
||||
|
||||
.slick-slider {
|
||||
position: relative;
|
||||
display: block;
|
||||
box-sizing: border-box;
|
||||
-webkit-touch-callout: none;
|
||||
-webkit-user-select: none;
|
||||
-khtml-user-select: none;
|
||||
-moz-user-select: none;
|
||||
-ms-user-select: none;
|
||||
user-select: none;
|
||||
-ms-touch-action: pan-y;
|
||||
touch-action: pan-y;
|
||||
-webkit-tap-highlight-color: transparent;
|
||||
}
|
||||
.slick-list {
|
||||
position: relative;
|
||||
overflow: hidden;
|
||||
display: block;
|
||||
margin: 0;
|
||||
padding: 0;
|
||||
|
||||
&:focus {
|
||||
outline: none;
|
||||
}
|
||||
|
||||
&.dragging {
|
||||
cursor: pointer;
|
||||
cursor: hand;
|
||||
}
|
||||
}
|
||||
.slick-slider .slick-track,
|
||||
.slick-slider .slick-list {
|
||||
-webkit-transform: translate3d(0, 0, 0);
|
||||
-moz-transform: translate3d(0, 0, 0);
|
||||
-ms-transform: translate3d(0, 0, 0);
|
||||
-o-transform: translate3d(0, 0, 0);
|
||||
transform: translate3d(0, 0, 0);
|
||||
}
|
||||
|
||||
.slick-track {
|
||||
position: relative;
|
||||
left: 0;
|
||||
top: 0;
|
||||
display: block;
|
||||
margin-left: auto;
|
||||
margin-right: auto;
|
||||
|
||||
&:before,
|
||||
&:after {
|
||||
content: "";
|
||||
display: table;
|
||||
}
|
||||
|
||||
&:after {
|
||||
clear: both;
|
||||
}
|
||||
|
||||
.slick-loading & {
|
||||
visibility: hidden;
|
||||
}
|
||||
}
|
||||
.slick-slide {
|
||||
float: left;
|
||||
height: 100%;
|
||||
min-height: 1px;
|
||||
[dir="rtl"] & {
|
||||
float: right;
|
||||
}
|
||||
img {
|
||||
display: block;
|
||||
}
|
||||
&.slick-loading img {
|
||||
display: none;
|
||||
}
|
||||
|
||||
display: none;
|
||||
|
||||
&.dragging img {
|
||||
pointer-events: none;
|
||||
}
|
||||
|
||||
.slick-initialized & {
|
||||
display: block;
|
||||
}
|
||||
|
||||
.slick-loading & {
|
||||
visibility: hidden;
|
||||
}
|
||||
|
||||
.slick-vertical & {
|
||||
display: block;
|
||||
height: auto;
|
||||
border: 1px solid transparent;
|
||||
}
|
||||
}
|
||||
.slick-arrow.slick-hidden {
|
||||
display: none;
|
||||
}
|
||||
51
web/pages/cycle.ejs
Normal file
51
web/pages/cycle.ejs
Normal file
|
|
@ -0,0 +1,51 @@
|
|||
<%
|
||||
if(config.ssl&&config.ssl.port&&data.protocol==='https'){
|
||||
data.port=config.ssl.port
|
||||
}else{
|
||||
data.port=config.port
|
||||
}
|
||||
if(!data.port||data.port===''||data.port==80||data.port==443){data.url=baseUrl}else{data.url=baseUrl+':'+data.port}
|
||||
if(data.addon && data.addon.indexOf('relative')>-1){
|
||||
data.url=''
|
||||
}
|
||||
%>
|
||||
<script>
|
||||
var data = <%- JSON.stringify(data) %>
|
||||
if(!data.group || data.group === ''){
|
||||
data.group = '$'
|
||||
}
|
||||
</script>
|
||||
<link rel="stylesheet" href="<%=data.url%>/libs/css/font-awesome.min.css">
|
||||
<link rel="stylesheet" type="text/css" href="<%=data.url%>/libs/css/slick.css"/>
|
||||
<style>
|
||||
.cycle-item {
|
||||
|
||||
}
|
||||
</style>
|
||||
<script src="<%=data.url%>/libs/js/jquery.min.js"></script>
|
||||
<script type="text/javascript" src="<%=data.url%>/libs/js/slick.min.js"></script>
|
||||
<div id="slick"></div>
|
||||
<script type="text/javascript">
|
||||
$.cycle = {};
|
||||
$(function () {
|
||||
var show = <%-query.show || 1 %>;
|
||||
var scroll = <%-query.scroll || 1 %>;
|
||||
var playSpeed = <%-query.playSpeed || 3000 %>;
|
||||
var cycleEl = $('#slick')
|
||||
var tmp = ''
|
||||
$.each(<%- JSON.stringify(monitors) %>,function(n,monitor){
|
||||
tmp += '<iframe auth="'+data.auth+'" ke="'+data.ke+'" mid="'+monitor.mid+'" class="cycle-item" src="'+data.url+'/'+data.auth+'/embed/'+monitor.ke+'/'+monitor.mid+'/fullscreen|jquery|relative"></iframe>'
|
||||
})
|
||||
cycleEl.html(tmp)
|
||||
cycleEl.slick({
|
||||
slidesToShow: show,
|
||||
slidesToScroll: scroll,
|
||||
autoplay: true,
|
||||
autoplaySpeed: playSpeed,
|
||||
})
|
||||
.on('beforeChange', function(event, slick, currentSlide, nextSlide){
|
||||
console.log(nextSlide)
|
||||
})
|
||||
});
|
||||
</script>
|
||||
|
||||
Loading…
Add table
Add a link
Reference in a new issue