Use deepdetect-js to predict detection_600 classes from online webcam images

webcam_detect.js

var fs = require('fs');
var moment = require('moment');
var DD = require('deepdetect-js');

const dd = new DD({
  host: 'localhost',
  port: 18104,
  path: '/api/private/predict'
})

const  urls = [
  //'http://212.170.22.153:8080/jpg/image.jpg',
  //'http://oviso.axiscam.net/axis-cgi/jpg/image.cgi',
  //'http://mehamn.axiscam.net/jpg/image.jpg',
  //'http://194.103.218.15/jpg/image.jpg?time=1529449195253&dummy=image.jpg',
  //'https://static.earthcam.com/hof/england/abbeyroad/external/med/15294455093682_64_med.jpg',
  'http://ludington.axiscam.net:5700/axis-cgi/jpg/image.cgi',
]

const postData = {
  "service": "download",
  "parameters": {
    "output": {
      "confidence_threshold": 0.1,
      "bbox": true
    },
    "mllib": {
      "gpu": true
    }
  },
  "data": urls
}

TRIGGERS = {
  classes: {
    count: 1
  }
}

async function run() {
  const predict = await dd.postPredict(postData);

  predict.body.predictions.forEach( prediction => {

    if(prediction.classes.length >= TRIGGERS.classes.count) {
      fs.writeFileSync(`./json/${moment().format()}.json`, JSON.stringify(prediction));
    }

  });
  
}

run();
setInterval(run , 60000);