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Intrusion detection demo
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| { | |
| "sensors": [ | |
| { | |
| "label": "createAlarm", | |
| "name": "createAlarm", | |
| "version": "1.0.2", | |
| "properties": { | |
| "text": "Motion detected!", | |
| "severity": "MAJOR", | |
| "type": "motion", | |
| "resource": "$" | |
| }, | |
| "position": [ | |
| -39, | |
| 639 | |
| ], | |
| "dataTrigger": false, | |
| "tickTrigger": true, | |
| "timeout": "PT50S" | |
| }, | |
| { | |
| "label": "dataStream", | |
| "name": "stream", | |
| "version": "1.0.1", | |
| "resource": "$", | |
| "position": [ | |
| -479, | |
| 193 | |
| ], | |
| "dataTrigger": true, | |
| "tickTrigger": false, | |
| "timeout": "PT50S" | |
| }, | |
| { | |
| "label": "drawRectangles", | |
| "name": "detectedObjectsOnImage", | |
| "version": "1.0.9", | |
| "properties": { | |
| "fileName": "/sandbox/images/${nodes.dataStream.rawData.stream.image}", | |
| "jsonBoxes": "$${nodes.objectDetection.rawData.result}" | |
| }, | |
| "position": [ | |
| -39, | |
| 421 | |
| ], | |
| "dataTrigger": false, | |
| "tickTrigger": true, | |
| "timeout": "PT50S" | |
| }, | |
| { | |
| "label": "motionCheck", | |
| "name": "condition", | |
| "version": "1.1.6", | |
| "properties": { | |
| "condition": "${nodes.dataStream.rawData.stream.presence}==1" | |
| }, | |
| "position": [ | |
| -268, | |
| 191 | |
| ], | |
| "dataTrigger": false, | |
| "tickTrigger": true, | |
| "timeout": "PT50S" | |
| }, | |
| { | |
| "label": "objectDetection", | |
| "name": "tensorflowjsObjectDetection", | |
| "version": "1.0.20", | |
| "properties": { | |
| "imagefile": "/sandbox/images/${nodes.dataStream.rawData.stream.image}", | |
| "imageurl": "", | |
| "modelfile": "file:///sandbox/plugs/coco-ssd/model.json" | |
| }, | |
| "position": [ | |
| -17, | |
| 191 | |
| ], | |
| "dataTrigger": false, | |
| "tickTrigger": true, | |
| "timeout": "PT50S" | |
| }, | |
| { | |
| "label": "personCheck", | |
| "name": "condition", | |
| "version": "1.1.6", | |
| "properties": { | |
| "condition": "${nodes.personGet.rawData.numberOfObjects}>0" | |
| }, | |
| "position": [ | |
| -341, | |
| 419 | |
| ], | |
| "dataTrigger": false, | |
| "tickTrigger": true, | |
| "timeout": "PT50S" | |
| }, | |
| { | |
| "label": "personGet", | |
| "name": "script", | |
| "version": "2.0.1", | |
| "properties": { | |
| "script": "function example () {\n const boxes=JSON.parse('$${nodes.objectDetection.rawData.result}')\n const filteredBoxes= boxes.filter(function (el) {\n return ((el.class=='person' || el.class=='motorcycle' || el.class=='bird' || el.class=='cat' || el.class=='dog'));\n });\n return { numberOfObjects: filteredBoxes.length }\n}" | |
| }, | |
| "position": [ | |
| 234, | |
| 210 | |
| ], | |
| "dataTrigger": false, | |
| "tickTrigger": true, | |
| "timeout": "PT50S" | |
| }, | |
| { | |
| "label": "postFileToDiscord", | |
| "name": "postFileToDiscord", | |
| "version": "1.0.4", | |
| "properties": { | |
| "accessToken": "${vault.discordAccessToken}", | |
| "fileName": "${nodes.drawRectangles.rawData.finalFileName}", | |
| "channel": "${vault.discordChannelID}" | |
| }, | |
| "position": [ | |
| 286, | |
| 578 | |
| ], | |
| "dataTrigger": false, | |
| "tickTrigger": true, | |
| "timeout": "PT50S" | |
| }, | |
| { | |
| "label": "postFileToSlack", | |
| "name": "postFileToSlack", | |
| "version": "1.0.5", | |
| "properties": { | |
| "accessToken": "${vault.slackAccessToken}", | |
| "fileName": "${nodes.drawRectangles.rawData.finalFileName}", | |
| "channel": "#bot" | |
| }, | |
| "position": [ | |
| 276, | |
| 454 | |
| ], | |
| "dataTrigger": false, | |
| "tickTrigger": true, | |
| "timeout": "PT50S" | |
| } | |
| ], | |
| "triggers": [ | |
| { | |
| "sourceLabel": "personCheck", | |
| "destinationLabel": "createAlarm", | |
| "statesTrigger": [ | |
| "True" | |
| ] | |
| }, | |
| { | |
| "sourceLabel": "objectDetection", | |
| "destinationLabel": "personGet", | |
| "statesTrigger": [ | |
| "classified" | |
| ] | |
| }, | |
| { | |
| "sourceLabel": "motionCheck", | |
| "destinationLabel": "objectDetection", | |
| "statesTrigger": [ | |
| "True" | |
| ] | |
| }, | |
| { | |
| "sourceLabel": "drawRectangles", | |
| "destinationLabel": "postFileToDiscord", | |
| "statesTrigger": [ | |
| "success" | |
| ] | |
| }, | |
| { | |
| "sourceLabel": "dataStream", | |
| "destinationLabel": "motionCheck", | |
| "statesTrigger": [ | |
| "Data" | |
| ] | |
| }, | |
| { | |
| "sourceLabel": "personGet", | |
| "destinationLabel": "personCheck", | |
| "statesTrigger": [ | |
| "Success" | |
| ] | |
| }, | |
| { | |
| "sourceLabel": "drawRectangles", | |
| "destinationLabel": "postFileToSlack", | |
| "statesTrigger": [ | |
| "success" | |
| ] | |
| }, | |
| { | |
| "sourceLabel": "personCheck", | |
| "destinationLabel": "drawRectangles", | |
| "statesTrigger": [ | |
| "True" | |
| ] | |
| } | |
| ], | |
| "name": "demo motionsensor", | |
| "user": "test@waylay.io", | |
| "createTime": 1662376614862, | |
| "lastUpdateTime": 1662450998524, | |
| "discoveryTemplate": false, | |
| "taskDefaults": { | |
| "tags": {} | |
| } | |
| } |
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| { | |
| "name": "detectedObjectsOnImage", | |
| "version": "1.0.6", | |
| "type": "sensor", | |
| "script": "/*\n * ⚠️ Plugins should never throw exceptions, instead send an error back.\n *\n * ref: https://nodejs.org/api/errors.html#errors_error_first_callbacks\n */\nconst sharp = require('sharp');\n\n\nconst fileName = options.requiredProperties.fileName;\nconst jsonBoxes = options.requiredProperties.jsonBoxes;\nconst MAX_WIDTH = 1920;\nconst MAX_HEIGHT = 1080;\n\nif (!fileName || !jsonBoxes) {\n send(new Error('Missing property: fileName or jsonBoxes'));\n}\nconst dir = fileName.substring(0,fileName.lastIndexOf(\"/\"))\nlet state = \"success\"\nconst finalFileName = fileName.substring(0,fileName.lastIndexOf(\".\"))+\".markedImage.jpg\";\nconst rectanglePrefix=fileName.substring(0,fileName.lastIndexOf(\".\"))+\".rectangle\";\n\nconst images = new Array();\n\nasync function createRectangle(x, y, width, height, text, idx) {\n try {\n const svgImage = `\n <svg width=\"${width}\" height=\"${height}\">\n <style>\n .title { fill: #ff0000; font-size: 30px; font-weight: normal;}\n </style>\n <text x=\"15\" y=\"30\" text-anchor=\"left\" class=\"title\">${text}</text>\n </svg>\n `;\n \n await sharp(Buffer.from(svgImage))\n .extract({\n left: 5,\n top: 5,\n width: Math.floor(width)-10,\n height: Math.floor(height)-10\n })\n .extend({\n top: 5,\n bottom: 5,\n left: 5,\n right: 5,\n background: 'red'\n })\n .toFile(`${rectanglePrefix}${idx}.png`);\n\n } catch (error) {\n console.log(error);\n }\n}\n \nasync function composite(images,finalImage) {\n try {\n await sharp(fileName)\n .composite(images)\n .toFile(finalImage);\n\n } catch (error) {\n console.log(error);\n }\n}\n\nasync function execute(){\n const json = JSON.parse(jsonBoxes);\n for (const [idx,obj] of json.entries()){\n const y = Math.floor(obj.bbox[0])\n const x = Math.floor(obj.bbox[1])\n let width = Math.floor(obj.bbox[2])\n if(width>MAX_WIDTH){\n width = MAX_WIDTH\n }\n let height = Math.floor(obj.bbox[3])\n if(height>MAX_HEIGHT){\n height = MAX_HEIGHT\n }\n const text = obj.class\n\n images.push({\n input: `${rectanglePrefix}${idx}.png`,\n top: Math.floor(x),\n left: Math.floor(y)\n });\n\n await createRectangle(x, y, width, height, text, idx);\n }\n await composite(images,finalFileName)\n \n}\n\nexecute().then(()=>{\n const value = {\n observedState: state,\n rawData: {\n finalFileName: finalFileName\n }\n};\n\nsend(null, value);\n});\n", | |
| "metadata": { | |
| "author": "John Doe", | |
| "iconURL": "", | |
| "description": "", | |
| "rawData": [ | |
| { | |
| "dataType": "string", | |
| "parameter": "finalFileName" | |
| } | |
| ], | |
| "configuration": [ | |
| { | |
| "name": "fileName", | |
| "type": "string", | |
| "mandatory": true | |
| }, | |
| { | |
| "name": "jsonBoxes", | |
| "type": "string", | |
| "mandatory": true | |
| } | |
| ], | |
| "requiredProperties": [ | |
| "fileName", | |
| "jsonBoxes" | |
| ], | |
| "supportedStates": [ | |
| "success", | |
| "error" | |
| ] | |
| }, | |
| "dependencies": { | |
| "sharp": "0.30.7" | |
| } | |
| } |
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| { | |
| "name": "postFileToDiscord", | |
| "version": "1.0.4", | |
| "type": "sensor", | |
| "script": "//\nconst FormData = require('form-data')\nconst fs = require('fs-extra');\nconst axios = require('axios');\nconst { channel, accessToken, fileName} = options.requiredProperties\n\nasync function execute () {\n\n if (!accessToken || !channel || !fileName) {\n return send(new Error('Missing property'))\n }\n try {\n const stream = fs.createReadStream(fileName);\n const form = new FormData();\n form.append('files', stream);\n let headers = form.getHeaders(); \n const response = await axios.post('https://discord.com/api/v9/channels/'+channel+'/messages',\n form,\n { headers: { Authorization: `Bot ${accessToken}`, ...headers } })\n send(null, { observedState: 'Success', rawData: { response: response.data } })\n } catch (error) {\n console.error(error)\n send(null, { observedState: 'Error', rawData: { errorMessage: 'Error posting to slack api: ' + error } })\n }\n}\n\nexecute()", | |
| "metadata": { | |
| "author": "John Doe", | |
| "iconURL": "", | |
| "description": "", | |
| "rawData": [ | |
| { | |
| "dataType": "object", | |
| "parameter": "response" | |
| }, | |
| { | |
| "dataType": "string", | |
| "parameter": "errorMessage" | |
| } | |
| ], | |
| "configuration": [ | |
| { | |
| "name": "accessToken", | |
| "type": "string", | |
| "mandatory": true | |
| }, | |
| { | |
| "name": "fileName", | |
| "type": "string", | |
| "mandatory": true | |
| }, | |
| { | |
| "name": "channel", | |
| "type": "string", | |
| "mandatory": true | |
| } | |
| ], | |
| "requiredProperties": [ | |
| "accessToken", | |
| "fileName", | |
| "channel" | |
| ], | |
| "supportedStates": [ | |
| "Success", | |
| "Error" | |
| ] | |
| }, | |
| "dependencies": { | |
| "axios": "^0.26.1", | |
| "form-data": "4.0.0", | |
| "fs-extra": "10.1.0" | |
| } | |
| } |
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| { | |
| "name": "postFileToSlack", | |
| "version": "1.0.5", | |
| "type": "sensor", | |
| "script": "//\nconst FormData = require('form-data')\nconst fs = require('fs-extra');\nconst axios = require('axios');\nconst { channel, accessToken, fileName} = options.requiredProperties\n\nasync function execute () {\n\n if (!accessToken || !channel || !fileName) {\n return send(new Error('Missing property'))\n }\n try {\n const stream = fs.createReadStream(fileName);\n const form = new FormData();\n form.append('file', stream);\n form.append('channels', channel);\n let headers = form.getHeaders(); \n const response = await axios.post('https://slack.com/api/files.upload',\n form,\n { headers: { Authorization: `Bearer ${accessToken}`, ...headers } })\n send(null, { observedState: 'Success', rawData: { response: response.data } })\n } catch (error) {\n console.error(error)\n send(null, { observedState: 'Error', rawData: { errorMessage: 'Error posting to slack api: ' + error } })\n }\n}\n\nexecute()", | |
| "metadata": { | |
| "author": "John Doe", | |
| "iconURL": "", | |
| "description": "", | |
| "rawData": [ | |
| { | |
| "dataType": "object", | |
| "parameter": "response" | |
| }, | |
| { | |
| "dataType": "string", | |
| "parameter": "errorMessage" | |
| } | |
| ], | |
| "configuration": [ | |
| { | |
| "name": "accessToken", | |
| "type": "string", | |
| "mandatory": true | |
| }, | |
| { | |
| "name": "fileName", | |
| "type": "string", | |
| "mandatory": true | |
| }, | |
| { | |
| "name": "channel", | |
| "type": "string", | |
| "mandatory": true | |
| } | |
| ], | |
| "requiredProperties": [ | |
| "accessToken", | |
| "fileName", | |
| "channel" | |
| ], | |
| "supportedStates": [ | |
| "Success", | |
| "Error" | |
| ] | |
| }, | |
| "dependencies": { | |
| "axios": "^0.26.1", | |
| "form-data": "4.0.0", | |
| "fs-extra": "10.1.0" | |
| } | |
| } |
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| { | |
| "name": "tensorflowjsObjectDetection", | |
| "version": "1.0.18", | |
| "type": "sensor", | |
| "script": "//\n\nconst axios = require('axios');\nconst fs = require('fs-extra');\nconst cocoSsd = require('@tensorflow-models/coco-ssd');\n\n\n// tslint:disable-next-line: no-floating-promises\n\nconst { modelfile,imagefile, imageurl } = options.requiredProperties\n\n\nfunction base64_encode(file) {\n // read binary data\n var bitmap = fs.readFileSync(file);\n // convert binary data to base64 encoded string\n return new Buffer(bitmap).toString('base64');\n}\n\n\nasync function execute () {\n let model;\ntry {\n \n // Load the model\n const config={}\n if(modelfile){\n config.modelUrl=modelfile\n }\n \n model = await cocoSsd.load(config);\n\n\n const data = fs.readFileSync(imagefile);\n let classifyRes={};\n let state='classified'\n let imgTensor = tfnode.tidy( () => {\n try{\n return tfnode.node.decodeImage(data, 3); \n } catch (error) {\n console.error(error)\n return undefined;\n }\n })\n if(imgTensor){\n classifyRes = await model.detect(imgTensor)\n await model.dispose();\n tfnode.dispose(imgTensor)\n }else{\n state='error'\n }\n \n const classificationResult={};\n let value = {\n observedState: state,\n rawData: {\n result: classifyRes,\n }\n };\n \n if(imageurl){\n try {\n const method='POST';\n const modifiedResult={\"bounding_boxes\":[]}\n for (key in classifyRes) {\n const box={\n \"label\":classifyRes[key].class,\n \"value\":classifyRes[key].score,\n \"x\":Math.trunc(classifyRes[key].bbox[0]),\n \"y\":Math.trunc(classifyRes[key].bbox[1]),\n \"width\":Math.trunc(classifyRes[key].bbox[2]),\n \"height\":Math.trunc(classifyRes[key].bbox[3])\n \n }\n modifiedResult.bounding_boxes.push(box)\n };\n console.log(modifiedResult)\n const imgdataOriginal='data:image/png;base64, '+base64_encode(imagefile);\n const body={\n \"img\": imgdataOriginal,\n \"imgoriginal\":imgdataOriginal,\n \"classificationResult\":modifiedResult\n }\n const response = await axios({ url: imageurl, data: body, method: method, timeout: 2000 })\n value.rawData.httpSend = {\n status: response.status\n }\n } catch (error) {\n console.error(error)\n value.rawData.httpSend = {\n error: error\n } \n }\n }\n send(null, value);\n \n \n \n } catch (error) {\n console.error(error)\n send(null, { observedState: 'error', rawData: { errorMessage: 'Failed to call url: ' + error } })\n } finally {\n if(model){\n await model.dispose();\n }\n }\n\n}\n\n\n\nexecute()\n\n", | |
| "metadata": { | |
| "author": "John Doe", | |
| "iconURL": "", | |
| "description": "", | |
| "rawData": [], | |
| "configuration": [ | |
| { | |
| "name": "imagefile", | |
| "type": "string", | |
| "mandatory": true | |
| }, | |
| { | |
| "name": "imageurl", | |
| "type": "string", | |
| "mandatory": false | |
| }, | |
| { | |
| "name": "modelfile", | |
| "type": "string", | |
| "mandatory": false | |
| } | |
| ], | |
| "requiredProperties": [ | |
| "imagefile", | |
| "imageurl", | |
| "modelfile" | |
| ], | |
| "supportedStates": [ | |
| "classified", | |
| "error" | |
| ] | |
| }, | |
| "dependencies": { | |
| "axios": " ^0.20.0", | |
| "fs-extra": "^10.1.0", | |
| "@tensorflow-models/coco-ssd": "2.0.3" | |
| } | |
| } |
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