Successful stream stress test

Need to add stream watchdog timer and accessory timeout timer

.env.defaults

@@ -0,0 +1,2 @@
+TRAINED_MODEL_DIR=./trainedModels
+OUT_DIR=./out

.env.schema

@@ -0,0 +1,3 @@
+REF_IMAGE_DIR=
+TRAINED_MODEL_DIR=
+OUT_DIR=

.gitignore

@@ -107,3 +107,7 @@ dist
 # Stores VSCode versions used for testing VSCode extensions
 .vscode-test
 
+images/*
+bin
+out
+trainedModels/*

.vscode/launch.json

@@ -0,0 +1,30 @@
+{
+  // Use IntelliSense to learn about possible attributes.
+  // Hover to view descriptions of existing attributes.
+  // For more information, visit: https://go.microsoft.com/fwlink/?linkid=830387
+  "version": "0.2.0",
+  "configurations": [
+    {
+      "name": "Current TS File",
+      "type": "node",
+      "request": "launch",
+      "args": ["${relativeFile}"],
+      "runtimeArgs": ["--nolazy", "-r", "ts-node/register"],
+      "sourceMaps": true,
+      "cwd": "${workspaceRoot}",
+      "protocol": "inspector"
+    },
+    {
+      "type": "node",
+      "request": "launch",
+      "name": "Launch Program",
+      "preLaunchTask": "build",
+      "internalConsoleOptions": "openOnSessionStart",
+      "program": "/Users/brandonwatson/.nvm/versions/node/v14.15.0/lib/node_modules/homebridge/bin/homebridge",
+      "env": {
+        "HOMEBRIDGE_OPTS": "/Users/brandonwatson/.homebridge"
+      },
+      "sourceMaps": true
+    }
+  ]
+}

.vscode/tasks.json

@@ -0,0 +1,18 @@
+{
+  // See https://go.microsoft.com/fwlink/?LinkId=733558
+  // for the documentation about the tasks.json format
+  "version": "2.0.0",
+  "tasks": [
+    {
+      "type": "npm",
+      "script": "build",
+      "label": "build",
+      "problemMatcher": []
+    },
+    {
+      "type": "shell",
+      "label": "build and install",
+      "command": "npm run build&&sudo npm install -g --unsafe-perm ."
+    }
+  ]
+}

config.schema.json

@@ -0,0 +1,45 @@
+{
+  "pluginAlias": "HomeLocation",
+  "pluginType": "platform",
+  "singular": true,
+  "schema": {
+    "type": "object",
+    "properties": {
+      "name": {
+        "title": "Name",
+        "type": "string",
+        "required": true,
+        "default": "Example Dynamic Platform"
+      },
+      "refImageDirectory": {
+        "title": "RefImageDirectory",
+        "type": "string",
+        "required": true
+      },
+      "trainedModelDirectory": {
+        "title": "TrainedModelDirectory",
+        "type": "string",
+        "required": true
+      },
+      "rooms": {
+        "title": "Rooms",
+        "type": "array",
+        "items": {
+          "type": "object",
+          "properties": {
+            "name": {
+              "title": "Name",
+              "type": "string",
+              "required": true
+            },
+            "rtspCameraConnectionString": {
+              "title": "RtspCameraConnectionString",
+              "type": "string",
+              "required": true
+            }
+          }
+        }
+      }
+    }
+  }
+}

homebridge-face-location.code-workspace

@@ -0,0 +1,11 @@
+{
+	"folders": [
+        {
+            "path": "."
+        }
+    ],
+    "settings": {
+        "editor.tabSize": 2,
+        "debug.javascript.unmapMissingSources": true
+    }
+}

package.json

@@ -0,0 +1,43 @@
+{
+  "name": "homebridge-face-location",
+  "version": "1.0.0",
+  "description": "",
+  "main": "bin/index.js",
+  "scripts": {
+    "test": "echo \"Error: no test specified\" && exit 1",
+    "build": "npm run copy-files && tsc --build",
+    "copy-files": "copyfiles -u 1 -s weights/* bin/weights",
+    "train": "npx ts-node ./scripts/train.ts"
+  },
+  "repository": {
+    "type": "git",
+    "url": "ssh://git@thebword.ddns.net:3122/watsonb8/homebridge-face-location.git"
+  },
+  "keywords": [
+    "homebridge",
+    "typescript",
+    "homebridge-plugin"
+  ],
+  "engines": {
+    "homebridge": ">=1.1.6"
+  },
+  "author": "Brandon Watson",
+  "license": "ISC",
+  "dependencies": {
+    "@tensorflow/tfjs": "^2.6.0",
+    "@tensorflow/tfjs-node": "^2.6.0",
+    "@types/mime-types": "^2.1.0",
+    "@vladmandic/face-api": "^0.8.8",
+    "canvas": "^2.6.1",
+    "dotenv-extended": "^2.9.0",
+    "mime-types": "^2.1.27",
+    "tsyringe": "^4.4.0"
+  },
+  "devDependencies": {
+    "@types/webgl2": "0.0.5",
+    "typescript": "^4.0.5",
+    "ts-node": "^9.0.0",
+    "homebridge": "^1.1.6",
+    "copyfiles": "^2.4.0"
+  }
+}

scripts/streamAndDetect.ts

@@ -0,0 +1,58 @@
+import { Rtsp, IStreamEventArgs } from "../src/rtsp/rtsp";
+import { nets } from "@vladmandic/face-api";
+import * as faceapi from "@vladmandic/face-api";
+import canvas from "canvas";
+import fs from "fs";
+import * as path from "path";
+import dotenv from "dotenv-extended";
+import { delay, getFaceDetectorOptions, saveFile } from "../src/common";
+require("@tensorflow/tfjs-node");
+
+const { Canvas, Image, ImageData } = canvas;
+//@ts-ignore
+faceapi.env.monkeyPatch({ Canvas, Image, ImageData });
+
+const main = async () => {
+  dotenv.load({
+    silent: false,
+    errorOnMissing: true,
+  });
+
+  const modelDir = process.env.TRAINED_MODEL_DIR as string;
+
+  const rtsp = new Rtsp("rtsp://brandon:asdf1234@192.168.1.229/live", {
+    rate: 0.5,
+    image: true,
+    codec: "copy",
+  });
+  const faceDetectionNet = nets.ssdMobilenetv1;
+
+  await faceDetectionNet.loadFromDisk(path.join(__dirname, "../weights"));
+  await nets.faceLandmark68Net.loadFromDisk(path.join(__dirname, "../weights"));
+  await nets.faceRecognitionNet.loadFromDisk(
+    path.join(__dirname, "../weights")
+  );
+
+  const raw = fs.readFileSync(path.join(modelDir, "data.json"), "utf-8");
+  const content = JSON.parse(raw);
+  const matcher = faceapi.FaceMatcher.fromJSON(content);
+
+  rtsp.dataEvent.push(async (sender: Rtsp, args: IStreamEventArgs) => {
+    const input = ((await canvas.loadImage(args.data)) as unknown) as ImageData;
+    const out = faceapi.createCanvasFromMedia(input);
+    await saveFile(process.env.OUT_DIR as string, "image.jpg", args.data);
+    const resultsQuery = await faceapi
+      .detectAllFaces(out, getFaceDetectorOptions(faceDetectionNet))
+      .withFaceLandmarks()
+      .withFaceDescriptors();
+
+    for (const res of resultsQuery) {
+      const bestMatch = matcher.matchDescriptor(res.descriptor);
+      console.log("Face Detected: " + bestMatch.label);
+    }
+  });
+
+  rtsp.start();
+};
+
+main();

scripts/train.ts

@@ -0,0 +1,100 @@
+import * as faceapi from "@vladmandic/face-api";
+import canvas from "canvas";
+import fs, { lstatSync } from "fs";
+import * as path from "path";
+import { LabeledFaceDescriptors, TNetInput } from "@vladmandic/face-api";
+import * as mime from "mime-types";
+import dotenv from "dotenv-extended";
+import { getFaceDetectorOptions } from "../src/common";
+require("@tensorflow/tfjs-node");
+
+const { Canvas, Image, ImageData } = canvas;
+//@ts-ignore
+faceapi.env.monkeyPatch({ Canvas, Image, ImageData });
+
+const main = async () => {
+  dotenv.load({
+    silent: false,
+    errorOnMissing: true,
+  });
+  const inputDir = process.env.REF_IMAGE_DIR as string;
+  const outDir = process.env.TRAINED_MODEL_DIR as string;
+
+  const faceDetectionNet = faceapi.nets.ssdMobilenetv1;
+  await faceDetectionNet.loadFromDisk(path.join(__dirname, "../weights"));
+  await faceapi.nets.faceLandmark68Net.loadFromDisk(
+    path.join(__dirname, "../weights")
+  );
+  await faceapi.nets.faceRecognitionNet.loadFromDisk(
+    path.join(__dirname, "../weights")
+  );
+
+  const options = getFaceDetectorOptions(faceDetectionNet);
+
+  const dirs = fs.readdirSync(inputDir);
+
+  const refs: Array<LabeledFaceDescriptors> = [];
+  for (const dir of dirs) {
+    if (!lstatSync(path.join(inputDir, dir)).isDirectory()) {
+      continue;
+    }
+    const files = fs.readdirSync(path.join(inputDir, dir));
+    let referenceResults = await Promise.all(
+      files.map(async (file: string) => {
+        const mimeType = mime.contentType(
+          path.extname(path.join(inputDir, dir, file))
+        );
+        if (!mimeType || !mimeType.startsWith("image")) {
+          return;
+        }
+        console.log(path.join(inputDir, dir, file));
+
+        try {
+          const referenceImage = (await canvas.loadImage(
+            path.join(inputDir, dir, file)
+          )) as unknown;
+
+          const descriptor = await faceapi
+            .detectSingleFace(referenceImage as TNetInput, options)
+            .withFaceLandmarks()
+            .withFaceDescriptor();
+          if (!descriptor || !descriptor.descriptor) {
+            throw new Error("No face found");
+          }
+
+          const faceDescriptors = [descriptor.descriptor];
+          return new faceapi.LabeledFaceDescriptors(dir, faceDescriptors);
+        } catch (err) {
+          console.log(
+            "An error occurred loading image at path: " +
+              path.join(inputDir, dir, file)
+          );
+        }
+        return undefined;
+      })
+    );
+
+    if (referenceResults) {
+      refs.push(
+        ...(referenceResults.filter((e) => e) as LabeledFaceDescriptors[])
+      );
+    }
+  }
+
+  const faceMatcher = new faceapi.FaceMatcher(refs);
+
+  fs.writeFile(
+    path.join(outDir, "data.json"),
+    JSON.stringify(faceMatcher.toJSON()),
+    "utf8",
+    (err) => {
+      if (err) {
+        console.log(`An error occurred while writing data model to file`);
+      }
+
+      console.log(`Successfully wrote data model to file`);
+    }
+  );
+};
+
+main();

src/common.ts

@@ -0,0 +1,53 @@
+import * as faceapi from "@vladmandic/face-api";
+import * as path from "path";
+import fs from "fs";
+
+// SsdMobilenetv1Options
+export const minConfidence = 0.5;
+
+// TinyFaceDetectorOptions
+export const inputSize = 408;
+export const scoreThreshold = 0.5;
+
+export const getFaceDetectorOptions = (net: faceapi.NeuralNetwork<any>) => {
+  return net === faceapi.nets.ssdMobilenetv1
+    ? new faceapi.SsdMobilenetv1Options({ minConfidence })
+    : new faceapi.TinyFaceDetectorOptions({ inputSize, scoreThreshold });
+};
+
+export function saveFile(
+  basePath: string,
+  fileName: string,
+  buf: Buffer
+): Promise<void> {
+  const writeFile = (): Promise<void> => {
+    return new Promise((resolve, reject) => {
+      fs.writeFile(path.resolve(basePath, fileName), buf, "base64", (err) => {
+        if (err) {
+          return reject(err);
+        }
+        resolve();
+      });
+    });
+  };
+  return new Promise(async (resolve, reject) => {
+    if (!fs.existsSync(basePath)) {
+      fs.mkdir(basePath, async (err) => {
+        if (err) {
+          return reject(err);
+        }
+        resolve(await writeFile());
+      });
+    } else {
+      resolve(await writeFile());
+    }
+  });
+}
+
+export const delay = (ms: number): Promise<void> => {
+  return new Promise((resolve) => {
+    setTimeout(() => {
+      resolve();
+    }, ms);
+  });
+};

src/config.ts

@@ -0,0 +1,39 @@
+import { PlatformConfig } from "homebridge";
+
+export interface IConfig extends PlatformConfig {
+  refImageDirectory: string;
+  trainedModelDirectory: string;
+  weightDirectory: string;
+  outputDirectory: string;
+  trainOnStartup: boolean;
+  rooms: Array<IRoom>;
+  detectionTimeout: number;
+  debug: boolean;
+  writeOutput: boolean;
+}
+
+export interface IRoom {
+  name: string;
+  rtspConnectionStrings: Array<string>;
+}
+
+export const isRoom = (object: any): object is IRoom => {
+  return "name" in object && "rtspConnectionStrings" in object;
+};
+
+export const isConfig = (object: any): object is IConfig => {
+  const roomsOkay =
+    object["rooms"].filter((room: any) => isRoom(room)).length ===
+    object["rooms"].length;
+  return (
+    "refImageDirectory" in object &&
+    "trainedModelDirectory" in object &&
+    "weightDirectory" in object &&
+    "outputDirectory" in object &&
+    "trainOnStartup" in object &&
+    "detectionTimeout" in object &&
+    "writeOutput" in object &&
+    "rooms" in object &&
+    roomsOkay
+  );
+};

src/events/event.ts

@@ -0,0 +1,12 @@
+import { EventDelegate } from "./eventDelegate";
+
+export class Event<T, K> extends Array<EventDelegate<T, K>> {
+  constructor() {
+    super();
+  }
+  public fire = (source: T, args: K) => {
+    for (const delegate of this) {
+      delegate(source, args);
+    }
+  };
+}

src/events/eventDelegate.ts

@@ -0,0 +1 @@
+export type EventDelegate<T, K> = (sender: T, args: K) => void;

src/events/index.ts

@@ -0,0 +1,2 @@
+export * from "./event";
+export * from "./eventDelegate";

src/homeLocationPlatform.ts

@@ -0,0 +1,229 @@
+import {
+  API,
+  DynamicPlatformPlugin,
+  Logger,
+  PlatformAccessory,
+  PlatformConfig,
+  Service,
+  Characteristic,
+} from "homebridge";
+import { IConfig, isConfig } from "./config";
+import * as faceapi from "@vladmandic/face-api";
+import canvas from "canvas";
+import fs, { lstatSync } from "fs";
+import * as path from "path";
+import { nets } from "@vladmandic/face-api";
+import {
+  LabeledFaceDescriptors,
+  TNetInput,
+  FaceMatcher,
+} from "@vladmandic/face-api";
+import * as mime from "mime-types";
+import { Monitor } from "./monitor";
+import { getFaceDetectorOptions } from "./common";
+require("@tensorflow/tfjs-node");
+
+const { Canvas, Image, ImageData } = canvas;
+//@ts-ignore
+faceapi.env.monkeyPatch({ Canvas, Image, ImageData });
+
+import { PLATFORM_NAME, PLUGIN_NAME } from "./settings";
+import { LocationAccessory } from "./locationAccessory";
+
+/**
+ * HomebridgePlatform
+ * This class is the main constructor for your plugin, this is where you should
+ * parse the user config and discover/register accessories with Homebridge.
+ */
+export class HomeLocationPlatform implements DynamicPlatformPlugin {
+  public readonly Service: typeof Service = this.api.hap.Service;
+  public readonly Characteristic: typeof Characteristic = this.api.hap
+    .Characteristic;
+
+  // this is used to track restored cached accessories
+  public readonly accessories: PlatformAccessory[] = [];
+  public config: IConfig;
+
+  constructor(
+    public readonly log: Logger,
+    config: PlatformConfig,
+    public readonly api: API
+  ) {
+    this.log.debug("Finished initializing platform:", config.name);
+
+    if (!isConfig(config)) {
+      this.log.error("Configuration is incorrect or incomplete");
+      process.exit(1);
+    } else {
+      this.config = config;
+    }
+
+    this.api.on("didFinishLaunching", async () => {
+      log.debug("Executed didFinishLaunching callback");
+      // run the method to discover / register your devices as accessories
+      await this.discoverDevices();
+    });
+  }
+
+  /**
+   * This function is invoked when homebridge restores cached accessories from disk at startup.
+   * It should be used to setup event handlers for characteristics and update respective values.
+   */
+  public configureAccessory(accessory: PlatformAccessory) {
+    this.log.info("Loading accessory from cache:", accessory.displayName);
+
+    // add the restored accessory to the accessories cache so we can track if it has already been registered
+    this.accessories.push(accessory);
+  }
+
+  /**
+   * This is an example method showing how to register discovered accessories.
+   * Accessories must only be registered once, previously created accessories
+   * must not be registered again to prevent "duplicate UUID" errors.
+   */
+  public async discoverDevices() {
+    //Train facial recognition model
+    let faceMatcher: FaceMatcher;
+    if (this.config.trainOnStartup) {
+      faceMatcher = await this.trainModels();
+    } else {
+      const faceDetectionNet = nets.ssdMobilenetv1;
+
+      await faceDetectionNet.loadFromDisk(this.config.weightDirectory);
+      await nets.faceLandmark68Net.loadFromDisk(this.config.weightDirectory);
+      await nets.faceRecognitionNet.loadFromDisk(this.config.weightDirectory);
+
+      const raw = fs.readFileSync(
+        path.join(this.config.trainedModelDirectory, "data.json"),
+        "utf-8"
+      );
+      faceMatcher = FaceMatcher.fromJSON(JSON.parse(raw));
+    }
+
+    const locationMonitor = new Monitor(
+      this.config.rooms,
+      faceMatcher,
+      this.log,
+      this.config
+    );
+
+    locationMonitor.startStreams();
+
+    const labels = faceMatcher.labeledDescriptors.map((e) => e.label);
+    for (const room of this.config.rooms) {
+      const uuid = this.api.hap.uuid.generate(room.name);
+
+      const existingAccessory = this.accessories.find((e) => e.UUID === uuid);
+      if (existingAccessory) {
+        this.log.info(
+          "Restoring existing accessory from cache: ",
+          existingAccessory.displayName
+        );
+
+        new LocationAccessory(this, existingAccessory, locationMonitor, room);
+
+        this.api.updatePlatformAccessories([existingAccessory]);
+      } else {
+        this.log.info("Adding new accessory:", `${room.name}`);
+
+        // create a new accessory
+        const accessory = new this.api.platformAccessory(`${room.name}`, uuid);
+
+        accessory.context["DeviceName"] = `${room.name}`;
+
+        // create the accessory handler for the newly create accessory
+        // this is imported from `platformAccessory.ts`
+        new LocationAccessory(this, accessory, locationMonitor, room);
+
+        // link the accessory to your platform
+        this.api.registerPlatformAccessories(PLUGIN_NAME, PLATFORM_NAME, [
+          accessory,
+        ]);
+      }
+    }
+  }
+
+  private async trainModels(): Promise<FaceMatcher> {
+    const faceDetectionNet = faceapi.nets.ssdMobilenetv1;
+    await faceDetectionNet.loadFromDisk(this.config.weightDirectory);
+    await faceapi.nets.faceLandmark68Net.loadFromDisk(
+      this.config.weightDirectory
+    );
+    await faceapi.nets.faceRecognitionNet.loadFromDisk(
+      this.config.weightDirectory
+    );
+
+    const options = getFaceDetectorOptions(faceDetectionNet);
+
+    const dirs = fs.readdirSync(this.config.refImageDirectory);
+
+    const refs: Array<LabeledFaceDescriptors> = [];
+    for (const dir of dirs) {
+      if (
+        !lstatSync(path.join(this.config.refImageDirectory, dir)).isDirectory()
+      ) {
+        continue;
+      }
+      const files = fs.readdirSync(
+        path.join(this.config.refImageDirectory, dir)
+      );
+      let referenceResults = await Promise.all(
+        files.map(async (file: string) => {
+          const mimeType = mime.contentType(
+            path.extname(path.join(this.config.refImageDirectory, dir, file))
+          );
+          if (!mimeType || !mimeType.startsWith("image")) {
+            return;
+          }
+          console.log(path.join(this.config.refImageDirectory, dir, file));
+
+          try {
+            const referenceImage = (await canvas.loadImage(
+              path.join(this.config.refImageDirectory, dir, file)
+            )) as unknown;
+
+            const descriptor = await faceapi
+              .detectSingleFace(referenceImage as TNetInput, options)
+              .withFaceLandmarks()
+              .withFaceDescriptor();
+            if (!descriptor || !descriptor.descriptor) {
+              throw new Error("No face found");
+            }
+
+            const faceDescriptors = [descriptor.descriptor];
+            return new faceapi.LabeledFaceDescriptors(dir, faceDescriptors);
+          } catch (err) {
+            console.log(
+              "An error occurred loading image at path: " +
+                path.join(this.config.refImageDirectory, dir, file)
+            );
+          }
+          return undefined;
+        })
+      );
+
+      if (referenceResults) {
+        refs.push(
+          ...(referenceResults.filter((e) => e) as LabeledFaceDescriptors[])
+        );
+      }
+    }
+
+    const faceMatcher = new faceapi.FaceMatcher(refs);
+
+    fs.writeFile(
+      path.join(this.config.trainedModelDirectory, "data.json"),
+      JSON.stringify(faceMatcher.toJSON()),
+      "utf8",
+      (err) => {
+        if (err) {
+          console.log(`An error occurred while writing data model to file`);
+        }
+
+        console.log(`Successfully wrote data model to file`);
+      }
+    );
+
+    return faceMatcher;
+  }
+}

src/index.ts

@@ -0,0 +1,11 @@
+import { API } from "homebridge";
+
+import { PLATFORM_NAME } from "./settings";
+import { HomeLocationPlatform } from "./homeLocationPlatform";
+
+/**
+ * This method registers the platform with Homebridge
+ */
+export = (api: API) => {
+  api.registerPlatform(PLATFORM_NAME, HomeLocationPlatform);
+};

src/locationAccessory.ts

@@ -0,0 +1,91 @@
+import {
+  Service,
+  CharacteristicGetCallback,
+  PlatformAccessory,
+} from "homebridge";
+import { Monitor, IStateChangeEventArgs } from "./monitor";
+import { HomeLocationPlatform } from "./homeLocationPlatform";
+import { IRoom } from "./config";
+
+/**
+ * Platform Accessory
+ * An instance of this class is created for each accessory your platform registers
+ * Each accessory may expose multiple services of different service types.
+ */
+export class LocationAccessory {
+  private _services: Array<Service>;
+
+  constructor(
+    private readonly _platform: HomeLocationPlatform,
+    private readonly _accessory: PlatformAccessory,
+    private _monitor: Monitor,
+    private _room: IRoom
+  ) {
+    this._services = [];
+    // set accessory information
+    this._accessory
+      .getService(this._platform.Service.AccessoryInformation)!
+      .setCharacteristic(
+        this._platform.Characteristic.Manufacturer,
+        "Brandon Watson"
+      )
+      .setCharacteristic(
+        this._platform.Characteristic.Model,
+        "Person Location Sensor"
+      )
+      .setCharacteristic(
+        this._platform.Characteristic.SerialNumber,
+        "123-456-789"
+      );
+
+    //Init motion services
+    for (const label of this._monitor.labels) {
+      const newService =
+        this._accessory.getService(label) ||
+        this._accessory.addService(
+          this._platform.Service.MotionSensor,
+          label,
+          this._room + label
+        );
+
+      newService
+        .getCharacteristic(this._platform.Characteristic.MotionDetected)
+        .on("get", (callback: CharacteristicGetCallback) =>
+          this.onMotionDetectedGet(label, callback)
+        );
+
+      this._services.push(newService);
+    }
+
+    //Register monitor state change events
+    this._monitor.stateChangedEvent.push(this.onMonitorStateChange.bind(this));
+  }
+
+  private onMotionDetectedGet = (
+    label: string,
+    callback: CharacteristicGetCallback
+  ) => {
+    this._platform.log.debug("Triggered GET MotionDetected");
+
+    // set this to a valid value for MotionDetected
+    const currentValue =
+      this._monitor.getState(label) === this._room.name ? 1 : 0;
+
+    callback(null, currentValue);
+  };
+
+  private onMonitorStateChange = (
+    sender: Monitor,
+    args: IStateChangeEventArgs
+  ) => {
+    const service = this._services.find(
+      (service) => service.displayName == args.label
+    );
+    if (service) {
+      service.setCharacteristic(
+        this._platform.Characteristic.MotionDetected,
+        args.new === this._room.name
+      );
+    }
+  };
+}

src/monitor.ts

@@ -0,0 +1,161 @@
+import { FaceMatcher } from "@vladmandic/face-api";
+import { IRoom } from "./config";
+import {
+  Rtsp,
+  IStreamEventArgs,
+  ICloseEventArgs,
+  IErrorEventArgs,
+  IMessageEventArgs,
+} from "./rtsp/rtsp";
+import canvas from "canvas";
+import * as faceapi from "@vladmandic/face-api";
+import { getFaceDetectorOptions, saveFile } from "./common";
+import { nets } from "@vladmandic/face-api";
+import { Logger } from "homebridge";
+import { Event } from "./events";
+import { IConfig } from "./config";
+const { Canvas, Image, ImageData } = canvas;
+
+export type MonitorState = { [label: string]: string | null };
+export interface IStateChangeEventArgs {
+  label: string;
+  old: string | null;
+  new: string;
+}
+
+export class Monitor {
+  private _state: MonitorState = {};
+  private _streamsByRoom: { [roomName: string]: Array<Rtsp> } = {};
+  private _faceDetectionNet = nets.ssdMobilenetv1;
+  private _stateChangedEvent: Event<this, IStateChangeEventArgs>;
+
+  constructor(
+    private _rooms: Array<IRoom>,
+    private _matcher: FaceMatcher,
+    private _logger: Logger,
+    private _config: IConfig
+  ) {
+    this._stateChangedEvent = new Event();
+
+    //Initialize state
+    for (const room of this._rooms) {
+      this._streamsByRoom[room.name] = [
+        ...room.rtspConnectionStrings.map((connectionString) => {
+          const rtsp = new Rtsp(connectionString, {
+            rate: 0.7,
+            image: true,
+          });
+          rtsp.dataEvent.push((sender: Rtsp, args: IStreamEventArgs) =>
+            this.onData(room.name, args)
+          );
+          rtsp.closeEvent.push((sender: Rtsp, args: ICloseEventArgs) =>
+            this.onExit(connectionString, args)
+          );
+          rtsp.errorEvent.push((sender: Rtsp, args: IErrorEventArgs) =>
+            this.onError(args, connectionString)
+          );
+          if (this._config.debug) {
+            rtsp.messageEvent.push((sender: Rtsp, args: IMessageEventArgs) => {
+              this._logger.info(`[${connectionString}] ${args.message}`);
+            });
+          }
+
+          return rtsp;
+        }),
+      ];
+
+      _matcher.labeledDescriptors.forEach((descriptor) => {
+        this._state[descriptor.label] = null;
+      });
+    }
+  }
+
+  /**
+   * @method getState
+   *
+   * @param label The name of the label to retrieve state for
+   *
+   * The last known room of the requested label
+   */
+  public getState(label: string): string | null {
+    return this._state[label];
+  }
+
+  /**
+   * @property labels
+   *
+   * Gets the list of labels associated with the monitor
+   */
+  public get labels(): Array<string> {
+    return this._matcher.labeledDescriptors
+      .map((descriptor) => descriptor.label)
+      .filter(
+        (label: string, index: number, array: Array<string>) =>
+          array.indexOf(label) === index
+      );
+  }
+
+  public get stateChangedEvent(): Event<this, IStateChangeEventArgs> {
+    return this._stateChangedEvent;
+  }
+
+  /**
+   * @method startStreams
+   *
+   * Starts monitoring rtsp streams
+   */
+  public startStreams() {
+    for (const key in this._streamsByRoom) {
+      for (const stream of this._streamsByRoom[key]) {
+        stream.start();
+      }
+    }
+  }
+
+  /**
+   * @method closeStreams
+   *
+   * Stops monitoring rtsp streams
+   */
+  public closeStreams() {
+    for (const key in this._streamsByRoom) {
+      for (const stream of this._streamsByRoom[key]) {
+        stream.close();
+      }
+    }
+  }
+
+  private onData = async (room: string, args: IStreamEventArgs) => {
+    const input = ((await canvas.loadImage(args.data)) as unknown) as ImageData;
+    const out = faceapi.createCanvasFromMedia(input);
+    const resultsQuery = await faceapi
+      .detectAllFaces(out, getFaceDetectorOptions(this._faceDetectionNet))
+      .withFaceLandmarks()
+      .withFaceDescriptors();
+
+    //Write to output image
+    if (this._config.writeOutput) {
+      await saveFile(this._config.outputDirectory, room + ".jpg", args.data);
+    }
+
+    for (const res of resultsQuery) {
+      const bestMatch = this._matcher.matchDescriptor(res.descriptor);
+      const old = this._state[bestMatch.label];
+      this._state[bestMatch.label] = room;
+      this._stateChangedEvent.fire(this, {
+        old: old,
+        new: room,
+        label: bestMatch.label,
+      });
+
+      this._logger.info(`Face Detected: ${bestMatch.label} in room ${room}`);
+    }
+  };
+
+  private onError = (args: IErrorEventArgs, streamName: string) => {
+    this._logger.info(`[${streamName}] ${args.message}`);
+  };
+  private onExit = (streamName: string, args: ICloseEventArgs) => {
+    this._logger.info(`[${streamName}] Stream has exited: ${args.message}`);
+  };
+}

src/rtsp/options.ts

@@ -0,0 +1,7 @@
+export interface IOptions {
+  rate?: number;
+  quality?: number;
+  resolution?: string;
+  codec?: string;
+  image?: boolean;
+}

src/rtsp/rtsp.ts

@@ -0,0 +1,170 @@
+import { ChildProcess, spawn } from "child_process";
+import { Writable } from "stream";
+import { IOptions } from "./options";
+import { Event } from "../events";
+
+const ef1 = "ff";
+const ef2 = "d9";
+
+export interface IStreamEventArgs {
+  data: Buffer;
+}
+
+export interface ICloseEventArgs {
+  message: string;
+}
+export interface IErrorEventArgs {
+  message?: string;
+  err?: Error;
+}
+
+export interface IMessageEventArgs {
+  message: string;
+}
+
+export class Rtsp {
+  private _connecteionString: string;
+  private _childProcess: ChildProcess | undefined;
+  private _started: boolean;
+  private _buffer: Buffer;
+  private _options: IOptions;
+  private _paused: boolean;
+
+  private _dataEvent: Event<this, IStreamEventArgs>;
+  private _closeEvent: Event<this, ICloseEventArgs>;
+  private _errorEvent: Event<this, IErrorEventArgs>;
+  private _messageEvent: Event<this, IMessageEventArgs>;
+
+  constructor(connectionString: string, options: IOptions) {
+    this._started = false;
+    this._connecteionString = connectionString;
+    this._childProcess = undefined;
+    this._buffer = Buffer.from("");
+    this._options = options;
+    this._paused = false;
+    this._dataEvent = new Event();
+    this._closeEvent = new Event();
+    this._errorEvent = new Event();
+    this._messageEvent = new Event();
+
+    this.onData = this.onData.bind(this);
+  }
+
+  public get isStarted(): boolean {
+    return this._started;
+  }
+
+  public get isPaused(): boolean {
+    return this._paused;
+  }
+
+  public get dataEvent(): Event<this, IStreamEventArgs> {
+    return this._dataEvent;
+  }
+
+  public get messageEvent(): Event<this, IMessageEventArgs> {
+    return this._messageEvent;
+  }
+
+  public get closeEvent(): Event<this, ICloseEventArgs> {
+    return this._closeEvent;
+  }
+
+  public get errorEvent(): Event<this, IErrorEventArgs> {
+    return this._errorEvent;
+  }
+
+  public start(): void {
+    const argStrings = [
+      `-i ${this._connecteionString}`,
+      `-r ${this._options.rate ?? 10}`,
+      `-vf mpdecimate,setpts=N/FRAME_RATE/TB`,
+      this._options.image
+        ? `-f image2`
+        : `-codec:v ${this._options.codec ?? "libx264"}`,
+      `-update 1 -`,
+    ];
+    const args = argStrings.join(" ");
+    this._childProcess = spawn("ffmpeg", args.split(/\s+/));
+
+    if (!this._childProcess) {
+      return;
+    }
+
+    this._childProcess.stdout?.on("data", this.onData);
+    this._childProcess.stdout?.on("error", (err) =>
+      console.log("And error occurred" + err)
+    );
+    this._childProcess.stdout?.on("close", () => console.log("Stream closed"));
+    this._childProcess.stdout?.on("end", () => console.log("Stream ended"));
+
+    //Only register this event if there are subscribers
+    if (this._childProcess.stderr && this._messageEvent.length > 0) {
+      this._childProcess.stderr.on("data", this.onMessage);
+    }
+
+    this._childProcess.on("close", (code: number, signal: NodeJS.Signals) =>
+      this._closeEvent.fire(this, {
+        message: "FFmpeg exited with code: " + code + " and signal: " + signal,
+      })
+    );
+
+    this._childProcess.on("exit", (code: number, signal: NodeJS.Signals) =>
+      this._closeEvent.fire(this, {
+        message: "FFmpeg exited with code: " + code + " and signal: " + signal,
+      })
+    );
+
+    this._childProcess.on("error", (error: Error) =>
+      this._errorEvent.fire(this, { err: error })
+    );
+  }
+
+  public close(): void {
+    this._childProcess && this._childProcess.kill("SIGKILL");
+    this._closeEvent.fire(this, { message: "Process killed by user" });
+  }
+
+  public pause(): void {
+    this._paused = true;
+  }
+
+  public resume(): void {
+    this._paused = false;
+  }
+
+  public getStdin(): Writable | null {
+    return this._childProcess ? this._childProcess.stdin : null;
+  }
+
+  private onMessage = (data: any): void => {
+    if (!this._started) {
+      this._started = true;
+    }
+    let msg = "";
+    data
+      .toString()
+      .split(/\n/)
+      .forEach((line: string) => {
+        msg += `${line}\n`;
+      });
+
+    this._messageEvent.fire(this, { message: msg });
+  };
+
+  private onData(data: Buffer): void {
+    if (!this._paused && data.length > 1) {
+      this._buffer = this._buffer
+        ? Buffer.concat([this._buffer, data])
+        : (this._buffer = Buffer.from(data));
+      //End of image
+      if (
+        data[data.length - 2].toString(16) == ef1 &&
+        data[data.length - 1].toString(16) == ef2
+      ) {
+        this._dataEvent.fire(this, { data: this._buffer });
+        this._buffer = Buffer.from("");
+      }
+    }
+  }
+}

src/settings.ts

@@ -0,0 +1,9 @@
+/**
+ * This is the name of the platform that users will use to register the plugin in the Homebridge config.json
+ */
+export const PLATFORM_NAME = "HomeLocation";
+
+/**
+ * This must match the name of your plugin as defined the package.json
+ */
+export const PLUGIN_NAME = "homebridge-face-location";

tsconfig.json

@@ -0,0 +1,66 @@
+{
+  "compilerOptions": {
+    /* Basic Options */
+    // "incremental": true,                   /* Enable incremental compilation */
+    "target": "es5" /* Specify ECMAScript target version: 'ES3' (default), 'ES5', 'ES2015', 'ES2016', 'ES2017', 'ES2018', 'ES2019' or 'ESNEXT'. */,
+    "module": "commonjs" /* Specify module code generation: 'none', 'commonjs', 'amd', 'system', 'umd', 'es2015', or 'ESNext'. */,
+    // "lib": [],                             /* Specify library files to be included in the compilation. */
+    // "allowJs": true,                       /* Allow javascript files to be compiled. */
+    // "checkJs": true,                       /* Report errors in .js files. */
+    // "jsx": "preserve",                     /* Specify JSX code generation: 'preserve', 'react-native', or 'react'. */
+    // "declaration": true,                   /* Generates corresponding '.d.ts' file. */
+    // "declarationMap": true,                /* Generates a sourcemap for each corresponding '.d.ts' file. */
+    "sourceMap": true /* Generates corresponding '.map' file. */,
+    // "outFile": "./",                       /* Concatenate and emit output to single file. */
+    "outDir": "./bin" /* Redirect output structure to the directory. */,
+    "rootDir": "./src" /* Specify the root directory of input files. Use to control the output directory structure with --outDir. */,
+    "composite": true /* Enable project compilation */,
+    // "tsBuildInfoFile": "./",               /* Specify file to store incremental compilation information */
+    // "removeComments": true,                /* Do not emit comments to output. */
+    // "noEmit": true,                        /* Do not emit outputs. */
+    // "importHelpers": true,                 /* Import emit helpers from 'tslib'. */
+    // "downlevelIteration": true,            /* Provide full support for iterables in 'for-of', spread, and destructuring when targeting 'ES5' or 'ES3'. */
+    // "isolatedModules": true,               /* Transpile each file as a separate module (similar to 'ts.transpileModule'). */
+    /* Strict Type-Checking Options */
+    "strict": true /* Enable all strict type-checking options. */,
+    "noImplicitAny": true /* Raise error on expressions and declarations with an implied 'any' type. */,
+    // "strictNullChecks": true,              /* Enable strict null checks. */
+    "strictFunctionTypes": true /* Enable strict checking of function types. */,
+    // "strictBindCallApply": true,           /* Enable strict 'bind', 'call', and 'apply' methods on functions. */
+    // "strictPropertyInitialization": true,  /* Enable strict checking of property initialization in classes. */
+    // "noImplicitThis": true,                /* Raise error on 'this' expressions with an implied 'any' type. */
+    // "alwaysStrict": true,                  /* Parse in strict mode and emit "use strict" for each source file. */
+    /* Additional Checks */
+    // "noUnusedLocals": true,                /* Report errors on unused locals. */
+    // "noUnusedParameters": true,            /* Report errors on unused parameters. */
+    "noImplicitReturns": true /* Report error when not all code paths in function return a value. */,
+    "noFallthroughCasesInSwitch": true /* Report errors for fallthrough cases in switch statement. */,
+    /* Module Resolution Options */
+    // "moduleResolution": "node",            /* Specify module resolution strategy: 'node' (Node.js) or 'classic' (TypeScript pre-1.6). */
+    "baseUrl": "./" /* Base directory to resolve non-absolute module names. */,
+    "paths": {
+      "rtsp/*": ["node_modules/rtsp-stream/lib/*"],
+      "common/*": ["node_modules/node-common/lib/*"]
+    } /* A series of entries which re-map imports to lookup locations relative to the 'baseUrl'. */,
+    // "rootDirs": [],                        /* List of root folders whose combined content represents the structure of the project at runtime. */
+    // "typeRoots": [],                       /* List of folders to include type definitions from. */
+    // "types": [],                           /* Type declaration files to be included in compilation. */
+    // "allowSyntheticDefaultImports": true,  /* Allow default imports from modules with no default export. This does not affect code emit, just typechecking. */
+    "esModuleInterop": true /* Enables emit interoperability between CommonJS and ES Modules via creation of namespace objects for all imports. Implies 'allowSyntheticDefaultImports'. */,
+    // "preserveSymlinks": true,              /* Do not resolve the real path of symlinks. */
+    // "allowUmdGlobalAccess": true,          /* Allow accessing UMD globals from modules. */
+    /* Source Map Options */
+    // "sourceRoot": "",                      /* Specify the location where debugger should locate TypeScript files instead of source locations. */
+    // "mapRoot": "",                         /* Specify the location where debugger should locate map files instead of generated locations. */
+    // "inlineSourceMap": true,               /* Emit a single file with source maps instead of having a separate file. */
+    // "inlineSources": true,                 /* Emit the source alongside the sourcemaps within a single file; requires '--inlineSourceMap' or '--sourceMap' to be set. */
+    /* Experimental Options */
+    // "experimentalDecorators": true,        /* Enables experimental support for ES7 decorators. */
+    // "emitDecoratorMetadata": true,         /* Enables experimental support for emitting type metadata for decorators. */
+    /* Advanced Options */
+    "skipLibCheck": true,
+    "forceConsistentCasingInFileNames": true /* Disallow inconsistently-cased references to the same file. */
+  },
+  "include": ["./src"],
+  "exclude": ["node_modules"]
+}

weights/face_landmark_68_tiny_model-weights_manifest.json

@@ -0,0 +1 @@
+[{"weights":[{"name":"dense0/conv0/filters","shape":[3,3,3,32],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.008194216092427571,"min":-0.9423348506291708}},{"name":"dense0/conv0/bias","shape":[32],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.006839508168837603,"min":-0.8412595047670252}},{"name":"dense0/conv1/depthwise_filter","shape":[3,3,32,1],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.009194007106855804,"min":-1.2779669878529567}},{"name":"dense0/conv1/pointwise_filter","shape":[1,1,32,32],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.0036026100317637128,"min":-0.3170296827952067}},{"name":"dense0/conv1/bias","shape":[32],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.000740380117706224,"min":-0.06367269012273527}},{"name":"dense0/conv2/depthwise_filter","shape":[3,3,32,1],"dtype":"float32","quantization":{"dtype":"uint8","scale":1,"min":0}},{"name":"dense0/conv2/pointwise_filter","shape":[1,1,32,32],"dtype":"float32","quantization":{"dtype":"uint8","scale":1,"min":0}},{"name":"dense0/conv2/bias","shape":[32],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.0037702228508743585,"min":-0.6220867703942692}},{"name":"dense1/conv0/depthwise_filter","shape":[3,3,32,1],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.0033707996209462483,"min":-0.421349952618281}},{"name":"dense1/conv0/pointwise_filter","shape":[1,1,32,64],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.014611541991140328,"min":-1.8556658328748217}},{"name":"dense1/conv0/bias","shape":[64],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.002832523046755323,"min":-0.30307996600281956}},{"name":"dense1/conv1/depthwise_filter","shape":[3,3,64,1],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.006593170586754294,"min":-0.6329443763284123}},{"name":"dense1/conv1/pointwise_filter","shape":[1,1,64,64],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.012215249211180444,"min":-1.6001976466646382}},{"name":"dense1/conv1/bias","shape":[64],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.002384825547536214,"min":-0.3028728445370992}},{"name":"dense1/conv2/depthwise_filter","shape":[3,3,64,1],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.005859645441466687,"min":-0.7617539073906693}},{"name":"dense1/conv2/pointwise_filter","shape":[1,1,64,64],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.013121426806730382,"min":-1.7845140457153321}},{"name":"dense1/conv2/bias","shape":[64],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.0032247188044529336,"min":-0.46435950784122243}},{"name":"dense2/conv0/depthwise_filter","shape":[3,3,64,1],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.002659512618008782,"min":-0.32977956463308894}},{"name":"dense2/conv0/pointwise_filter","shape":[1,1,64,128],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.015499923743453681,"min":-1.9839902391620712}},{"name":"dense2/conv0/bias","shape":[128],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.0032450980999890497,"min":-0.522460794098237}},{"name":"dense2/conv1/depthwise_filter","shape":[3,3,128,1],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.005911862382701799,"min":-0.792189559282041}},{"name":"dense2/conv1/pointwise_filter","shape":[1,1,128,128],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.021025861478319356,"min":-2.2077154552235325}},{"name":"dense2/conv1/bias","shape":[128],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.00349616945958605,"min":-0.46149436866535865}},{"name":"dense2/conv2/depthwise_filter","shape":[3,3,128,1],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.008104994250278847,"min":-1.013124281284856}},{"name":"dense2/conv2/pointwise_filter","shape":[1,1,128,128],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.029337059282789044,"min":-3.5791212325002633}},{"name":"dense2/conv2/bias","shape":[128],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.0038808938334969913,"min":-0.4230174278511721}},{"name":"fc/weights","shape":[128,136],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.014016061670639936,"min":-1.8921683255363912}},{"name":"fc/bias","shape":[136],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.0029505149698724935,"min":0.088760145008564}}],"paths":["face_landmark_68_tiny_model-shard1"]}]

weights/mtcnn_model-weights_manifest.json

@@ -0,0 +1 @@
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weights/tiny_face_detector_model-weights_manifest.json

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