add typedocs and types

.eslintrc.json

@@ -38,6 +38,7 @@
     "import/extensions": "off",
     "import/no-absolute-path": "off",
     "import/no-extraneous-dependencies": "off",
+    "import/no-named-as-default": "off",
     "import/no-unresolved": "off",
     "import/prefer-default-export": "off",
     "lines-between-class-members": "off",

CHANGELOG.md

@@ -9,6 +9,12 @@ Repository: **<git+https://github.com/vladmandic/human.git>**
 
 ## Changelog
 
+### **HEAD -> main** 2021/03/13 mandic00@live.com
+
+
+### **origin/main** 2021/03/13 mandic00@live.com
+
+
 ### **1.1.2** 2021/03/12 mandic00@live.com
 
 - distance based on minkowski space and limited euclidean space

TODO.md

@@ -23,7 +23,6 @@
 
 ## WiP Items
 
-- face.tensor should return image in correct aspect ratio
 - box sizing on mobile
 
 ## Issues

package-lock.json

@@ -36,6 +36,7 @@
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@@ -2596,6 +2636,24 @@
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@@ -2961,6 +3025,30 @@
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@@ -3281,6 +3369,18 @@
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@@ -3452,6 +3552,33 @@
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@@ -3846,6 +3973,88 @@
         "url": "https://github.com/sponsors/sindresorhus"
       }
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@@ -3859,6 +4068,19 @@
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+          "resolved": "https://registry.npmjs.org/yallist/-/yallist-3.1.1.tgz",
+          "integrity": "sha512-a4UGQaWPH59mOXUYnAG2ewncQS4i4F43Tv3JoAM+s2VDAmS9NsK8GpDMLrCHPksFT7h3K6TOoUNn2pb7RoXx4g==",
+          "dev": true
+        }
+      }
+    },
     "optionator": {
       "version": "0.9.1",
       "resolved": "https://registry.npmjs.org/optionator/-/optionator-0.9.1.tgz",
@@ -6656,6 +6959,15 @@
         "picomatch": "^2.2.1"
       }
     },
+    "rechoir": {
+      "version": "0.6.2",
+      "resolved": "https://registry.npmjs.org/rechoir/-/rechoir-0.6.2.tgz",
+      "integrity": "sha1-hSBLVNuoLVdC4oyWdW70OvUOM4Q=",
+      "dev": true,
+      "requires": {
+        "resolve": "^1.1.6"
+      }
+    },
     "regenerator-runtime": {
       "version": "0.13.7",
       "resolved": "https://registry.npmjs.org/regenerator-runtime/-/regenerator-runtime-0.13.7.tgz",
@@ -6773,6 +7085,27 @@
       "integrity": "sha512-7++dFhtcx3353uBaq8DDR4NuxBetBzC7ZQOhmTQInHEd6bSrXdiEyzCvG07Z44UYdLShWUyXt5M/yhz8ekcb1A==",
       "dev": true
     },
+    "shelljs": {
+      "version": "0.8.4",
+      "resolved": "https://registry.npmjs.org/shelljs/-/shelljs-0.8.4.tgz",
+      "integrity": "sha512-7gk3UZ9kOfPLIAbslLzyWeGiEqx9e3rxwZM0KE6EL8GlGwjym9Mrlx5/p33bWTu9YG6vcS4MBxYZDHYr5lr8BQ==",
+      "dev": true,
+      "requires": {
+        "glob": "^7.0.0",
+        "interpret": "^1.0.0",
+        "rechoir": "^0.6.2"
+      }
+    },
+    "shiki": {
+      "version": "0.9.3",
+      "resolved": "https://registry.npmjs.org/shiki/-/shiki-0.9.3.tgz",
+      "integrity": "sha512-NEjg1mVbAUrzRv2eIcUt3TG7X9svX7l3n3F5/3OdFq+/BxUdmBOeKGiH4icZJBLHy354Shnj6sfBTemea2e7XA==",
+      "dev": true,
+      "requires": {
+        "onigasm": "^2.2.5",
+        "vscode-textmate": "^5.2.0"
+      }
+    },
     "signal-exit": {
       "version": "3.0.3",
       "resolved": "https://registry.npmjs.org/signal-exit/-/signal-exit-3.0.3.tgz",
@@ -7095,12 +7428,80 @@
       "integrity": "sha512-Ne+eE4r0/iWnpAxD852z3A+N0Bt5RN//NjJwRd2VFHEmrywxf5vsZlh4R6lixl6B+wz/8d+maTSAkN1FIkI3LQ==",
       "dev": true
     },
+    "typedoc": {
+      "version": "0.20.30",
+      "resolved": "https://registry.npmjs.org/typedoc/-/typedoc-0.20.30.tgz",
+      "integrity": "sha512-A4L6JDShPFwZDt9qp7FBsEpW7C6rA5fRv6ywgBuxGxZnT2wuF5afbWzmrwqHR3Xw38V1H2L4v/VJ0S/llBwV6Q==",
+      "dev": true,
+      "requires": {
+        "colors": "^1.4.0",
+        "fs-extra": "^9.1.0",
+        "handlebars": "^4.7.7",
+        "lodash": "^4.17.21",
+        "lunr": "^2.3.9",
+        "marked": "^2.0.1",
+        "minimatch": "^3.0.0",
+        "progress": "^2.0.3",
+        "shelljs": "^0.8.4",
+        "shiki": "^0.9.2",
+        "typedoc-default-themes": "^0.12.8"
+      },
+      "dependencies": {
+        "colors": {
+          "version": "1.4.0",
+          "resolved": "https://registry.npmjs.org/colors/-/colors-1.4.0.tgz",
+          "integrity": "sha512-a+UqTh4kgZg/SlGvfbzDHpgRu7AAQOmmqRHJnxhRZICKFUT91brVhNNt58CMWU9PsBbv3PDCZUHbVxuDiH2mtA==",
+          "dev": true
+        },
+        "fs-extra": {
+          "version": "9.1.0",
+          "resolved": "https://registry.npmjs.org/fs-extra/-/fs-extra-9.1.0.tgz",
+          "integrity": "sha512-hcg3ZmepS30/7BSFqRvoo3DOMQu7IjqxO5nCDt+zM9XWjb33Wg7ziNT+Qvqbuc3+gWpzO02JubVyk2G4Zvo1OQ==",
+          "dev": true,
+          "requires": {
+            "at-least-node": "^1.0.0",
+            "graceful-fs": "^4.2.0",
+            "jsonfile": "^6.0.1",
+            "universalify": "^2.0.0"
+          }
+        },
+        "jsonfile": {
+          "version": "6.1.0",
+          "resolved": "https://registry.npmjs.org/jsonfile/-/jsonfile-6.1.0.tgz",
+          "integrity": "sha512-5dgndWOriYSm5cnYaJNhalLNDKOqFwyDB/rr1E9ZsGciGvKPs8R2xYGCacuf3z6K1YKDz182fd+fY3cn3pMqXQ==",
+          "dev": true,
+          "requires": {
+            "graceful-fs": "^4.1.6",
+            "universalify": "^2.0.0"
+          }
+        },
+        "universalify": {
+          "version": "2.0.0",
+          "resolved": "https://registry.npmjs.org/universalify/-/universalify-2.0.0.tgz",
+          "integrity": "sha512-hAZsKq7Yy11Zu1DE0OzWjw7nnLZmJZYTDZZyEFHZdUhV8FkH5MCfoU1XMaxXovpyW5nq5scPqq0ZDP9Zyl04oQ==",
+          "dev": true
+        }
+      }
+    },
+    "typedoc-default-themes": {
+      "version": "0.12.8",
+      "resolved": "https://registry.npmjs.org/typedoc-default-themes/-/typedoc-default-themes-0.12.8.tgz",
+      "integrity": "sha512-tyjyDTKy/JLnBSwvhoqd99VIjrP33SdOtwcMD32b+OqnrjZWe8HmZECbfBoacqoxjHd58gfeNw6wA7uvqWFa4w==",
+      "dev": true
+    },
     "typescript": {
       "version": "4.2.3",
       "resolved": "https://registry.npmjs.org/typescript/-/typescript-4.2.3.tgz",
       "integrity": "sha512-qOcYwxaByStAWrBf4x0fibwZvMRG+r4cQoTjbPtUlrWjBHbmCAww1i448U0GJ+3cNNEtebDteo/cHOR3xJ4wEw==",
       "dev": true
     },
+    "uglify-js": {
+      "version": "3.13.1",
+      "resolved": "https://registry.npmjs.org/uglify-js/-/uglify-js-3.13.1.tgz",
+      "integrity": "sha512-EWhx3fHy3M9JbaeTnO+rEqzCe1wtyQClv6q3YWq0voOj4E+bMZBErVS1GAHPDiRGONYq34M1/d8KuQMgvi6Gjw==",
+      "dev": true,
+      "optional": true
+    },
     "unbox-primitive": {
       "version": "1.0.0",
       "resolved": "https://registry.npmjs.org/unbox-primitive/-/unbox-primitive-1.0.0.tgz",
@@ -7187,6 +7588,12 @@
       "integrity": "sha512-u0Lw+IYlgbEJFF6/qAqG2d1jQmJl0eyAGJHoAJqr2HT4M2BNuQYSEiSE75f52pXHSJm8AlTjnLLbBFPrdz2hpA==",
       "dev": true
     },
+    "vscode-textmate": {
+      "version": "5.2.0",
+      "resolved": "https://registry.npmjs.org/vscode-textmate/-/vscode-textmate-5.2.0.tgz",
+      "integrity": "sha512-Uw5ooOQxRASHgu6C7GVvUxisKXfSgW4oFlO+aa+PAkgmH89O3CXxEEzNRNtHSqtXFTl0nAC1uYj0GMSH27uwtQ==",
+      "dev": true
+    },
     "vscode-uri": {
       "version": "2.1.2",
       "resolved": "https://registry.npmjs.org/vscode-uri/-/vscode-uri-2.1.2.tgz",
@@ -7230,6 +7637,12 @@
       "integrity": "sha512-Hz/mrNwitNRh/HUAtM/VT/5VH+ygD6DV7mYKZAtHOrbs8U7lvPS6xf7EJKMF0uW1KJCl0H701g3ZGus+muE5vQ==",
       "dev": true
     },
+    "wordwrap": {
+      "version": "1.0.0",
+      "resolved": "https://registry.npmjs.org/wordwrap/-/wordwrap-1.0.0.tgz",
+      "integrity": "sha1-J1hIEIkUVqQXHI0CJkQa3pDLyus=",
+      "dev": true
+    },
     "wrap-ansi": {
       "version": "7.0.0",
       "resolved": "https://registry.npmjs.org/wrap-ansi/-/wrap-ansi-7.0.0.tgz",

package.json

@@ -6,7 +6,7 @@
   "main": "dist/human.node.js",
   "module": "dist/human.esm.js",
   "browser": "dist/human.esm.js",
-  "types": "types/human.d.ts",
+  "types": "types/src/human.d.ts",
   "author": "Vladimir Mandic <mandic00@live.com>",
   "bugs": {
     "url": "https://github.com/vladmandic/human/issues"
@@ -23,7 +23,7 @@
   "scripts": {
     "start": "node --trace-warnings --unhandled-rejections=strict --trace-uncaught --no-deprecation demo/node.js",
     "dev": "node --trace-warnings --unhandled-rejections=strict --trace-uncaught server/serve.js",
-    "build": "rimraf dist/* && rimraf types/* && node --trace-warnings --unhandled-rejections=strict --trace-uncaught server/build.js && node server/changelog.js",
+    "build": "rimraf dist/* types/* typedoc/* && node --trace-warnings --unhandled-rejections=strict --trace-uncaught server/build.js",
     "lint": "eslint src server demo",
     "test": "npm run lint && npm run start"
   },
@@ -71,6 +71,7 @@
     "rimraf": "^3.0.2",
     "simple-git": "^2.36.2",
     "tslib": "^2.1.0",
+    "typedoc": "^0.20.30",
     "typescript": "^4.2.3"
   }
 }

server/build.js

@@ -1,11 +1,14 @@
 #!/usr/bin/env -S node --trace-warnings
 
+const ts = require('typescript');
 const log = require('@vladmandic/pilogger');
 const esbuild = require('esbuild');
-const ts = require('typescript');
+const TypeDoc = require('typedoc');
+const changelog = require('./changelog');
 
 // keeps esbuild service instance cached
 let busy = false;
+let td = null;
 const banner = { js: `
   /*
   Human library
@@ -172,7 +175,7 @@ async function getStats(json) {
 }
 
 // rebuild typings
-function compile(entryPoint, options) {
+async function compile(entryPoint, options) {
   log.info('Compile typings:', entryPoint);
   const program = ts.createProgram(entryPoint, options);
   const emit = program.emit();
@@ -192,6 +195,18 @@ function compile(entryPoint, options) {
   }
 }
 
+async function typedoc(entryPoint) {
+  log.info('Generate TypeDocs:', entryPoint);
+  if (!td) {
+    td = new TypeDoc.Application();
+    td.options.addReader(new TypeDoc.TSConfigReader());
+    td.bootstrap({ entryPoints: entryPoint });
+  }
+  const project = td.convert();
+  const result = project ? await td.generateDocs(project, 'typedoc') : null;
+  if (result) log.warn('TypeDoc:', result);
+}
+
 // rebuild on file change
 async function build(f, msg, dev = false) {
   if (busy) {
@@ -217,8 +232,12 @@ async function build(f, msg, dev = false) {
         log.state(`Build for: ${targetGroupName} type: ${targetName}:`, stats);
       }
     }
-    // generate typings
+    if (!dev) {
-    compile(targets.browserBundle.esm.entryPoints, tsconfig);
+      // generate typings & typedoc only when run as explict build
+      await compile(targets.browserBundle.esm.entryPoints, tsconfig);
+      await changelog.update('../CHANGELOG.md');
+      await typedoc(targets.browserBundle.esm.entryPoints);
+    }
     if (require.main === module) process.exit(0);
   } catch (err) {
     // catch errors and print where it occured

server/changelog.js

@@ -45,15 +45,11 @@ async function update(f) {
 
   const name = path.join(__dirname, f);
   fs.writeFileSync(name, text);
-  logger.state('Change log updated:', name);
+  logger.info('Update Change log:', [name]);
 }
 
-exports.update = update;
+if (require.main === module) {
-
+  update('../CHANGELOG.md');
-try {
+} else {
-  if (require.main === module) {
+  exports.update = update;
-    update('../CHANGELOG.md');
-  }
-} catch {
-  //
 }

server/serve.js

@@ -32,7 +32,7 @@ const options = {
   httpsPort: 10031,
   insecureHTTPParser: false,
   minElapsed: 2,
-  monitor: ['package.json', 'config.js', 'demo', 'src'],
+  monitor: ['package.json', 'config.ts', 'demo', 'src'],
 };
 
 // just some predefined mime types

src/blazeface/facemesh.ts

@@ -13,9 +13,9 @@ export class MediaPipeFaceMesh {
     this.config = config;
   }
 
-  async estimateFaces(input, config) {
+  async estimateFaces(input, config): Promise<{ confidence, boxConfidence, faceConfidence, box, mesh, boxRaw, meshRaw, annotations, image }[]> {
     const predictions = await this.facePipeline.predict(input, config);
-    const results: Array<{}> = [];
+    const results: Array<{ confidence, boxConfidence, faceConfidence, box, mesh, boxRaw, meshRaw, annotations, image }> = [];
     for (const prediction of (predictions || [])) {
       if (prediction.isDisposedInternal) continue; // guard against disposed tensors on long running operations such as pause in middle of processing
       const mesh = prediction.coords ? prediction.coords.arraySync() : [];

src/draw.ts

@@ -2,22 +2,22 @@ import config from '../config';
 import { TRI468 as triangulation } from './blazeface/coords';
 
 export const options = {
-  color: 'rgba(173, 216, 230, 0.3)', // 'lightblue' with light alpha channel
+  color: <string>'rgba(173, 216, 230, 0.3)', // 'lightblue' with light alpha channel
-  labelColor: 'rgba(173, 216, 230, 1)', // 'lightblue' with dark alpha channel
+  labelColor: <string>'rgba(173, 216, 230, 1)', // 'lightblue' with dark alpha channel
-  shadowColor: 'black',
+  shadowColor: <string>'black',
-  font: 'small-caps 16px "Segoe UI"',
+  font: <string>'small-caps 16px "Segoe UI"',
-  lineHeight: 20,
+  lineHeight: <number>20,
-  lineWidth: 6,
+  lineWidth: <number>6,
-  pointSize: 2,
+  pointSize: <number>2,
-  roundRect: 28,
+  roundRect: <number>28,
-  drawPoints: false,
+  drawPoints: <Boolean>false,
-  drawLabels: true,
+  drawLabels: <Boolean>true,
-  drawBoxes: true,
+  drawBoxes: <Boolean>true,
-  drawPolygons: true,
+  drawPolygons: <Boolean>true,
-  fillPolygons: false,
+  fillPolygons: <Boolean>false,
-  useDepth: true,
+  useDepth: <Boolean>true,
-  useCurves: false,
+  useCurves: <Boolean>false,
-  bufferedOutput: false,
+  bufferedOutput: <Boolean>false,
 };
 
 function point(ctx, x, y, z = null) {

src/human.ts

@@ -24,6 +24,48 @@ const now = () => {
   return parseInt((Number(process.hrtime.bigint()) / 1000 / 1000).toString());
 };
 
+type Tensor = {};
+type Model = {};
+export type Result = {
+  face: Array<{
+    confidence: Number,
+    boxConfidence: Number,
+    faceConfidence: Number,
+    box: [Number, Number, Number, Number],
+    mesh: Array<[Number, Number, Number]>
+    meshRaw: Array<[Number, Number, Number]>
+    boxRaw: [Number, Number, Number, Number],
+    annotations: any,
+    age: Number,
+    gender: String,
+    genderConfidence: Number,
+    emotion: String,
+    embedding: any,
+    iris: Number,
+    angle: { roll: Number | null, yaw: Number | null, pitch: Number | null },
+  }>,
+  body: Array<{
+    id: Number,
+    part: String,
+    position: { x: Number, y: Number, z: Number },
+    score: Number,
+    presence: Number }>,
+  hand: Array<{
+    confidence: Number,
+    box: any,
+    landmarks: any,
+    annotations: any,
+  }>,
+  gesture: Array<{
+    part: String,
+    gesture: String,
+  }>,
+  performance: { any },
+  canvas: OffscreenCanvas | HTMLCanvasElement,
+}
+
+export type { default as Config } from '../config';
+
 // helper function: perform deep merge of multiple objects so it allows full inheriance with overrides
 function mergeDeep(...objects) {
   const isObject = (obj) => obj && typeof obj === 'object';
@@ -39,25 +81,25 @@ function mergeDeep(...objects) {
   }, {});
 }
 
-class Human {
+export class Human {
-  version: string;
+  version: String;
   config: typeof config.default;
-  state: string;
+  state: String;
-  image: { tensor: typeof tf.Tensor, canvas: OffscreenCanvas | HTMLCanvasElement };
+  image: { tensor: Tensor, canvas: OffscreenCanvas | HTMLCanvasElement };
   // classes
   tf: typeof tf;
-  draw: typeof draw;
+  draw: { options?: typeof draw.options, gesture: Function, face: Function, body: Function, hand: Function, canvas: Function, all: Function };
   // models
   models: {
-    face,
+    face: facemesh.MediaPipeFaceMesh | null,
-    posenet,
+    posenet: posenet.PoseNet | null,
-    blazepose,
+    blazepose: Model | null,
-    handpose,
+    handpose: handpose.HandPose | null,
-    iris,
+    iris: Model | null,
-    age,
+    age: Model | null,
-    gender,
+    gender: Model | null,
-    emotion,
+    emotion: Model | null,
-    embedding,
+    embedding: Model | null,
   };
   classes: {
     facemesh: typeof facemesh;
@@ -67,13 +109,13 @@ class Human {
     body: typeof posenet | typeof blazepose;
     hand: typeof handpose;
   };
-  sysinfo: { platform: string, agent: string };
+  sysinfo: { platform: String, agent: String };
   #package: any;
   #perf: any;
   #numTensors: number;
-  #analyzeMemoryLeaks: boolean;
+  #analyzeMemoryLeaks: Boolean;
-  #checkSanity: boolean;
+  #checkSanity: Boolean;
-  #firstRun: boolean;
+  #firstRun: Boolean;
   // definition end
 
   constructor(userConfig = {}) {
@@ -102,7 +144,7 @@ class Human {
     };
     // export access to image processing
     // @ts-ignore
-    this.image = (input: tf.Tensor | ImageData | HTMLCanvasElement | HTMLVideoElement | OffscreenCanvas) => image.process(input, this.config);
+    this.image = (input: Tensor | ImageData | HTMLCanvasElement | HTMLVideoElement | OffscreenCanvas) => image.process(input, this.config);
     // export raw access to underlying models
     this.classes = {
       facemesh,
@@ -122,6 +164,7 @@ class Human {
   }
 
   // helper function: measure tensor leak
+  /** @hidden */
   #analyze = (...msg) => {
     if (!this.#analyzeMemoryLeaks) return;
     const current = this.tf.engine().state.numTensors;
@@ -132,12 +175,11 @@ class Human {
   }
 
   // quick sanity check on inputs
-  #sanity = (input): null | string => {
+  /** @hidden */
+  #sanity = (input): null | String => {
     if (!this.#checkSanity) return null;
     if (!input) return 'input is not defined';
-    if (this.tf.ENV.flags.IS_NODE && !(input instanceof tf.Tensor)) {
+    if (this.tf.ENV.flags.IS_NODE && !(input instanceof tf.Tensor)) return 'input must be a tensor';
-      return 'input must be a tensor';
-    }
     try {
       this.tf.getBackend();
     } catch {
@@ -146,18 +188,18 @@ class Human {
     return null;
   }
 
-  simmilarity(embedding1: Array<number>, embedding2: Array<number>): number {
+  simmilarity(embedding1: Array<Number>, embedding2: Array<Number>): Number {
     if (this.config.face.embedding.enabled) return embedding.simmilarity(embedding1, embedding2);
     return 0;
   }
 
-  enhance(input: typeof tf.Tensor): typeof tf.Tensor | null {
+  enhance(input: Tensor): Tensor | null {
     if (this.config.face.embedding.enabled) return embedding.enhance(input);
     return null;
   }
 
   // preload models, not explicitly required as it's done automatically on first use
-  async load(userConfig = null) {
+  async load(userConfig: Object = {}) {
     this.state = 'load';
     const timeStamp = now();
     if (userConfig) this.config = mergeDeep(this.config, userConfig);
@@ -215,6 +257,7 @@ class Human {
   }
 
   // check if backend needs initialization if it changed
+  /** @hidden */
   #checkBackend = async (force = false) => {
     if (this.config.backend && (this.config.backend !== '') && force || (this.tf.getBackend() !== this.config.backend)) {
       const timeStamp = now();
@@ -267,7 +310,8 @@ class Human {
     }
   }
 
-  #calculateFaceAngle = (mesh): { roll: number | null, yaw: number | null, pitch: number | null } => {
+  /** @hidden */
+  #calculateFaceAngle = (mesh): { roll: Number | null, yaw: Number | null, pitch: Number | null } => {
     if (!mesh || mesh.length < 300) return { roll: null, yaw: null, pitch: null };
     const radians = (a1, a2, b1, b2) => Math.atan2(b2 - a2, b1 - a1);
     // eslint-disable-next-line no-unused-vars, @typescript-eslint/no-unused-vars
@@ -285,6 +329,7 @@ class Human {
     return angle;
   }
 
+  /** @hidden */
   #detectFace = async (input): Promise<any> => {
     // run facemesh, includes blazeface and iris
     // eslint-disable-next-line no-async-promise-executor
@@ -294,27 +339,29 @@ class Human {
     let emotionRes;
     let embeddingRes;
     const faceRes: Array<{
-      confidence: number,
+      confidence: Number,
-      boxConfidence: number,
+      boxConfidence: Number,
-      faceConfidence: number,
+      faceConfidence: Number,
-      box: [number, number, number, number],
+      box: [Number, Number, Number, Number],
-      mesh: Array<[number, number, number]>
+      mesh: Array<[Number, Number, Number]>
-      meshRaw: Array<[number, number, number]>
+      meshRaw: Array<[Number, Number, Number]>
-      boxRaw: [number, number, number, number],
+      boxRaw: [Number, Number, Number, Number],
       annotations: any,
-      age: number,
+      age: Number,
-      gender: string,
+      gender: String,
-      genderConfidence: number,
+      genderConfidence: Number,
-      emotion: string,
+      emotion: String,
       embedding: any,
-      iris: number,
+      iris: Number,
-      angle: { roll: number | null, yaw: number | null, pitch: number | null },
+      angle: { roll: Number | null, yaw: Number | null, pitch: Number | null },
+      tensor: Tensor,
     }> = [];
 
     this.state = 'run:face';
     timeStamp = now();
     const faces = await this.models.face?.estimateFaces(input, this.config);
     this.#perf.face = Math.trunc(now() - timeStamp);
+    if (!faces) return [];
     for (const face of faces) {
       this.#analyze('Get Face');
 
@@ -418,45 +465,7 @@ class Human {
   }
 
   // main detect function
-  async detect(input, userConfig = {}): Promise<{
+  async detect(input: Tensor | ImageData | HTMLCanvasElement | HTMLVideoElement | OffscreenCanvas, userConfig: Object = {}): Promise<Result | { error: String }> {
-      face: Array<{
-        confidence: number,
-        boxConfidence: number,
-        faceConfidence: number,
-        box: [number, number, number, number],
-        mesh: Array<[number, number, number]>
-        meshRaw: Array<[number, number, number]>
-        boxRaw: [number, number, number, number],
-        annotations: any,
-        age: number,
-        gender: string,
-        genderConfidence: number,
-        emotion: string,
-        embedding: any,
-        iris: number,
-        angle: { roll: number | null, yaw: number | null, pitch: number | null },
-      }>,
-      body: Array<{
-        id: number,
-        part: string,
-        position: { x: number, y: number, z: number },
-        score: number,
-        presence: number }>,
-      hand: Array<{
-        confidence: number,
-        box: any,
-        landmarks: any,
-        annotations: any,
-      }>,
-      gesture: Array<{
-        part: string,
-        gesture: string,
-      }>,
-      performance: { any },
-      canvas: OffscreenCanvas | HTMLCanvasElement
-    } | { error: string }> {
-    // end definition
-
     // detection happens inside a promise
     return new Promise(async (resolve) => {
       this.state = 'config';
@@ -562,6 +571,7 @@ class Human {
     });
   }
 
+  /** @hidden */
   #warmupBitmap = async () => {
     const b64toBlob = (base64, type = 'application/octet-stream') => fetch(`data:${type};base64,${base64}`).then((res) => res.blob());
     let blob;
@@ -579,6 +589,7 @@ class Human {
     return res;
   }
 
+  /** @hidden */
   #warmupCanvas = async () => new Promise((resolve) => {
     let src;
     let size = 0;
@@ -611,6 +622,7 @@ class Human {
     else resolve(null);
   });
 
+  /** @hidden */
   #warmupNode = async () => {
     const atob = (str) => Buffer.from(str, 'base64');
     const img = this.config.warmup === 'face' ? atob(sample.face) : atob(sample.body);
@@ -624,7 +636,7 @@ class Human {
     return res;
   }
 
-  async warmup(userConfig): Promise<{ face, body, hand, gesture, performance, canvas } | { error }> {
+  async warmup(userConfig: Object = {}): Promise<Result | { error }> {
     const t0 = now();
     if (userConfig) this.config = mergeDeep(this.config, userConfig);
     const video = this.config.videoOptimized;

tsconfig.json

@@ -22,4 +22,19 @@
   },
   "formatCodeOptions": { "indentSize": 2, "tabSize": 2 },
   "include": ["src/*", "src/***/*", "demo/*"],
+  "typedocOptions": {
+    "excludePrivate": true,
+    "excludeExternals": true,
+    "excludeProtected": true,
+    "excludeInternal": true,
+    "disableSources": true,
+    "gitRevision": "main",
+    "hideGenerator": "true",
+    "theme": "default",
+    "readme": "none",
+    "out": "typedoc",
+    "entryPoints": "src/human.ts",
+    "logLevel": "Error",
+    "logger": "none"
+  }
 }

types/blazeface/facemesh.d.ts

@@ -1,7 +0,0 @@
-export declare class MediaPipeFaceMesh {
-    facePipeline: any;
-    config: any;
-    constructor(blazeFace: any, blazeMeshModel: any, irisModel: any, config: any);
-    estimateFaces(input: any, config: any): Promise<{}[]>;
-}
-export declare function load(config: any): Promise<MediaPipeFaceMesh>;

types/config.d.ts

@@ -0,0 +1,101 @@
+declare const _default: {
+    backend: string;
+    wasmPath: string;
+    debug: boolean;
+    async: boolean;
+    profile: boolean;
+    deallocate: boolean;
+    scoped: boolean;
+    videoOptimized: boolean;
+    warmup: string;
+    filter: {
+        enabled: boolean;
+        width: number;
+        height: number;
+        return: boolean;
+        brightness: number;
+        contrast: number;
+        sharpness: number;
+        blur: number;
+        saturation: number;
+        hue: number;
+        negative: boolean;
+        sepia: boolean;
+        vintage: boolean;
+        kodachrome: boolean;
+        technicolor: boolean;
+        polaroid: boolean;
+        pixelate: number;
+    };
+    gesture: {
+        enabled: boolean;
+    };
+    face: {
+        enabled: boolean;
+        detector: {
+            modelPath: string;
+            rotation: boolean;
+            maxFaces: number;
+            skipFrames: number;
+            skipInitial: boolean;
+            minConfidence: number;
+            iouThreshold: number;
+            scoreThreshold: number;
+            return: boolean;
+        };
+        mesh: {
+            enabled: boolean;
+            modelPath: string;
+        };
+        iris: {
+            enabled: boolean;
+            modelPath: string;
+        };
+        age: {
+            enabled: boolean;
+            modelPath: string;
+            skipFrames: number;
+        };
+        gender: {
+            enabled: boolean;
+            minConfidence: number;
+            modelPath: string;
+            skipFrames: number;
+        };
+        emotion: {
+            enabled: boolean;
+            minConfidence: number;
+            skipFrames: number;
+            modelPath: string;
+        };
+        embedding: {
+            enabled: boolean;
+            modelPath: string;
+        };
+    };
+    body: {
+        enabled: boolean;
+        modelPath: string;
+        maxDetections: number;
+        scoreThreshold: number;
+        nmsRadius: number;
+    };
+    hand: {
+        enabled: boolean;
+        rotation: boolean;
+        skipFrames: number;
+        skipInitial: boolean;
+        minConfidence: number;
+        iouThreshold: number;
+        scoreThreshold: number;
+        maxHands: number;
+        landmarks: boolean;
+        detector: {
+            modelPath: string;
+        };
+        skeleton: {
+            modelPath: string;
+        };
+    };
+};
+export default _default;

types/human.d.ts

@@ -1,119 +0,0 @@
-import * as tf from '../dist/tfjs.esm.js';
-import * as facemesh from './blazeface/facemesh';
-import * as age from './age/age';
-import * as gender from './gender/gender';
-import * as emotion from './emotion/emotion';
-import * as posenet from './posenet/posenet';
-import * as handpose from './handpose/handpose';
-import * as blazepose from './blazepose/blazepose';
-import * as config from '../config';
-import * as draw from './draw';
-declare class Human {
-    #private;
-    version: string;
-    config: typeof config.default;
-    state: string;
-    image: {
-        tensor: typeof tf.Tensor;
-        canvas: OffscreenCanvas | HTMLCanvasElement;
-    };
-    tf: typeof tf;
-    draw: typeof draw;
-    models: {
-        face: any;
-        posenet: any;
-        blazepose: any;
-        handpose: any;
-        iris: any;
-        age: any;
-        gender: any;
-        emotion: any;
-        embedding: any;
-    };
-    classes: {
-        facemesh: typeof facemesh;
-        age: typeof age;
-        gender: typeof gender;
-        emotion: typeof emotion;
-        body: typeof posenet | typeof blazepose;
-        hand: typeof handpose;
-    };
-    sysinfo: {
-        platform: string;
-        agent: string;
-    };
-    constructor(userConfig?: {});
-    profileData(): {
-        newBytes: any;
-        newTensors: any;
-        peakBytes: any;
-        numKernelOps: any;
-        timeKernelOps: any;
-        slowestKernelOps: any;
-        largestKernelOps: any;
-    } | {};
-    simmilarity(embedding1: Array<number>, embedding2: Array<number>): number;
-    enhance(input: typeof tf.Tensor): typeof tf.Tensor | null;
-    load(userConfig?: null): Promise<void>;
-    detect(input: any, userConfig?: {}): Promise<{
-        face: Array<{
-            confidence: number;
-            boxConfidence: number;
-            faceConfidence: number;
-            box: [number, number, number, number];
-            mesh: Array<[number, number, number]>;
-            meshRaw: Array<[number, number, number]>;
-            boxRaw: [number, number, number, number];
-            annotations: any;
-            age: number;
-            gender: string;
-            genderConfidence: number;
-            emotion: string;
-            embedding: any;
-            iris: number;
-            angle: {
-                roll: number | null;
-                yaw: number | null;
-                pitch: number | null;
-            };
-        }>;
-        body: Array<{
-            id: number;
-            part: string;
-            position: {
-                x: number;
-                y: number;
-                z: number;
-            };
-            score: number;
-            presence: number;
-        }>;
-        hand: Array<{
-            confidence: number;
-            box: any;
-            landmarks: any;
-            annotations: any;
-        }>;
-        gesture: Array<{
-            part: string;
-            gesture: string;
-        }>;
-        performance: {
-            any: any;
-        };
-        canvas: OffscreenCanvas | HTMLCanvasElement;
-    } | {
-        error: string;
-    }>;
-    warmup(userConfig: any): Promise<{
-        face: any;
-        body: any;
-        hand: any;
-        gesture: any;
-        performance: any;
-        canvas: any;
-    } | {
-        error: any;
-    }>;
-}
-export { Human as default };

types/src/blazeface/facemesh.d.ts

@@ -0,0 +1,17 @@
+export declare class MediaPipeFaceMesh {
+    facePipeline: any;
+    config: any;
+    constructor(blazeFace: any, blazeMeshModel: any, irisModel: any, config: any);
+    estimateFaces(input: any, config: any): Promise<{
+        confidence: any;
+        boxConfidence: any;
+        faceConfidence: any;
+        box: any;
+        mesh: any;
+        boxRaw: any;
+        meshRaw: any;
+        annotations: any;
+        image: any;
+    }[]>;
+}
+export declare function load(config: any): Promise<MediaPipeFaceMesh>;

types/src/draw.d.ts

@@ -7,14 +7,14 @@ export declare const options: {
     lineWidth: number;
     pointSize: number;
     roundRect: number;
-    drawPoints: boolean;
+    drawPoints: Boolean;
-    drawLabels: boolean;
+    drawLabels: Boolean;
-    drawBoxes: boolean;
+    drawBoxes: Boolean;
-    drawPolygons: boolean;
+    drawPolygons: Boolean;
-    fillPolygons: boolean;
+    fillPolygons: Boolean;
-    useDepth: boolean;
+    useDepth: Boolean;
-    useCurves: boolean;
+    useCurves: Boolean;
-    bufferedOutput: boolean;
+    bufferedOutput: Boolean;
 };
 export declare function gesture(inCanvas: any, result: any): Promise<void>;
 export declare function face(inCanvas: any, result: any): Promise<void>;

types/src/human.d.ts

@@ -0,0 +1,124 @@
+import * as tf from '../dist/tfjs.esm.js';
+import * as facemesh from './blazeface/facemesh';
+import * as age from './age/age';
+import * as gender from './gender/gender';
+import * as emotion from './emotion/emotion';
+import * as posenet from './posenet/posenet';
+import * as handpose from './handpose/handpose';
+import * as blazepose from './blazepose/blazepose';
+import * as config from '../config';
+import * as draw from './draw';
+declare type Tensor = {};
+declare type Model = {};
+export declare type Result = {
+    face: Array<{
+        confidence: Number;
+        boxConfidence: Number;
+        faceConfidence: Number;
+        box: [Number, Number, Number, Number];
+        mesh: Array<[Number, Number, Number]>;
+        meshRaw: Array<[Number, Number, Number]>;
+        boxRaw: [Number, Number, Number, Number];
+        annotations: any;
+        age: Number;
+        gender: String;
+        genderConfidence: Number;
+        emotion: String;
+        embedding: any;
+        iris: Number;
+        angle: {
+            roll: Number | null;
+            yaw: Number | null;
+            pitch: Number | null;
+        };
+    }>;
+    body: Array<{
+        id: Number;
+        part: String;
+        position: {
+            x: Number;
+            y: Number;
+            z: Number;
+        };
+        score: Number;
+        presence: Number;
+    }>;
+    hand: Array<{
+        confidence: Number;
+        box: any;
+        landmarks: any;
+        annotations: any;
+    }>;
+    gesture: Array<{
+        part: String;
+        gesture: String;
+    }>;
+    performance: {
+        any: any;
+    };
+    canvas: OffscreenCanvas | HTMLCanvasElement;
+};
+export type { default as Config } from '../config';
+export declare class Human {
+    #private;
+    version: String;
+    config: typeof config.default;
+    state: String;
+    image: {
+        tensor: Tensor;
+        canvas: OffscreenCanvas | HTMLCanvasElement;
+    };
+    tf: typeof tf;
+    draw: {
+        options?: typeof draw.options;
+        gesture: Function;
+        face: Function;
+        body: Function;
+        hand: Function;
+        canvas: Function;
+        all: Function;
+    };
+    models: {
+        face: facemesh.MediaPipeFaceMesh | null;
+        posenet: posenet.PoseNet | null;
+        blazepose: Model | null;
+        handpose: handpose.HandPose | null;
+        iris: Model | null;
+        age: Model | null;
+        gender: Model | null;
+        emotion: Model | null;
+        embedding: Model | null;
+    };
+    classes: {
+        facemesh: typeof facemesh;
+        age: typeof age;
+        gender: typeof gender;
+        emotion: typeof emotion;
+        body: typeof posenet | typeof blazepose;
+        hand: typeof handpose;
+    };
+    sysinfo: {
+        platform: String;
+        agent: String;
+    };
+    constructor(userConfig?: {});
+    profileData(): {
+        newBytes: any;
+        newTensors: any;
+        peakBytes: any;
+        numKernelOps: any;
+        timeKernelOps: any;
+        slowestKernelOps: any;
+        largestKernelOps: any;
+    } | {};
+    simmilarity(embedding1: Array<Number>, embedding2: Array<Number>): Number;
+    enhance(input: Tensor): Tensor | null;
+    load(userConfig?: Object): Promise<void>;
+    detect(input: Tensor | ImageData | HTMLCanvasElement | HTMLVideoElement | OffscreenCanvas, userConfig?: Object): Promise<Result | {
+        error: String;
+    }>;
+    warmup(userConfig?: Object): Promise<Result | {
+        error: any;
+    }>;
+}
+export { Human as default };

wiki

@@ -1 +1 @@
-Subproject commit 4c5d355a1d413c54f7f8ff2fa8bb39c535cc58b4
+Subproject commit 17f65ba8169f07140d23ea7b31f9c22b13b83642