ngx-scanner-face

This library is built to provide a solution analysis of human face recognition.
This library analyzes each face and provides statistics for Angular web applications easily.
This Github.

Installation

Install ngx-scanner-face from npm:

npm install ngx-scanner-face@<version> --save

Add wanted package to NgModule imports:

import { NgxScannerFaceModule } from 'ngx-scanner-face';
@NgModule({
  imports: [
    NgxScannerFaceModule
  ]
})

Camera 🛠️

<ngx-scanner-face #scanner="scanner" [isAuto]="true"></ngx-scanner-face>

<span>{{scanner.data.value | json}}</span><!-- value -->
<span>{{scanner.data | async | json}}</span><!-- async -->

Image src 🛠️

<ngx-scanner-face #scanner="scanner" [src]="'http://domain.com/picture.png'"></ngx-scanner-face>

<span>{{scanner.data.value | json}}</span><!-- value -->
<span>{{scanner.data | async | json}}</span><!-- async -->

Select files 🛠️

import { NgxScannerFaceService, ScannerFaceConfig, ScannerFaceResult } from 'ngx-scanner-face';

public scannerConfig: ScannerFaceConfig = {};

public scannerResult: ScannerFaceResult[] = [];

constructor(private face: NgxScannerFaceService) {}

public onSelects(files: any) {
  this.face.loadFiles(files, this.scannerConfig).subscribe((res: ScannerFaceResult[]) => {
    this.scannerResult = res;
  });
}

<input #file type="file" (change)="onSelects(file.files)" [multiple]="'multiple'" [accept]="'.jpg, .png'"/>

<div *ngFor="let row of scannerResult">
  <img [src]="row.url" [alt]="row.name"><!-- Need bypassSecurityTrustUrl -->
</div>

API Documentation

Input 🗝️

Field	Description	Type	Default
[src]	image url	string	-
[isAuto]	auto camera	boolean	false
[fps]	frames/ms	number	30
[timeoutDetect]	detect faces/ms	number	1000
[style]	style for canvas and video	Object	null
[videoStyle]	style for video	Object	null
[canvasStyle]	style for canvas	Object	null
[constraints]	setting video	MediaStreamConstraints	{ audio: false, video: true }
[env]	env config		{ perfadd: false }
[draw]	draw config		{ font: 'monospace', lineHeight: 20 }
[human]	user configuration for human, used to fine-tune behavior		{...}
[config]	Config all	BaseConfig	{ src:..., isAuto:..., isLoading:..., fps:..., env:..., draw:..., human:..., style:..., constraints:... }

Output 🗝️

Field	Description	Type	Default
(event)	Data	Result	-

Global variable in component 🗝️

Field	Description	Type	Default
isStart	start status	boolean	false
isPause	pause status	boolean	false
isLoading	loading status	boolean	false
isTorch	flashlight status	boolean	false
data	data	BehaviorSubject	{}
devices	devices	BehaviorSubject<Device[]>	[]
deviceIndexActive	device index	number	0

Global event in component 🗝️

Field	Description	Type	Default
(start)	start camera	AsyncSubject	-
(stop)	stop camera	AsyncSubject	-
(play)	play video	AsyncSubject	-
(pause)	pause video	AsyncSubject	-
(torcher)	toggle on/off flashlight	AsyncSubject	-
(loadImage)	load image from src	AsyncSubject	-
(download)	download image form video	AsyncSubject	-

Global event in service 🗝️

Field	Description	Type	Default
(toBase64)	used for file selection	AsyncSubject	-
(loadFiles)	used for file selection	AsyncSubject	-
(streamToBase64)	used for with camera scanner	AsyncSubject	-
(streamToBlobURL)	used for with camera scanner	AsyncSubject	-

Models 🧲

ScannerFaceConfig

interface ScannerFaceConfig {
  src?: string;
  isAuto?: boolean;
  isLoading?: boolean;
  fps?: number;
  timeoutDetect?: number;
  env?: Partial<Env>;
  draw?: Partial<DrawOptions>;
  human?: Partial<Config>;
  constraints?: MediaStreamConstraints;
}

ScannerFaceResult

interface ScannerFaceResult {
  file?: File;
  name?: string;
  url?: string;
  blob?: any;
  base64?: string;
  result?: Result;
}

Device

interface Device {
  deviceId: string;
  kind: string;
  label: string;
  groupId: string;
}

Env

class Env {
  /** Running in Browser */
  browser: boolean;
  /** Running in NodeJS */
  node: boolean;
  /** Running in WebWorker thread */
  worker: boolean;
  /** Detected platform */
  platform: string;
  /** Detected agent */
  agent: string;
  /** List of supported backends */
  backends: string[];
  /** Has any work been performed so far */
  initial: boolean;
  /** Are image filters supported? */
  filter: boolean | undefined;
  /** TFJS instance details */
  tfjs: {
      version: undefined | string;
  };
  /** Is offscreenCanvas supported? */
  offscreen: undefined | boolean;
  /** Are performance counter instant values or additive */
  perfadd: boolean;
  /** If using tfjs-node get version of underlying tensorflow shared library and if gpu acceleration is enabled */
  tensorflow: {
      version: undefined | string;
      gpu: undefined | boolean;
  };
  /** WASM detected capabilities */
  wasm: {
      supported: undefined | boolean;
      backend: undefined | boolean;
      simd: undefined | boolean;
      multithread: undefined | boolean;
  };
  /** WebGL detected capabilities */
  webgl: {
      supported: undefined | boolean;
      backend: undefined | boolean;
      version: undefined | string;
      renderer: undefined | string;
  };
  /** WebGPU detected capabilities */
  webgpu: {
      supported: undefined | boolean;
      backend: undefined | boolean;
      adapter: undefined | string;
  };
  /** CPU info */
  cpu: {
      model: undefined | string;
      flags: string[];
  };
  /** List of supported kernels for current backend */
  kernels: string[];
  /** MonkeyPatch for Canvas */
  Canvas: undefined;
  /** MonkeyPatch for Image */
  Image: undefined;
  /** MonkeyPatch for ImageData */
  ImageData: undefined;
  constructor();
  /** update backend information */
  updateBackend(): Promise<void>;
  /** update cpu information */
  updateCPU(): void;
}

Config

interface Config {
  /** Backend used for TFJS operations
   * valid build-in backends are:
   * - Browser: `cpu`, `wasm`, `webgl`, `humangl`, `webgpu`
   * - NodeJS: `cpu`, `wasm`, `tensorflow`
   * default: `webgl` for browser and `tensorflow` for nodejs
   */
  backend: '' | 'cpu' | 'wasm' | 'webgl' | 'humangl' | 'tensorflow' | 'webgpu';
  /** Path to *.wasm files if backend is set to `wasm`
   *
   * default: auto-detects to link to CDN `jsdelivr` when running in browser
   */
  wasmPath: string;
  /** Force WASM loader to use platform fetch
   *
   * default: auto-detects to link to CDN `jsdelivr` when running in browser
   */
  wasmPlatformFetch: boolean;
  /** Print debug statements to console
   *
   * default: `true`
   */
  debug: boolean;
  /** Perform model loading and inference concurrently or sequentially
   *
   * default: `true`
   */
  async: boolean;
  /** What to use for `human.warmup()`
   * - warmup pre-initializes all models for faster inference but can take significant time on startup
   * - used by `webgl`, `humangl` and `webgpu` backends
   *
   * default: `full`
   */
  warmup: '' | 'none' | 'face' | 'full' | 'body';
  /** Base model path (typically starting with file://, http:// or https://) for all models
   * - individual modelPath values are relative to this path
   *
   * default: `../models/` for browsers and `file://models/` for nodejs
   */
  modelBasePath: string;
  /** Cache models in IndexDB on first sucessfull load
   * default: true if indexdb is available (browsers), false if its not (nodejs)
   */
  cacheModels: boolean;
  /** Validate kernel ops used in model during model load
   * default: true
   * any errors will be printed on console but will be treated as non-fatal
   */
  validateModels: boolean;
  /** Cache sensitivity
   * - values 0..1 where 0.01 means reset cache if input changed more than 1%
   * - set to 0 to disable caching
   *
   * default: 0.7
   */
  cacheSensitivity: number;
  /** Explicit flags passed to initialize TFJS */
  flags: Record<string, unknown>;
  /** Software Kernels
   * Registers software kernel ops running on CPU when accelerated version of kernel is not found in the current backend
   */
  softwareKernels: boolean;
  /** Perform immediate garbage collection on deallocated tensors instead of caching them */
  deallocate: boolean;
  /** Internal Variable */
  skipAllowed: boolean;
  /** Filter config {@link FilterConfig} */
  filter: Partial<FilterConfig>;
  /** Gesture config {@link GestureConfig} */
  gesture: Partial<GestureConfig>;
  /** Face config {@link FaceConfig} */
  face: Partial<FaceConfig>;
  /** Body config {@link BodyConfig} */
  body: Partial<BodyConfig>;
  /** Hand config {@link HandConfig} */
  hand: Partial<HandConfig>;
  /** Object config {@link ObjectConfig} */
  object: Partial<ObjectConfig>;
  /** Segmentation config {@link SegmentationConfig} */
  segmentation: Partial<SegmentationConfig>;
}

DrawOptions

interface DrawOptions {
  /** draw line color */
  color: string;
  /** alpha value used for lines */
  alpha: number;
  /** label color */
  labelColor: string;
  /** label shadow color */
  shadowColor: string;
  /** label font */
  font: string;
  /** line spacing between labels */
  lineHeight: number;
  /** line width for drawn lines */
  lineWidth: number;
  /** size of drawn points */
  pointSize: number;
  /** draw rounded boxes by n pixels */
  roundRect: number;
  /** should points be drawn? */
  drawPoints: boolean;
  /** should labels be drawn? */
  drawLabels: boolean;
  /** should face attention keypoints be highlighted */
  drawAttention: boolean;
  /** should detected gestures be drawn? */
  drawGestures: boolean;
  /** should draw boxes around detection results? */
  drawBoxes: boolean;
  /** should draw polygons from detection points? */
  drawPolygons: boolean;
  /** should draw gaze arrows? */
  drawGaze: boolean;
  /** should fill polygons? */
  fillPolygons: boolean;
  /** use z-coordinate when available */
  useDepth: boolean;
  /** should lines be curved? */
  useCurves: boolean;
}

Result

interface Result {
  /** {@link FaceResult}: detection & analysis results */
  face: FaceResult[];
  /** {@link BodyResult}: detection & analysis results */
  body: BodyResult[];
  /** {@link HandResult}: detection & analysis results */
  hand: HandResult[];
  /** {@link GestureResult}: detection & analysis results */
  gesture: GestureResult[];
  /** {@link ObjectResult}: detection & analysis results */
  object: ObjectResult[];
  /** global performance object with timing values for each operation */
  performance: Record<string, number>;
  /** optional processed canvas that can be used to draw input on screen */
  canvas?: AnyCanvas | null;
  /** timestamp of detection representing the milliseconds elapsed since the UNIX epoch */
  readonly timestamp: number;
  /** getter property that returns unified persons object  */
  persons: PersonResult[];
  /** Last known error message */
  error: string | null;
  /** ===================== */
  /**  start version 1.1.6  */
  /** ===================== */
  /** Draw frames for detected faces */
  /** In this case the scanner will not drawn frame on the original image */
  /** Need to use service to handle streamToBase64 and streamToBlobURL */
  /** This solves the problem related to perfomance */
  canvas2: HTMLCanvasElement;
  /** using for service with streamToBase64() */
  base64: string;
  /** using for service with streamToBlobURL() */
  blobUrl?: string;
}

Models in Config 🧲

FilterConfig

interface FilterConfig {
  /** are image filters enabled? */
  enabled: boolean;
  /** perform image histogram equalization
   * - equalization is performed on input as a whole and detected face before its passed for further analysis
   */
  equalization: boolean;
  /** resize input width
   * - if both width and height are set to 0, there is no resizing
   * - if just one is set, second one is scaled automatically
   * - if both are set, values are used as-is
   */
  width: number;
  /** resize input height
   * - if both width and height are set to 0, there is no resizing
   * - if just one is set, second one is scaled automatically
   * - if both are set, values are used as-is
   */
  height: number;
  /** return processed canvas imagedata in result */
  return: boolean;
  /** flip input as mirror image */
  flip: boolean;
  /** range: -1 (darken) to 1 (lighten) */
  brightness: number;
  /** range: -1 (reduce contrast) to 1 (increase contrast) */
  contrast: number;
  /** range: 0 (no sharpening) to 1 (maximum sharpening) */
  sharpness: number;
  /** range: 0 (no blur) to N (blur radius in pixels) */
  blur: number;
  /** range: -1 (reduce saturation) to 1 (increase saturation) */
  saturation: number;
  /** range: 0 (no change) to 360 (hue rotation in degrees) */
  hue: number;
  /** image negative */
  negative: boolean;
  /** image sepia colors */
  sepia: boolean;
  /** image vintage colors */
  vintage: boolean;
  /** image kodachrome colors */
  kodachrome: boolean;
  /** image technicolor colors */
  technicolor: boolean;
  /** image polaroid camera effect */
  polaroid: boolean;
  /** range: 0 (no pixelate) to N (number of pixels to pixelate) */
  pixelate: number;
}

GestureConfig

interface GestureConfig {
  /** is gesture detection enabled? */
  enabled: boolean;
}

FaceConfig

interface FaceConfig extends GestureConfig {
  detector: Partial<FaceDetectorConfig>;
  mesh: Partial<FaceMeshConfig>;
  attention: Partial<FaceAttentionConfig>;
  iris: Partial<FaceIrisConfig>;
  description: Partial<FaceDescriptionConfig>;
  emotion: Partial<FaceEmotionConfig>;
  antispoof: Partial<FaceAntiSpoofConfig>;
  liveness: Partial<FaceLivenessConfig>;
  gear: Partial<FaceGearConfig>;
}

BodyConfig

interface BodyConfig extends GenericConfig {
  /** maximum number of detected bodies */
  maxDetected: number;
  /** minimum confidence for a detected body before results are discarded */
  minConfidence: number;
}

HandConfig

interface HandConfig extends GenericConfig {
  /** should hand rotation correction be performed after hand detection? */
  rotation: boolean;
  /** minimum confidence for a detected hand before results are discarded */
  minConfidence: number;
  /** minimum overlap between two detected hands before one is discarded */
  iouThreshold: number;
  /** maximum number of detected hands */
  maxDetected: number;
  /** should hand landmarks be detected or just return detected hand box */
  landmarks: boolean;
  detector: {
      /** path to hand detector model json */
      modelPath?: string;
  };
  skeleton: {
      /** path to hand skeleton model json */
      modelPath?: string;
  };
}

ObjectConfig

interface ObjectConfig extends GenericConfig {
  /** minimum confidence for a detected objects before results are discarded */
  minConfidence: number;
  /** minimum overlap between two detected objects before one is discarded */
  iouThreshold: number;
  /** maximum number of detected objects */
  maxDetected: number;
}

SegmentationConfig

interface SegmentationConfig extends GenericConfig {
  /** blur segmentation output by <number> pixels for more realistic image */
  blur: number;
}

Models in Result 🧲

FaceResult

interface FaceResult {
  /** face id */
  id: number;
  /** overall face score */
  score: number;
  /** detection score */
  boxScore: number;
  /** mesh score */
  faceScore: number;
  /** detected face box */
  box: Box;
  /** detected face box normalized to 0..1 */
  boxRaw: Box;
  /** detected face mesh */
  mesh: Point[];
  /** detected face mesh normalized to 0..1 */
  meshRaw: Point[];
  /** face contours as array of 2d points normalized to 0..1 */
  /** face contours as array of 2d points */
  /** mesh keypoints combined into annotated results */
  annotations: Record<FaceLandmark, Point[]>;
  /** detected age */
  age?: number;
  /** detected gender */
  gender?: Gender;
  /** gender detection score */
  genderScore?: number;
  /** detected emotions */
  emotion?: {
      score: number;
      emotion: Emotion;
  }[];
  /** detected race */
  race?: {
      score: number;
      race: Race;
  }[];
  /** face descriptor */
  embedding?: number[];
  /** face iris distance from camera */
  iris?: number;
  /** face anti-spoofing result confidence */
  real?: number;
  /** face liveness result confidence */
  live?: number;
  /** face rotation details */
  rotation?: {
      angle: {
          roll: number;
          yaw: number;
          pitch: number;
      };
      matrix: [number, number, number, number, number, number, number, number, number];
      gaze: {
          bearing: number;
          strength: number;
      };
  } | null;
  /** detected face as tensor that can be used in further pipelines */
  tensor?: Tensor;
}

BodyResult

interface BodyResult {
  /** body id */
  id: number;
  /** body detection score */
  score: number;
  /** detected body box */
  box: Box;
  /** detected body box normalized to 0..1 */
  boxRaw: Box;
  /** detected body keypoints */
  keypoints: BodyKeypoint[];
  /** detected body keypoints combined into annotated parts */
  annotations: Record<BodyAnnotation, Point[][]>;
}

HandResult

interface HandResult {
  /** hand id */
  id: number;
  /** hand overal score */
  score: number;
  /** hand detection score */
  boxScore: number;
  /** hand skelton score */
  fingerScore: number;
  /** detected hand box */
  box: Box;
  /** detected hand box normalized to 0..1 */
  boxRaw: Box;
  /** detected hand keypoints */
  keypoints: Point[];
  /** detected hand class */
  label: HandType;
  /** detected hand keypoints combined into annotated parts */
  annotations: Record<Finger, Point[]>;
  /** detected hand parts annotated with part gestures */
  landmarks: Record<Finger, {
      curl: FingerCurl;
      direction: FingerDirection;
  }>;
}

GestureResult

type GestureResult = {
  'face': number;
  gesture: FaceGesture;
} | {
  'iris': number;
  gesture: IrisGesture;
} | {
  'body': number;
  gesture: BodyGesture;
} | {
  'hand': number;
  gesture: HandGesture;
};

ObjectResult

interface ObjectResult {
  /** object id */
  id: number;
  /** object detection score */
  score: number;
  /** detected object class id */
  class: number;
  /** detected object class name */
  label: ObjectType;
  /** detected object box */
  box: Box;
  /** detected object box normalized to 0..1 */
  boxRaw: Box;
}

PersonResult

interface PersonResult {
  /** person id */
  id: number;
  /** face result that belongs to this person */
  face: FaceResult;
  /** body result that belongs to this person */
  body: BodyResult | null;
  /** left and right hand results that belong to this person */
  hands: {
      left: HandResult | null;
      right: HandResult | null;
  };
  /** detected gestures specific to this person */
  gestures: GestureResult[];
  /** box that defines the person */
  box: Box;
  /** box that defines the person normalized to 0..1 */
  boxRaw?: Box;
}

Models in FaceConfig 🧲

FaceDetectorConfig

interface FaceDetectorConfig extends GenericConfig {
  /** is face rotation correction performed after detecting face?
   * used to correctly analyze faces under high angles
   */
  rotation: boolean;
  /** maximum number of detected faces */
  maxDetected: number;
  /** minimum confidence for a detected face before results are discarded */
  minConfidence: number;
  /** minimum overlap between two detected faces before one is discarded */
  iouThreshold: number;
  /** should child models perform on masked image of a face */
  mask: boolean;
  /** should face detection return processed and cropped face tensor that can with an external model for addtional processing?
   * if enabled it must be manually deallocated to avoid memory leak */
  return: boolean;
}

FaceMeshConfig

interface FaceMeshConfig extends GenericConfig {
    /** Keep detected faces that cannot be verified using facemesh */
    keepInvalid: boolean;
}

FaceDescriptionConfig

interface FaceDescriptionConfig extends GenericConfig {
    /** minimum confidence for a detected face before results are discarded */
    minConfidence: number;
}

FaceEmotionConfig

interface FaceEmotionConfig extends GenericConfig {
    /** minimum confidence for a detected face before results are discarded */
    minConfidence: number;
}

FaceGearConfig

interface FaceGearConfig extends GenericConfig {
    /** minimum confidence for a detected race before results are discarded */
    minConfidence: number;
}

Support versions

Support versions
Angular 16	1.2.3
Angular 12	1.2.2

Author Information

Author Information
Author	DaiDH
Phone	+84845882882
Country	Vietnam

To make this library more complete, please donate to me if you can!

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MIT License. Copyright (c) 2021 DaiDH