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auto-852devify

Inspired by auto-nounify, an open source tool by 852dev.xyz to anonymize event participants by adding a specific graphic to cover their faces

Installation

  • npm i

Build

  • npm run build

Run development mode

  • npm run dev

JEST unit test

  • npx jest

JEST update snapshot

  • npx jest -u

Settings

  • Image files should be placed in "public" folder
  • Updating the settings file settings/global.ts
  • Setting structure

global.ts Example

{
    "modelsFolder": "/models",
    "enlargeByTypes": [1.2, 2, 1, 1],
    "default": {
        "enlarge": 1.2,
        "mask": {widthAdjust: 1.18, uriL: './left.png', uriR: './right.png', comment: "Width Adjust: noggles width(160), noggles holder(30),due expand 1/5 for better output"},
        "confidence": 0.3,
        "flip": true,
        "showMask":true,
        "showLM":false
    },
   
}
  • modelsFolder: Folder path of faceApi Models. Should be place inside /public
  • enlargeByTypes: Mask resize ratio according the mask types
  • default: All default attributes here
  • default.enlarge: Default mark enlarge size on initial.
  • default.mask: Default mask for initialize
  • default.mask.widthAdjust: Default value is 1. The value for adjusting the size of the mask for example the noggles' handle width is are 0.18 ratio of the whole noggles and which should not count as the width of the mask. Thus the adjust value should be 1.18
  • default.mask.uriL: Uri of the mask if the target face direction is facing Left side.
  • default.mask.uriR: Uri of the mask if the target face direction is facing Right side.
  • default.mask.comment: Comment text for the mask attribute.
  • default.confidence: default confidence of face detection. Recommend range 0.3 - 0.4
  • default.flip: auto flip mask according to face direction
  • default.showMask: Show/Hide mask in the photo
  • default.showLM: Show/Hide lanmark points in the photo
  • maskTypes: Predefined mask calculation types: {"byFaceEyesWidth","byEyesMiddle", "byFaceWidth", "fullFace"}

Frontend Usage

  • Upload the photo in the File input box
  • Click 852devify to process the face detection
  • Change the Left/Right Mask for customization
  • Change the Mask Type for the Predefine Mask area
  • Change Min. Conf. for mininum conference of face detection
  • Change Width Adjust the customize resize ratio for the mask
  • Click Auto-Flip to enable/disable auto flipping of the mask
  • Click Auto-Mask to enable/disable the drawing of the mask
  • Click Show landmarks to enable/disable the face landmarks points for checking

Function Usage

Face Detecction API

import { singlePhotoFaceDetection, multplePhotoFaceDection } from '@/components/methods/faceDetection';

singlePhotoFaceDetection(uri, minConfidence)

  • uri: target photo uri
  • minConfidence: minimum confidence from face detection. Suggest the better min. confidence should be between 3 - 3.5
  • return:
faceapi.WithFaceLandmarks<{detection: faceapi.FaceDetection;}>[]

multplePhotoFaceDection(photoList: string[], minConfidence:number = 0.35)

  • uri: Array of target photo uri
  • minConfidence: minimum confidence from face detection. Suggest the better min. confidence should be between 3 - 3.5
  • return
{
    uri: string; 
    filename: string;
    detections: faceapi.WithFaceLandmarks<{
    detection: faceapi.FaceDetection;
    }>[] | undefined;
}[]

Position calculation API

import { calcuateMaskPosition, getMaskDimension } from '@/components/methods/calculateMaskPosition'

getMaskDimension(mask: HTMLImageElement, widthAdjust: number = 1)

  • Getting mask dimension for calculation use.
  • mask: HTMLImageElement object from mask uri
  • widthAdjust: Width adjust ratio for the mask
  • return
{width, height, widthAdjust}

calcuateMaskPosition(landmarks: faceapi.FaceLandmarks68, maskDimension: MaskDimension)

  • Calculate the mask position on the photo. 4 predefined types are supported.
  • Landmarks from detections
  • maskDimension from getMaskDimension {width, height, widthAdjust}
  • return
[midX , midY, width, height, angle, hscale]

OutputCanvas

import { OutputCanvas } from '@/components/ui/OutputCanvas';
  • Output html canvas of the photo. All canvas draw are based on this canvas.
  • baseImageUri: Target Photo uri
  • maskImageUri: Mask Image uri
  • detections: Detections from singlePhotoFaceDetection / multplePhotoFaceDection
  • showLandmarks: Show landmarks points in the result canvas if set to true, default false
  • showMask: Show mask in the result canvas if set to true, default true
  • photoTitle: Card Head title for the result canvas container
  • maskSize: ratio of resizing the mask width e.g. adjust the mask size to cover the face,
  • maskAdjust: additional ratio of reszing mask e.g. additional adjust for the ratio of noggles holder
  • Return HTMLCanvasElement