Age SDK Lite

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Age SDK Lite Implementation is an npm package that uses the W3C WebAssembly to perform 1:N fully homomorphically encrypted (FHE) face recognition.

Please update code accordingly because it might cause issue.

• Face biometric capture
• Encrypted face recognition every 200ms
• 1:n biometric match in 60ms constant time
• Human age estimation
• Unlimited users (unlimited gallery size)
• Fair, accurate and unbiased
• Preserves user privacy with neural network cryptography + fully homomorphic encryption (CryptoNets)
• IEEE 2410 Standard for Biometric Privacy, ISO 27001, ISO 9001 compliant
• Exempt from GDPR, CCPA, BIPA, and HIPAA privacy law obligations
• Predicts in 50ms with or without network using local storage

• Verified Identity
• Web Sign-in
• Payments
• Phone Unlock
• Ticketless Access Control
• Account Recovery
• Face CAPTCHA

Sign up on the waitlist on https://private.id to obtain your apiKey.

Installation

npm install @privateid/cryptonets-web-sdk

Copy the necessary dependencies to the public folder of your app

"prestart": "cp -R ./node_modules/@privateid/cryptonets-web-sdk/wasm public/&& cp -R ./node_modules/@privateid/cryptonets-web-sdk/workers public/",
"prebuild": "cp -R ./node_modules/@privateid/cryptonets-web-sdk/wasm public/ && cp -R ./node_modules/@privateid/cryptonets-web-sdk/workers public/"

Add the necessary environment variables on the .env file in the root of your project

SKIP_PREFLIGHT_CHECK=true
REACT_APP_API_URL= 
REACT_APP_API_KEY=
REACT_APP_WASM_MODULE= face_mask | face | voice

Optional environment variable

REACT_APP_API_ORCHESTRATION=
REACT_APP_SET_CACHE= true | false (Used for predict caching)

The first step is to load and initialize the wasm module and clear the content of the local database.

import { loadPrivIdModule, clearDB } from '@privateid/cryptonets-web-sdk';

const isSupported = await loadPrivIdModule();
clearDB();

In case of .env file (evironment variable) does not work for you we have added a support to set the variables on load.

import { loadPrivIdModule } from '@privateid/cryptonets-web-sdk';

const isSupported =await loadPrivIdModule(
  api_url, 
  api_key,
  api_orchestration_url,
  wasm_url,
  wasm_module,
);

The loadPrivIdModule() function returns an object to check if the device is supporting WASM and WebRTC.

{
    support: boolean,
    message: string,
}

The first step is to load and initialize the wasm module.

To open user camera use the openCamera function with element id of the video tag in the DOM

import { openCamera } from '@privateid/cryptonets-web-sdk';

const { devices, faceMode } = await openCamera(element);

it returns list of the available video devices.

To switch to another media device use the switchCamera function with the ID of the device to be used

import { switchCamera } from '@privateid/cryptonets-web-sdk';

switchCamera(deviceID);

for the mobile phone we can select whether it's front or back camera for this we pass 'front' or 'back' to the switch function

import { switchCamera } from '@privateid/cryptonets-web-sdk';

switchCamera('front');

To close user camera use the closeCamera function with element id of the video tag in the DOM.

import { closeCamera } from '@privateid/cryptonets-web-sdk';

closeCamera(element); // Will specifically look for the element id and will close that camera
closeCamera(); // By default will close opened camera using openCamera

Perform an age estimation using predictAge function on all detected faces from image or camera.

import { predictAge } from '@privateid/cryptonets-web-sdk';

await predictAge(null, predictAgeCallback);

The function takes 3 parameters

Callback

Here are sample returned data to callback from predictAge :

{
    "status": "WASM_RESPONSE",
    "returnValue": {
        "error": 0,
        "faces": [
            {
                "status": 0,
                "age": 16.912670135498047,
                "box": {
                    "top_left": {
                        "x": 486,
                        "y": 371
                    },
                    "bottom_right": {
                        "x": 652,
                        "y": 545
                    }
                }
            },
        ]
    }
}