AI Face Detect API

CUTOS Face Recognition Service Features:
- Supports face register, search, unregister, and comparison.

##### Installation


npm install @cutos/ai-face-detect


##### Import Dependencies

``js
import {Face} from '@cutos/ai-face-detect'
`

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##### 1. Automatic Installation (Recommended)

When running npm install, the installation script will automatically download the model files and copy them into the project directory:

`
public/cutos-ai-face-models/
`

No additional action is required from developers. Once installation is complete, the project can be used directly.

##### 2. Manual Installation

If automatic installation fails or manual setup is preferred, follow the steps below:

(1) Locate the downloaded model files in the dependency package directory:

`
/node_modules/@cutos/ai-face-detect/cutos-ai-face-models/
`

(2) Copy this entire directory into the project path public/cutos-ai-face-models/.
The final directory structure should look like this:

`
public/
├── cutos-ai-face-models/ # Model file directory
│ ├── blaze_face_short_range.tflite
│ ├── vision_wasm_internal.js
│ └── vision_wasm_internal.wasm
├── config.json
├── index.html
└── thumbnail.png
`




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Constructor, creates a face recognition service instance

`js
const faceInstance = new Face();
`




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Initialize the face recognition gateway service

`js
faceInstance.init(gwClient);
`


- gwClient： Object, instance of the face recognition gateway service.

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Detect a single face in the camera stream

`js
faceInstance.detectSingleFace(videoElement);
`
- videoElement:

##### Example:

`js
//index.html

...
//main.js
const $cam = document.querySelector('#cam')
const result = faceInstance.detectSingleFace($cam);
console.log(result)
`

- Example return result:

`json
{
"face": "data:image/jpeg;base64,/9j/4AAQSkZJRgABAQAAAQABAA",
"fullFrame": "data:image/jpeg;base64,/9j/4AAQSkZJRgABAQAAAQABAA",
"score": 0.9609517455101013
}
`
- result.face: The detected face image.
- result.fullFrame: The original camera frame (Blob in base64).
- result.score: Confidence score (0--1), recommended above 0.9 to
consider detection successful.




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Register a face image
`js
faceInstance.register(fullFrame)
`
- fullFrame：Base64 formatted image

##### Example:

` js
const id = faceInstance.register('data:image/jpeg;base64,/9jtUgA.../Z);')
console.log(id)
`

- Example return result:

` json
"f956ac67-0dd8-4dc4-ae5b-55f37d99bc6b" //Returns ID after successful registration
`

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Search for a registered face
`js
faceInstance.search(fullFrame)
`
- fullFrame：Base64 formatted image

##### Example:

` js
const result = faceInstance.search('data:image/jpeg;base64,/9jtUgA.../Z);');
console.log(result)
`

- Example return result:

` json
{
"id": "f956ac67-0dd8-4dc4-ae5b-55f37d99bc6b",
"payload": {},
"score": 0.9953916239059821
}
`

- result.id: Matched ID.
- result.score: Matching score.

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Unregister a face ID

` js
faceInstance.unregister(id);
`

##### Example:

` js
const id = faceInstance.unregister("f956ac67-0dd8-4dc4-ae5b-55f37d99bc6b");
console.log(id)
`

- Example return result:

` json
"f956ac67-0dd8-4dc4-ae5b-55f37d99bc6b" //Returns ID after successful unregistration
`

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Compare two faces

` js
faceInstance.compare(image1, image2);
`

- image1: Base64 formatted image of face 1.
- image2: Base64 formatted image of face 2.

##### Example:

` js
const score = faceInstance.compare('data:image/jpeg;base64,/9j/4...', 'data:image/jpeg;base64,/9j/4...');
console.log(score)
`

- Example return result:

` json
0.9973043918609619 //Recommended above 0.9 to consider a successful match
``