### Install dependencies and build

Source: https://github.com/vladmandic/face-api/blob/master/README.md

After cloning or installing, run these commands to install all necessary dependencies and then build the project.

```shell
npm install --production=false
npm run build
```

--------------------------------

### Install face-api via npm

Source: https://github.com/vladmandic/face-api/blob/master/README.md

Install the face-api module using npm. This is the recommended approach for most users.

```shell
npm install @vladmandic/face-api
cd node_modules/@vladmandic/face-api
```

--------------------------------

### Install Development Dependencies

Source: https://github.com/vladmandic/face-api/blob/master/README.md

Install development dependencies for the project. Ensure to set production to false.

```shell
npm install --production=false
```

--------------------------------

### Start Test & Dev Web Server

Source: https://github.com/vladmandic/face-api/blob/master/README.md

Start the built-in test and development web server. This command will launch HTTP and HTTPS servers.

```shell
npm run dev
```

--------------------------------

### Node.js Weights Loader Example

Source: https://github.com/vladmandic/face-api/blob/master/typedoc/functions/tf.io.weightsLoaderFactory.html

Example of creating a Node.js weight loader using fs.readFileSync to load weights from disk. It demonstrates how to define a fetch function and use weightsLoaderFactory to create a weight loading function.

```typescript
import * as fs from 'fs'
const fetchWeightsFromDisk = (filePaths: string[]) =>
  filePaths.map(filePath => fs.readFileSync(filePath).buffer)
const loadWeights = tf.io.weightsLoaderFactory(fetchWeightsFromDisk)
const manifest = JSON.parse(
  fs.readFileSync('./my_model-weights_manifest').toString())
const weightMap = await loadWeights(manifest, './')
```

--------------------------------

### Install FaceAPI Package

Source: https://github.com/vladmandic/face-api/blob/master/README.md

Install the FaceAPI package using npm for use with a bundler like webpack, rollup, or esbuild.

```shell
  npm install @vladmandic/face-api 

```

--------------------------------

### Install FaceAPI with TensorFlow.js Node GPU

Source: https://github.com/vladmandic/face-api/blob/master/README.md

Install packages for FaceAPI with the TensorFlow.js Node.js GPU backend. Ensure CUDA libraries are installed and working prior to installation.

```shell
npm install @tensorflow/tfjs-node-gpu
npm install @vladmandic/face-api
```

--------------------------------

### Install FaceAPI with TensorFlow.js Node (CPU)

Source: https://github.com/vladmandic/face-api/blob/master/README.md

Install the necessary packages for using FaceAPI with the TensorFlow.js Node.js CPU backend. This is recommended for standard NodeJS projects.

```shell
npm install @tensorflow/tfjs-node
npm install @vladmandic/face-api
```

--------------------------------

### Install Canvas for NodeJS Graphical Functions

Source: https://github.com/vladmandic/face-api/blob/master/README.md

Install the 'canvas' package to provide graphical functions like HTMLImageElement and HTMLCanvasElement in a NodeJS environment.

```shell
npm install canvas
```

--------------------------------

### Development Server Log Output

Source: https://github.com/vladmandic/face-api/blob/master/README.md

Example log output from the development server, showing version information, environment details, and build toolchain status.

```log
2022-01-14 09:56:19 INFO:  @vladmandic/face-api version 1.6.4
2022-01-14 09:56:19 INFO:  User: vlado Platform: linux Arch: x64 Node: v17.2.0
2022-01-14 09:56:19 INFO:  Application: { name: '@vladmandic/face-api', version: '1.6.4' }
2022-01-14 09:56:19 INFO:  Environment: { profile: 'development', config: '.build.json', package: 'package.json', tsconfig: true, eslintrc: true, git: true }
2022-01-14 09:56:19 INFO:  Toolchain: { build: '0.6.7', esbuild: '0.14.11', typescript: '4.5.4', typedoc: '0.22.10', eslint: '8.6.0' }
2022-01-14 09:56:19 INFO:  Build: { profile: 'development', steps: [ 'serve', 'watch', 'compile' ] }
2022-01-14 09:56:19 STATE: WebServer: { ssl: false, port: 8000, root: '.' }
2022-01-14 09:56:19 STATE: WebServer: { ssl: true, port: 8001, root: '.', sslKey: 'build/cert/https.key', sslCrt: 'build/cert/https.crt' }
2022-01-14 09:56:19 STATE: Watch: { locations: [ 'src/**', 'README.md', 'src/**', 'src/**' ] }
2022-01-14 09:56:19 STATE: Compile: { name: 'tfjs/node/cpu', format: 'cjs', platform: 'node', input: 'src/tfjs/tf-node.ts', output: 'dist/tfjs.esm.js', files: 1, inputBytes: 143, outputBytes: 1276 }
2022-01-14 09:56:19 STATE: Compile: { name: 'faceapi/node/cpu', format: 'cjs', platform: 'node', input: 'src/index.ts', output: 'dist/face-api.node.js', files: 162, inputBytes: 234787, outputBytes: 175203 }
2022-01-14 09:56:19 STATE: Compile: { name: 'tfjs/node/gpu', format: 'cjs', platform: 'node', input: 'src/tfjs/tf-node-gpu.ts', output: 'dist/tfjs.esm.js', files: 1, inputBytes: 147, outputBytes: 1296 }
2022-01-14 09:56:19 STATE: Compile: { name: 'faceapi/node/gpu', format: 'cjs', platform: 'node', input: 'src/index.ts', output: 'dist/face-api.node-gpu.js', files: 162, inputBytes: 234807, outputBytes: 175219 }
2022-01-14 09:56:19 STATE: Compile: { name: 'tfjs/node/wasm', format: 'cjs', platform: 'node', input: 'src/tfjs/tf-node-wasm.ts', output: 'dist/tfjs.esm.js', files: 1, inputBytes: 185, outputBytes: 1367 }
2022-01-14 09:56:19 STATE: Compile: { name: 'faceapi/node/wasm', format: 'cjs', platform: 'node', input: 'src/index.ts', output: 'dist/face-api.node-wasm.js', files: 162, inputBytes: 234878, outputBytes: 175294 }
2022-01-14 09:56:19 STATE: Compile: { name: 'tfjs/browser/tf-version', format: 'esm', platform: 'browser', input: 'src/tfjs/tf-version.ts', output: 'dist/tfjs.version.js', files: 1, inputBytes: 1063, outputBytes: 1662 }
2022-01-14 09:56:19 STATE: Compile: { name: 'tfjs/browser/esm/nobundle', format: 'esm', platform: 'browser', input: 'src/tfjs/tf-browser.ts', output: 'dist/tfjs.esm.js', files: 2, inputBytes: 2172, outputBytes: 811 }
2022-01-14 09:56:19 STATE: Compile: { name: 'faceapi/browser/esm/nobundle', format: 'esm', platform: 'browser', input: 'src/index.ts', output: 'dist/face-api.esm-nobundle.js', files: 162, inputBytes: 234322, outputBytes: 169437 }
2022-01-14 09:56:19 STATE: Compile: { name: 'tfjs/browser/esm/bundle', format: 'esm', platform: 'browser', input: 'src/tfjs/tf-browser.ts', output: 'dist/tfjs.esm.js', files: 11, inputBytes: 2172, outputBytes: 2444105 }
2022-01-14 09:56:20 STATE: Compile: { name: 'faceapi/browser/iife/bundle', format: 'iife', platform: 'browser', input: 'src/index.ts', output: 'dist/face-api.js', files: 162, inputBytes: 2677616, outputBytes: 1252572 }
2022-01-14 09:56:20 STATE: Compile: { name: 'faceapi/browser/esm/bundle', format: 'esm', platform: 'browser', input: 'src/index.ts', output: 'dist/face-api.esm.js', files: 162, inputBytes: 2677616, outputBytes: 2435063 }
2022-01-14 09:56:20 INFO:  Listening...
...
2022-01-14 09:56:46 DATA:  HTTPS: { method: 'GET', ver: '2.0', status: 200, mime: 'text/html', size: 1047, url: '/', remote: '::1' }
2022-01-14 09:56:46 DATA:  HTTPS: { method: 'GET', ver: '2.0', status: 200, mime: 'text/javascript', size: 6919, url: '/index.js', remote: '::1' }
2022-01-14 09:56:46 DATA:  HTTPS: { method: 'GET', ver: '2.0', status: 200, mime: 'text/javascript', size: 2435063, url: '/dist/face-api.esm.js', remote: '::1' }
2022-01-14 09:56:47 DATA:  HTTPS: { method: 'GET', ver: '2.0', status: 200, mime: 'application/octet-stream', size: 4125244, url: '/dist/face-api.esm.js.map', remote: '::1' }
2022-01-14 09:56:47 DATA:  HTTPS: { method: 'GET', ver: '2.0', status: 200, mime: 'application/json', size: 3219, url: '/model/tiny_face_detector_model-weights_manifest.json', remote: '::1' }
```

--------------------------------

### Import FaceAPI with Bundler (Recommended)

Source: https://github.com/vladmandic/face-api/blob/master/README.md

Import FaceAPI using a bundler after installing the package. This is the recommended approach for modern web development.

```javascript
  import * as faceapi from '@vladmandic/face-api';

```

--------------------------------

### range(num, start, step)

Source: https://github.com/vladmandic/face-api/blob/master/typedoc/functions/utils.range.html

Generates an array of numbers starting from 'start', incrementing by 'step', for a total of 'num' elements.

```APIDOC
## Function range

### Description
Generates an array of numbers.

### Signature
`range(num: number, start: number, step: number): number[]`

### Parameters
#### Parameters
- **num** (number) - The total number of elements in the generated array.
- **start** (number) - The starting number of the sequence.
- **step** (number) - The increment between numbers in the sequence.

### Returns
- **number[]** - An array of numbers.
```

--------------------------------

### NodeJS Multiprocessing Demo Log

Source: https://github.com/vladmandic/face-api/blob/master/README.md

This log demonstrates the output of the NodeJS multiprocessing example, showing the initialization of workers, dispatching of image processing tasks, and the results of face detection.

```json
2021-03-14 08:42:03 INFO:  @vladmandic/face-api version 1.0.2
2021-03-14 08:42:03 INFO:  User: vlado Platform: linux Arch: x64 Node: v15.7.0
2021-03-14 08:42:03 INFO:  FaceAPI multi-process test
2021-03-14 08:42:03 STATE:  Main: started worker: 1888019
2021-03-14 08:42:03 STATE:  Main: started worker: 1888025
2021-03-14 08:42:04 STATE:  Worker: PID: 1888025 TensorFlow/JS 3.3.0 FaceAPI 1.0.2 Backend: tensorflow
2021-03-14 08:42:04 STATE:  Worker: PID: 1888019 TensorFlow/JS 3.3.0 FaceAPI 1.0.2 Backend: tensorflow
2021-03-14 08:42:04 STATE:  Main: dispatching to worker: 1888019
2021-03-14 08:42:04 STATE:  Main: dispatching to worker: 1888025
2021-03-14 08:42:04 DATA:  Worker received message: 1888019 { image: 'demo/sample1.jpg' }
2021-03-14 08:42:04 DATA:  Worker received message: 1888025 { image: 'demo/sample2.jpg' }
2021-03-14 08:42:06 DATA:  Main: worker finished: 1888025 detected faces: 3
2021-03-14 08:42:06 STATE:  Main: dispatching to worker: 1888025
2021-03-14 08:42:06 DATA:  Worker received message: 1888025 { image: 'demo/sample3.jpg' }
2021-03-14 08:42:06 DATA:  Main: worker finished: 1888019 detected faces: 3
2021-03-14 08:42:06 STATE:  Main: dispatching to worker: 1888019
2021-03-14 08:42:06 DATA:  Worker received message: 1888019 { image: 'demo/sample4.jpg' }
2021-03-14 08:42:07 DATA:  Main: worker finished: 1888025 detected faces: 3
2021-03-14 08:42:07 STATE:  Main: dispatching to worker: 1888025
2021-03-14 08:42:07 DATA:  Worker received message: 1888025 { image: 'demo/sample5.jpg' }
2021-03-14 08:42:08 DATA:  Main: worker finished: 1888019 detected faces: 4
2021-03-14 08:42:08 STATE:  Main: dispatching to worker: 1888019
2021-03-14 08:42:08 DATA:  Worker received message: 1888019 { image: 'demo/sample6.jpg' }
2021-03-14 08:42:09 DATA:  Main: worker finished: 1888025 detected faces: 5
2021-03-14 08:42:09 STATE:  Main: worker exit: 1888025 0
2021-03-14 08:42:09 DATA:  Main: worker finished: 1888019 detected faces: 4
2021-03-14 08:42:09 INFO:  Processed 15 images in 5944 ms
2021-03-14 08:42:09 STATE:  Main: worker exit: 1888019 0
```

--------------------------------

### SsdMobilenetv1Options Interface and Example

Source: https://github.com/vladmandic/face-api/blob/master/TUTORIAL.md

Defines the interface for SsdMobilenetv1 detection options, including minimum confidence and maximum results, with an example of creating an options object.

```typescript
export interface ISsdMobilenetv1Options {
  // minimum confidence threshold
  // default: 0.5
  minConfidence?: number

  // maximum number of faces to return
  // default: 100
  maxResults?: number
}

// example
const options = new faceapi.SsdMobilenetv1Options({ minConfidence: 0.8 })
```

--------------------------------

### params

Source: https://github.com/vladmandic/face-api/blob/master/typedoc/classes/TinyYolov2.html

Gets the network parameters. Inherited from TinyYolov2Base.

```APIDOC
## params

### Description
Getter for the network parameters.

### Method
`get params(): TNetParams | undefined`

#### Returns
TNetParams | undefined - The network parameters or undefined if not available.
```

--------------------------------

### TinyFaceDetectorOptions Interface and Example

Source: https://github.com/vladmandic/face-api/blob/master/TUTORIAL.md

Defines the interface for TinyFaceDetector options, including input size and score threshold, with an example of creating an options object.

```typescript
export interface ITinyFaceDetectorOptions {
  // size at which image is processed, the smaller the faster,
  // but less precise in detecting smaller faces, must be divisible
  // by 32, common sizes are 128, 160, 224, 320, 416, 512, 608,
  // for face tracking via webcam I would recommend using smaller sizes,
  // e.g. 128, 160, for detecting smaller faces use larger sizes, e.g. 512, 608
  // default: 416
  inputSize?: number

  // minimum confidence threshold
  // default: 0.5
  scoreThreshold?: number
}

// example
const options = new faceapi.TinyFaceDetectorOptions({ inputSize: 320 })
```

--------------------------------

### Saving a Model to an HTTP Server with Default POST Method

Source: https://github.com/vladmandic/face-api/blob/master/typedoc/functions/tf.io.http.html

This example shows a simplified way to save a model to an HTTP server using the default POST method by just providing the URL to model.save.

```typescript
const saveResult = await model.save('http://model-server:5000/upload');
```

--------------------------------

### Loading a Keras-style model from memory

Source: https://github.com/vladmandic/face-api/blob/master/typedoc/functions/tf.io.fromMemorySync.html

This example demonstrates how to load a Keras-style model using `tf.loadLayersModel` with artifacts provided by `tf.io.fromMemory`. Ensure `modelTopology`, `weightSpecs`, and `weightData` are defined in your scope.

```typescript
const model = await tf.loadLayersModel(tf.io.fromMemory(
    modelTopology, weightSpecs, weightData));
```

--------------------------------

### Moving a Model Between Local Storage and IndexedDB

Source: https://github.com/vladmandic/face-api/blob/master/typedoc/functions/tf.io.moveModel.html

This example demonstrates how to move a model from Local Storage to IndexedDB. It first saves a model, lists available models, performs the move operation, lists models again to show the change, and finally removes the moved model from its new location. Ensure models are saved before attempting to move them.

```typescript
const model = tf.sequential();
model.add(tf.layers.dense({
    units: 1,
    inputShape: [10],
    activation: 'sigmoid'
}));
await model.save('localstorage://demo/management/model1');

// Then list existing models.
console.log(JSON.stringify(await tf.io.listModels()));

// Move the model, from Local Storage to IndexedDB.
await tf.io.moveModel(
    'localstorage://demo/management/model1',
    'indexeddb://demo/management/model1');

// List models again.
console.log(JSON.stringify(await tf.io.listModels()));

// Remove the moved model.
await tf.io.removeModel('indexeddb://demo/management/model1');
```

--------------------------------

### Create Tensor from WebGLData

Source: https://github.com/vladmandic/face-api/blob/master/typedoc/functions/tf.tensor-2.html

This example demonstrates creating a tensor directly from WebGL texture data, avoiding CPU/GPU synchronization. It requires setting up a custom WebGL backend and configuring texture parameters.

```typescript
if (tf.findBackend('custom-webgl') == null) {
  const customCanvas = document.createElement('canvas');
  const customBackend = new tf.MathBackendWebGL(customCanvas);
  tf.registerBackend('custom-webgl', () => customBackend);
}
const savedBackend = tf.getBackend();
await tf.setBackend('custom-webgl');
const gl = tf.backend().gpgpu.gl;
const texture = gl.createTexture();
const tex2d = gl.TEXTURE_2D;
const width = 2;
const height = 2;
gl.bindTexture(tex2d, texture);
gl.texParameteri(tex2d, gl.TEXTURE_WRAP_S, gl.CLAMP_TO_EDGE);
gl.texParameteri(tex2d, gl.TEXTURE_WRAP_T, gl.CLAMP_TO_EDGE);
gl.texParameteri(tex2d, gl.TEXTURE_MIN_FILTER, gl.NEAREST);
gl.texParameteri(tex2d, gl.TEXTURE_MAG_FILTER, gl.NEAREST);
gl.texImage2D(
  tex2d, 0, gl.RGBA32F, // internalFormat
  width, height, 0,
  gl.RGBA, // textureFormat
  gl.FLOAT, // textureType
  new Float32Array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15])
);
const logicalShape = [height * width * 2];
const a = tf.tensor({texture, height, width, channels: 'BR'}, logicalShape);
a.print();
const tex = a.dataToGPU();
await tf.setBackend(savedBackend);
```

--------------------------------

### Remove Model Example

Source: https://github.com/vladmandic/face-api/blob/master/typedoc/functions/tf.io.removeModel.html

This snippet demonstrates how to save a model, list existing models, remove a specific model by its URL, and then list the models again to confirm deletion. It uses 'localstorage' as the storage medium.

```typescript
const model = tf.sequential();
model.add(tf.layers.dense({
  units: 1,
  inputShape: [10],
  activation: 'sigmoid'
}));
await model.save('localstorage://demo/management/model1');

// Then list existing models.
console.log(JSON.stringify(await tf.io.listModels()));

// Delete the model.
await tf.io.removeModel('localstorage://demo/management/model1');

// List models again.
console.log(JSON.stringify(await tf.io.listModels()));
```

--------------------------------

### tf.slice 2D Example

Source: https://github.com/vladmandic/face-api/blob/master/typedoc/functions/tf.slice.html

Extracts a 1x2 slice starting from coordinates [1, 0] from a 2D tensor.

```typescript
const x = tf.tensor2d([1, 2, 3, 4], [2, 2]);
x.slice([1, 0], [1, 2]).print();
```

--------------------------------

### tf.slice 1D Example

Source: https://github.com/vladmandic/face-api/blob/master/typedoc/functions/tf.slice.html

Extracts a slice of size 2 starting from index 1 from a 1D tensor.

```typescript
const x = tf.tensor1d([1, 2, 3, 4]);
x.slice([1], [2]).print();
```

--------------------------------

### Prepare Overlay Canvas

Source: https://github.com/vladmandic/face-api/blob/master/TUTORIAL.md

Sets up the overlay canvas to match the input video dimensions for displaying detection results.

```javascript
const displaySize = { width: input.width, height: input.height }
// resize the overlay canvas to the input dimensions
const canvas = document.getElementById('overlay')
faceapi.matchDimensions(canvas, displaySize)
```

--------------------------------

### loadFromDisk Method

Source: https://github.com/vladmandic/face-api/blob/master/typedoc/classes/NeuralNetwork.html

Loads network weights from the local disk.

```APIDOC
## loadFromDisk

### Description
Loads network weights from the local disk.

### Returns
* Promise<void>
```

--------------------------------

### load

Source: https://github.com/vladmandic/face-api/blob/master/typedoc/classes/TinyFaceDetector.html

Loads the network from a given configuration.

```APIDOC
## load

### Description
Loads the network from a given configuration.

### Method
load

### Parameters
None

### Response
None
```

--------------------------------

### SsdMobilenetv1Options Constructor

Source: https://github.com/vladmandic/face-api/blob/master/typedoc/classes/SsdMobilenetv1Options.html

Initializes a new instance of the SsdMobilenetv1Options class. Allows configuration of detection parameters.

```APIDOC
## constructor

### Description
Initializes a new instance of the SsdMobilenetv1Options class.

### Parameters
#### Path Parameters
*   **__namedParameters** (ISsdMobilenetv1Options) - Optional - Configuration options for SsdMobilenetv1.

### Returns
*   **SsdMobilenetv1Options** - A new instance of SsdMobilenetv1Options.
```

--------------------------------

### Install FaceAPI with TensorFlow.js WASM Backend

Source: https://github.com/vladmandic/face-api/blob/master/README.md

Install packages for FaceAPI using the WebAssembly (WASM) backend in NodeJS. This is an alternative when native TensorFlow binaries are not supported.

```shell
npm install @tensorflow/tfjs
npm install @tensorflow/tfjs-backend-wasm
npm install @vladmandic/face-api
```

--------------------------------

### TinyYolov2Options Constructor

Source: https://github.com/vladmandic/face-api/blob/master/typedoc/classes/TinyYolov2Options.html

Initializes a new instance of TinyYolov2Options. It accepts an optional object with configuration options.

```APIDOC
## constructor

### Signature

*   `new TinyYolov2Options(__namedParameters?: ITinyYolov2Options): TinyYolov2Options`

### Parameters

*   `__namedParameters` (ITinyYolov2Options) - Optional. An object containing configuration options for TinyYolov2.

### Returns

*   `TinyYolov2Options` - A new instance of TinyYolov2Options.
```

--------------------------------

### Initialize FaceMatcher with Reference Image Descriptors

Source: https://github.com/vladmandic/face-api/blob/master/TUTORIAL.md

Initializes a FaceMatcher with descriptors detected from a reference image. Ensure that faces are detected and descriptors are extracted from the reference image before creating the matcher.

```javascript
const results = await faceapi
  .detectAllFaces(referenceImage)
  .withFaceLandmarks()
  .withFaceDescriptors()

if (!results.length) {
  return
}

// create FaceMatcher with automatically assigned labels
// from the detection results for the reference image
const faceMatcher = new faceapi.FaceMatcher(results)
```

--------------------------------

### loadFromDisk

Source: https://github.com/vladmandic/face-api/blob/master/typedoc/classes/TinyFaceDetector.html

Loads the network from disk.

```APIDOC
## loadFromDisk

### Description
Loads the network from disk.

### Method
loadFromDisk

### Parameters
None

### Response
None
```

--------------------------------

### AgeGenderNet.params

Source: https://github.com/vladmandic/face-api/blob/master/typedoc/classes/AgeGenderNet.html

Gets the network parameters for the AgeGenderNet.

```APIDOC
## params

### Description
Accessor for the network parameters of the AgeGenderNet. This can be undefined if the network has not been loaded.

### Signature
```typescript
get params(): undefined | TNetParams
```

### Returns
*   undefined | TNetParams - The network parameters or undefined if not loaded.

### Inherited from
*   NeuralNetwork.params
```

--------------------------------

### AgeGenderNet.paramMappings

Source: https://github.com/vladmandic/face-api/blob/master/typedoc/classes/AgeGenderNet.html

Gets the parameter mappings for the AgeGenderNet.

```APIDOC
## paramMappings

### Description
Accessor for the parameter mappings associated with the AgeGenderNet. These mappings define how network parameters are organized and accessed.

### Signature
```typescript
get paramMappings(): ParamMapping[]
```

### Returns
*   ParamMapping[] - An array of parameter mappings.

### Inherited from
*   NeuralNetwork.paramMappings
```

--------------------------------

### Copying Models Between Storage Locations

Source: https://github.com/vladmandic/face-api/blob/master/typedoc/functions/tf.io.copyModel.html

Demonstrates how to create, save, list, copy, and then remove models between Local Storage and IndexedDB. This snippet illustrates copying within a storage medium and between two different storage mediums.

```typescript
const model = tf.sequential();
model.add(tf.layers.dense({
    units: 1,
    inputShape: [10],
    activation: 'sigmoid'
}));
await model.save('localstorage://demo/management/model1');

// Then list existing models.
console.log(JSON.stringify(await tf.io.listModels()));

// Copy the model, from Local Storage to IndexedDB.
await tf.io.copyModel(
    'localstorage://demo/management/model1',
    'indexeddb://demo/management/model1');

// List models again.
console.log(JSON.stringify(await tf.io.listModels()));

// Remove both models.
await tf.io.removeModel('localstorage://demo/management/model1');
await tf.io.removeModel('indexeddb://demo/management/model1');
```

--------------------------------

### DrawFaceLandmarksOptions Constructor

Source: https://github.com/vladmandic/face-api/blob/master/typedoc/classes/draw.DrawFaceLandmarksOptions.html

Initializes a new instance of the DrawFaceLandmarksOptions class with optional configuration.

```APIDOC
## constructor DrawFaceLandmarksOptions

### Description
Initializes a new instance of the DrawFaceLandmarksOptions class.

### Parameters
#### Path Parameters
* None

#### Query Parameters
* None

#### Request Body
* None

### Parameters
* **options** (IDrawFaceLandmarksOptions) - Optional. An object containing configuration options for drawing face landmarks.

### Returns
* **DrawFaceLandmarksOptions** - A new instance of DrawFaceLandmarksOptions.
```

--------------------------------

### LabeledFaceDescriptors.label Accessor

Source: https://github.com/vladmandic/face-api/blob/master/typedoc/classes/LabeledFaceDescriptors.html

Gets the label associated with this instance.

```APIDOC
## get label

### Description
Gets the label associated with this instance.

### Returns
*   string - The label associated with the face descriptors.
```

--------------------------------

### getMediaDimensions

Source: https://github.com/vladmandic/face-api/blob/master/typedoc/index.html

Gets the dimensions (width and height) of a media element.

```APIDOC
## getMediaDimensions

### Description
Gets the dimensions (width and height) of a media element.

### Method
```javascript
getMediaDimensions(media: HTMLImageElement | HTMLVideoElement | HTMLCanvasElement)
```

### Parameters
#### Path Parameters
None

#### Query Parameters
None

#### Request Body
None

### Request Example
```javascript
// Example usage:
const img = new Image();
img.src = 'path/to/image.jpg';
await awaitMediaLoaded(img);
const dimensions = getMediaDimensions(img);
```

### Response
#### Success Response (200)
- **dimensions** (object) - An object containing the width and height of the media element.
  - **width** (number)
  - **height** (number)

#### Response Example
```json
{
  "width": 800,
  "height": 600
}
```
```

--------------------------------

### constructor

Source: https://github.com/vladmandic/face-api/blob/master/typedoc/classes/TinyFaceDetector.html

Initializes a new instance of the TinyFaceDetector class.

```APIDOC
## constructor

### Description
Initializes a new instance of the TinyFaceDetector class.

### Method
constructor

### Parameters
None

### Response
None
```

--------------------------------

### Face-API Build Output

Source: https://github.com/vladmandic/face-api/blob/master/README.md

This output shows the detailed process of the build script, including compilation steps for different targets and environments. It logs information about the application, environment, toolchain, and build steps.

```js
> @vladmandic/face-api@1.7.1 build /home/vlado/dev/face-api
> node build.js

2022-07-25 08:21:05 INFO:  Application: { name: '@vladmandic/face-api', version: '1.7.1' }
2022-07-25 08:21:05 INFO:  Environment: { profile: 'production', config: '.build.json', package: 'package.json', tsconfig: true, eslintrc: true, git: true }
2022-07-25 08:21:05 INFO:  Toolchain: { build: '0.7.7', esbuild: '0.14.50', typescript: '4.7.4', typedoc: '0.23.9', eslint: '8.20.0' }
2022-07-25 08:21:05 INFO:  Build: { profile: 'production', steps: [ 'clean', 'compile', 'typings', 'typedoc', 'lint', 'changelog' ] }
2022-07-25 08:21:05 STATE: Clean: { locations: [ 'dist/*', 'typedoc/*', 'types/lib/src' ] }
2022-07-25 08:21:05 STATE: Compile: { name: 'tfjs/node/cpu', format: 'cjs', platform: 'node', input: 'src/tfjs/tf-node.ts', output: 'dist/tfjs.esm.js', files: 1, inputBytes: 143, outputBytes: 614 }
2022-07-25 08:21:05 STATE: Compile: { name: 'faceapi/node/cpu', format: 'cjs', platform: 'node', input: 'src/index.ts', output: 'dist/face-api.node.js', files: 162, inputBytes: 234137, outputBytes: 85701 }
2022-07-25 08:21:05 STATE: Compile: { name: 'tfjs/node/gpu', format: 'cjs', platform: 'node', input: 'src/tfjs/tf-node-gpu.ts', output: 'dist/tfjs.esm.js', files: 1, inputBytes: 147, outputBytes: 618 }
2022-07-25 08:21:05 STATE: Compile: { name: 'faceapi/node/gpu', format: 'cjs', platform: 'node', input: 'src/index.ts', output: 'dist/face-api.node-gpu.js', files: 162, inputBytes: 234141, outputBytes: 85705 }
2022-07-25 08:21:05 STATE: Compile: { name: 'tfjs/node/wasm', format: 'cjs', platform: 'node', input: 'src/tfjs/tf-node-wasm.ts', output: 'dist/tfjs.esm.js', files: 1, inputBytes: 185, outputBytes: 670 }
2022-07-25 08:21:05 STATE: Compile: { name: 'faceapi/node/wasm', format: 'cjs', platform: 'node', input: 'src/index.ts', output: 'dist/face-api.node-wasm.js', files: 162, inputBytes: 234193, outputBytes: 85755 }
2022-07-25 08:21:05 STATE: Compile: { name: 'tfjs/browser/tf-version', format: 'esm', platform: 'browser', input: 'src/tfjs/tf-version.ts', output: 'dist/tfjs.version.js', files: 1, inputBytes: 1063, outputBytes: 400 }
2022-07-25 08:21:05 STATE: Compile: { name: 'tfjs/browser/esm/nobundle', format: 'esm', platform: 'browser', input: 'src/tfjs/tf-browser.ts', output: 'dist/tfjs.esm.js', files: 2, inputBytes: 910, outputBytes: 527 }
2022-07-25 08:21:05 STATE: Compile: { name: 'faceapi/browser/esm/nobundle', format: 'esm', platform: 'browser', input: 'src/index.ts', output: 'dist/face-api.esm-nobundle.js', files: 162, inputBytes: 234050, outputBytes: 82787 }
2022-07-25 08:21:05 STATE: Compile: { name: 'tfjs/browser/esm/bundle', format: 'esm', platform: 'browser', input: 'src/tfjs/tf-browser.ts', output: 'dist/tfjs.esm.js', files: 11, inputBytes: 910, outputBytes: 1184871 }
2022-07-25 08:21:05 STATE: Compile: { name: 'faceapi/browser/iife/bundle', format: 'iife', platform: 'browser', input: 'src/index.ts', output: 'dist/face-api.js', files: 162, inputBytes: 1418394, outputBytes: 1264631 }
2022-07-25 08:21:05 STATE: Compile: { name: 'faceapi/browser/esm/bundle', format: 'esm', platform: 'browser', input: 'src/index.ts', output: 'dist/face-api.esm.js', files: 162, inputBytes: 1418394, outputBytes: 1264150 }
2022-07-25 08:21:07 STATE: Typings: { input: 'src/index.ts', output: 'types/lib', files: 93 }
2022-07-25 08:21:09 STATE: TypeDoc: { input: 'src/index.ts', output: 'typedoc', objects: 154, generated: true }
2022-07-25 08:21:13 STATE: Lint: { locations: [ 'src/' ], files: 174, errors: 0, warnings: 0 }
2022-07-25 08:21:14 STATE: ChangeLog: { repository: 'https://github.com/vladmandic/face-api', branch: 'master', output: 'CHANGELOG.md' }
2022-07-25 08:21:14 INFO:  Done...
2022-07-25 08:21:14 STATE: Copy: { input: 'types/lib/dist/tfjs.esm.d.ts' }
2022-07-25 08:21:15 STATE: API-Extractor: { succeeeded: true, errors: 0, warnings: 417 }
2022-07-25 08:21:15 INFO:  FaceAPI Build complete...
```

--------------------------------

### TinyFaceDetector.config

Source: https://github.com/vladmandic/face-api/blob/master/typedoc/classes/TinyFaceDetector.html

Gets the configuration object for the TinyFaceDetector, which is inherited from TinyYolov2Base.

```APIDOC
## config

### Description
Gets the configuration object for the TinyFaceDetector.

### Returns
- [TinyYolov2Config](../types/TinyYolov2Config.html): The configuration object.

### Inherited from
TinyYolov2Base.config
```

--------------------------------

### TinyFaceDetector.boxEncodingSize

Source: https://github.com/vladmandic/face-api/blob/master/typedoc/classes/TinyFaceDetector.html

Gets the size of the bounding box encoding for the TinyFaceDetector.

```APIDOC
## boxEncodingSize

### Description
Gets the size of the bounding box encoding for the TinyFaceDetector.

### Returns
- number: The size of the box encoding.

### Inherited from
TinyYolov2Base.boxEncodingSize
```

--------------------------------

### scoreThreshold Accessor

Source: https://github.com/vladmandic/face-api/blob/master/typedoc/classes/TinyYolov2Options.html

Gets the score threshold for filtering detections.

```APIDOC
## scoreThreshold

### Signature

*   `get scoreThreshold(): number`

### Returns

*   `number` - The configured score threshold.
```

--------------------------------

### FaceLandmark68Net Constructor

Source: https://github.com/vladmandic/face-api/blob/master/typedoc/classes/FaceLandmark68Net.html

Initializes a new instance of the FaceLandmark68Net class. Optionally accepts a FaceFeatureExtractor.

```APIDOC
## constructor

### Description
Initializes a new instance of the FaceLandmark68Net class.

### Signature
```typescript
new FaceLandmark68Net(faceFeatureExtractor?: FaceFeatureExtractor)
```

### Parameters
*   **faceFeatureExtractor** (FaceFeatureExtractor) - Optional. An instance of FaceFeatureExtractor.

### Returns
*   [FaceLandmark68Net](FaceLandmark68Net.html)
```

--------------------------------

### NetInput Constructor

Source: https://github.com/vladmandic/face-api/blob/master/typedoc/classes/NetInput.html

Initializes a new instance of the NetInput class. It takes an array of resolved net inputs and an optional boolean to treat them as a batch.

```APIDOC
## constructor NetInput

### Description
Initializes a new instance of the NetInput class.

### Parameters
*   **inputs** (TResolvedNetInput[]) - An array of resolved net inputs.
*   **treatAsBatchInput** (boolean) - Optional. Defaults to false. If true, the inputs are treated as a batch.

### Returns
*   **NetInput** - A new instance of the NetInput class.
```

--------------------------------

### inputSize Accessor

Source: https://github.com/vladmandic/face-api/blob/master/typedoc/classes/TinyYolov2Options.html

Gets the input size for the TinyYOLOv2 model.

```APIDOC
## inputSize

### Signature

*   `get inputSize(): number`

### Returns

*   `number` - The configured input size.
```

--------------------------------

### SsdMobilenetv1Options.minConfidence Accessor

Source: https://github.com/vladmandic/face-api/blob/master/typedoc/classes/SsdMobilenetv1Options.html

Gets the minimum confidence threshold for detections.

```APIDOC
## minConfidence

### Description
Gets the minimum confidence threshold for detections.

### Returns
*   **number** - The minimum confidence threshold.
```

--------------------------------

### AgeGenderNet.faceFeatureExtractor

Source: https://github.com/vladmandic/face-api/blob/master/typedoc/classes/AgeGenderNet.html

Gets the face feature extractor used by the AgeGenderNet.

```APIDOC
## faceFeatureExtractor

### Description
Accessor for the face feature extractor used by the AgeGenderNet.

### Signature
```typescript
get faceFeatureExtractor(): TinyXception
```

### Returns
*   TinyXception - The face feature extractor instance.
```

--------------------------------

### List and Delete Models using tf.io.listModels

Source: https://github.com/vladmandic/face-api/blob/master/typedoc/functions/tf.io.listModels.html

Demonstrates how to create, save, list, and then delete a model using local storage. This snippet shows the lifecycle of managing a model in a web browser environment.

```typescript
const model = tf.sequential();
model.add(tf.layers.dense({
    units: 1,
    inputShape: [10],
    activation: 'sigmoid'
}));
await model.save('localstorage://demo/management/model1');

// Then list existing models.
console.log(JSON.stringify(await tf.io.listModels()));

// Delete the model.
await tf.io.removeModel('localstorage://demo/management/model1');

// List models again.
console.log(JSON.stringify(await tf.io.listModels()));
```

--------------------------------

### SsdMobilenetv1Options.maxResults Accessor

Source: https://github.com/vladmandic/face-api/blob/master/typedoc/classes/SsdMobilenetv1Options.html

Gets the maximum number of results to return from the detection.

```APIDOC
## maxResults

### Description
Gets the maximum number of results to return from the detection.

### Returns
*   **number** - The maximum number of results.
```

--------------------------------

### run Method

Source: https://github.com/vladmandic/face-api/blob/master/typedoc/classes/DetectAllFacesTask.html

Executes the face detection task and returns a promise that resolves with an array of detected faces. This method overrides the base class implementation.

```APIDOC
## run

### Description
Executes the face detection task and returns a promise with the detected faces.

### Returns
Promise<FaceDetection[]> - A promise that resolves with an array of FaceDetection objects.
```

--------------------------------

### LabeledFaceDescriptors.descriptors Accessor

Source: https://github.com/vladmandic/face-api/blob/master/typedoc/classes/LabeledFaceDescriptors.html

Gets the array of face descriptors associated with this instance.

```APIDOC
## get descriptors

### Description
Gets the array of face descriptors associated with this instance.

### Returns
*   Float32Array[] - The array of face descriptors.
```

--------------------------------

### isHTTPScheme

Source: https://github.com/vladmandic/face-api/blob/master/typedoc/functions/tf.io.isHTTPScheme.html

Checks if a URL string starts with 'http://' or 'https://'.

```APIDOC
## isHTTPScheme

### Description

Checks if a given URL uses an HTTP or HTTPS scheme.

### Method

`isHTTPScheme(url: string): boolean`

### Parameters

#### Path Parameters

*   **url** (string) - The URL to check.

### Returns

*   **boolean** - True if the URL starts with 'http://' or 'https://', false otherwise.

### Defined in

`node_modules/.pnpm/@tensorflow+tfjs-core@4.22.0/node_modules/@tensorflow/tfjs-core/dist/io/http.d.ts:57`
```

--------------------------------

### Point Constructor

Source: https://github.com/vladmandic/face-api/blob/master/typedoc/classes/Point.html

Initializes a new Point object with the given x and y coordinates.

```APIDOC
## constructor

### Description
Initializes a new Point object.

### Parameters
*   **x** (number) - The x-coordinate.
*   **y** (number) - The y-coordinate.

### Returns
*   [Point](Point.html)

### Defined in
src/classes/Point.ts:11
```

--------------------------------

### TinyFaceDetector.paramMappings

Source: https://github.com/vladmandic/face-api/blob/master/typedoc/classes/TinyFaceDetector.html

Gets the parameter mappings for the TinyFaceDetector, used for managing model parameters.

```APIDOC
## paramMappings

### Description
Gets the parameter mappings for the TinyFaceDetector, used for managing model parameters.

### Returns
- ParamMapping[]: An array of ParamMapping objects.

### Inherited from
TinyYolov2Base.paramMappings
```

--------------------------------

### FaceMatch Constructor

Source: https://github.com/vladmandic/face-api/blob/master/typedoc/classes/FaceMatch.html

Initializes a new instance of the FaceMatch class.

```APIDOC
## constructor FaceMatch

### Description
Initializes a new instance of the FaceMatch class.

### Parameters
*   **label** (string) - The label associated with the face match.
*   **distance** (number) - The distance or similarity score of the match.

### Returns
*   [FaceMatch](FaceMatch.html) - A new FaceMatch object.
```

--------------------------------

### TinyFaceDetector.anchors

Source: https://github.com/vladmandic/face-api/blob/master/typedoc/classes/TinyFaceDetector.html

Gets the anchor points used by the TinyFaceDetector for bounding box prediction.

```APIDOC
## anchors

### Description
Gets the anchor points used by the TinyFaceDetector for bounding box prediction.

### Returns
- [Point](Point.html)[]: An array of Point objects representing the anchor sizes.
```

--------------------------------

### params Accessor

Source: https://github.com/vladmandic/face-api/blob/master/typedoc/classes/NeuralNetwork.html

Gets the parameters of the neural network. This can be undefined if the network has not been initialized with parameters.

```APIDOC
## params

### Description
Gets the parameters of the neural network.

### Returns
* undefined | [TNetParams](NeuralNetwork.html#constructorneuralnetworktnetparams) - The network parameters or undefined if not yet set.
```

--------------------------------

### Load Options

Source: https://github.com/vladmandic/face-api/blob/master/typedoc/interfaces/tf.io.LoadOptions.html

Configuration options for loading models and weights.

```APIDOC
### `Optional` strict

strict?: boolean

Strict loading model: whether extraneous weights or missing weights should trigger an `Error`.

If `true`, require that the provided weights exactly match those required by the layers. `false` means that both extra weights and missing weights will be silently ignored.

Default: `true`.

### `Optional` weightPathPrefix

weightPathPrefix?: string

Path prefix for weight files, by default this is calculated from the path of the model JSON file.

For instance, if the path to the model JSON file is `http://localhost/foo/model.json`, then the default path prefix will be `http://localhost/foo/`. If a weight file has the path value `group1-shard1of2` in the weight manifest, then the weight file will be loaded from `http://localhost/foo/group1-shard1of2` by default. However, if you provide a `weightPathPrefix` value of `http://localhost/foo/alt-weights`, then the weight file will be loaded from the path `http://localhost/foo/alt-weights/group1-shard1of2` instead.

### `Optional` weightUrlConverter

weightUrlConverter?: (weightFileName: string) => Promise<string>

An async function to convert weight file name to URL. The weight file names are stored in model.json's weightsManifest.paths field. By default we consider weight files are colocated with the model.json file. For example: model.json URL: `https://www.google.com/models/1/model.json` group1-shard1of1.bin url: `https://www.google.com/models/1/group1-shard1of1.bin`

With this func you can convert the weight file name to any URL.
```

--------------------------------

### ComputeFaceDescriptorsTaskBase.run Method

Source: https://github.com/vladmandic/face-api/blob/master/typedoc/classes/ComputeFaceDescriptorsTaskBase.html

Executes the face descriptor computation task. This method is inherited from ComposableTask and should be called to start the task execution.

```APIDOC
## run

### Description
Executes the face descriptor computation task.

### Returns
*   Promise<TReturn> - A promise that resolves with the computed face descriptors.
```