/** Dectector part of face configuration */
export interface FaceDetectorConfig {
    modelPath: string;
    rotation: boolean;
    maxDetected: number;
    skipFrames: number;
    minConfidence: number;
    iouThreshold: number;
    return: boolean;
}
/** Mesh part of face configuration */
export interface FaceMeshConfig {
    enabled: boolean;
    modelPath: string;
}
/** Iris part of face configuration */
export interface FaceIrisConfig {
    enabled: boolean;
    modelPath: string;
}
/** Description or face embedding part of face configuration
 * - also used by age and gender detection
 */
export interface FaceDescriptionConfig {
    enabled: boolean;
    modelPath: string;
    skipFrames: number;
    minConfidence: number;
}
/** Emotion part of face configuration */
export interface FaceEmotionConfig {
    enabled: boolean;
    minConfidence: number;
    skipFrames: number;
    modelPath: string;
}
/** Controlls and configures all face-specific options:
 * - face detection, face mesh detection, age, gender, emotion detection and face description
 *
 * Parameters:
 * - enabled: true/false
 * - modelPath: path for each of face models
 * - minConfidence: threshold for discarding a prediction
 * - iouThreshold: ammount of overlap between two detected objects before one object is removed
 * - maxDetected: maximum number of faces detected in the input, should be set to the minimum number for performance
 * - rotation: use calculated rotated face image or just box with rotation as-is, false means higher performance, but incorrect mesh mapping on higher face angles
 * - return: return extracted face as tensor for futher user processing, in which case user is reponsible for manually disposing the tensor
*/
export interface FaceConfig {
    enabled: boolean;
    detector: Partial<FaceDetectorConfig>;
    mesh: Partial<FaceMeshConfig>;
    iris: Partial<FaceIrisConfig>;
    description: Partial<FaceDescriptionConfig>;
    emotion: Partial<FaceEmotionConfig>;
}
/** Controlls and configures all body detection specific options
 *
 * Parameters:
 * - enabled: true/false
 * - modelPath: body pose model, can be absolute path or relative to modelBasePath
 * - minConfidence: threshold for discarding a prediction
 * - maxDetected: maximum number of people detected in the input, should be set to the minimum number for performance
 *
 * Changing `modelPath` will change module responsible for hand detection and tracking
 * Allowed values are 'posenet.json', 'blazepose.json', 'efficientpose.json', 'movenet-lightning.json', 'movenet-thunder.json', 'movenet-multipose.json'
*/
export interface BodyConfig {
    enabled: boolean;
    modelPath: string;
    maxDetected: number;
    minConfidence: number;
    skipFrames: number;
}
/** Controlls and configures all hand detection specific options
 *
 * Parameters:
 * - enabled: true/false
 * - landmarks: detect hand landmarks or just hand boundary box
 * - modelPath: paths for hand detector and hand skeleton models, can be absolute path or relative to modelBasePath
 * - minConfidence: threshold for discarding a prediction
 * - iouThreshold: ammount of overlap between two detected objects before one object is removed
 * - maxDetected: maximum number of hands detected in the input, should be set to the minimum number for performance
 * - rotation: use best-guess rotated hand image or just box with rotation as-is, false means higher performance, but incorrect finger mapping if hand is inverted
 *
 * Changing `detector.modelPath` will change module responsible for hand detection and tracking
 * Allowed values are `handdetect.json` and `handtrack.json`
*/
export interface HandConfig {
    enabled: boolean;
    rotation: boolean;
    skipFrames: number;
    minConfidence: number;
    iouThreshold: number;
    maxDetected: number;
    landmarks: boolean;
    detector: {
        modelPath?: string;
    };
    skeleton: {
        modelPath?: string;
    };
}
/** Controlls and configures all object detection specific options
 * - enabled: true/false
 * - modelPath: object detection model, can be absolute path or relative to modelBasePath
 * - minConfidence: minimum score that detection must have to return as valid object
 * - iouThreshold: ammount of overlap between two detected objects before one object is removed
 * - maxDetected: maximum number of detections to return
 *
 * Changing `modelPath` will change module responsible for hand detection and tracking
 * Allowed values are `mb3-centernet.json` and `nanodet.json`
*/
export interface ObjectConfig {
    enabled: boolean;
    modelPath: string;
    minConfidence: number;
    iouThreshold: number;
    maxDetected: number;
    skipFrames: number;
}
/** Controlls and configures all body segmentation module
 * removes background from input containing person
 * if segmentation is enabled it will run as preprocessing task before any other model
 * alternatively leave it disabled and use it on-demand using human.segmentation method which can
 * remove background or replace it with user-provided background
 *
 * - enabled: true/false
 * - modelPath: object detection model, can be absolute path or relative to modelBasePath
 * - blur: blur segmentation output by <number> pixels for more realistic image
 *
 * Changing `modelPath` will change module responsible for hand detection and tracking
 * Allowed values are `selfie.json` and `meet.json`

*/
export interface SegmentationConfig {
    enabled: boolean;
    modelPath: string;
    blur: number;
}
/** Run input through image filters before inference
 * - available only in Browser environments
 * - image filters run with near-zero latency as they are executed on the GPU using WebGL
*/
export interface FilterConfig {
    enabled: 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;
}
/** Controlls gesture detection */
export interface GestureConfig {
    enabled: boolean;
}
/**
 * Configuration interface definition for **Human** library
 *
 * Contains all configurable parameters
 * @typedef Config
 *
 * Defaults: [config](https://github.com/vladmandic/human/blob/main/src/config.ts#L292)
 */
export interface Config {
    /** Backend used for TFJS operations
     * Valid build-in backends are:
     * - Browser: `cpu`, `wasm`, `webgl`, `humangl`
     * - NodeJS: `cpu`, `wasm`, `tensorflow`
     *
     * Experimental:
     * - Browser: `webgpu` - requires custom build of `tfjs-backend-webgpu`
     *
     * Defaults: `humangl` for browser and `tensorflow` for nodejs
    */
    backend: '' | 'cpu' | 'wasm' | 'webgl' | 'humangl' | 'tensorflow' | 'webgpu';
    /** Path to *.wasm files if backend is set to `wasm`
     * - if not set, auto-detects to link to CDN `jsdelivr` when running in browser
    */
    wasmPath: string;
    /** Print debug statements to console */
    debug: boolean;
    /** Perform model loading and inference concurrently or sequentially */
    async: boolean;
    /** What to use for `human.warmup()`
     * - warmup pre-initializes all models for faster inference but can take significant time on startup
    */
    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
    */
    modelBasePath: string;
    /** Cache sensitivity
     * - values 0..1 where 0.01 means reset cache if input changed more than 1%
     * - set to 0 to disable caching
    */
    cacheSensitivity: number;
    /** Internal Variable */
    skipFrame: boolean;
    /** Run input through image filters before inference
     * - image filters run with near-zero latency as they are executed on the GPU
     *
     * {@link FilterConfig}
    */
    filter: Partial<FilterConfig>;
    /** {@link GestureConfig} */
    gesture: Partial<GestureConfig>;
    /** {@link FaceConfig} */
    face: Partial<FaceConfig>;
    /** {@link BodyConfig} */
    body: Partial<BodyConfig>;
    /** {@link HandConfig} */
    hand: Partial<HandConfig>;
    /** {@link ObjectConfig} */
    object: Partial<ObjectConfig>;
    /** {@link SegmentationConfig} */
    segmentation: Partial<SegmentationConfig>;
}
/**
 * [See all default Config values...](https://github.com/vladmandic/human/blob/main/src/config.ts#L244)
 *
 */
declare const config: Config;
export { config as defaults };
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