/**
 * Result interface definition for **Human** library
 *
 * Contains all possible detection results
 */
export interface Result {
    /** Face results
     * Combined results of face detector, face mesh, age, gender, emotion, embedding, iris models
     * Some values may be null if specific model is not enabled
     *
     * Array of individual results with one object per detected face
     * Each result has:
     * - overal detection confidence value
     * - box detection confidence value
     * - mesh detection confidence value
     * - box as array of [x, y, width, height], normalized to image resolution
     * - boxRaw as array of [x, y, width, height], normalized to range 0..1
     * - mesh as array of [x, y, z] points of face mesh, normalized to image resolution
     * - meshRaw as array of [x, y, z] points of face mesh, normalized to range 0..1
     * - annotations as array of annotated face mesh points
     * - age as value
     * - gender as value
     * - genderConfidence as value
     * - emotion as array of possible emotions with their individual scores
     * - iris as distance value
     * - angle as object with values for roll, yaw and pitch angles
     */
    face: Array<{
        confidence: Number;
        boxConfidence: Number;
        faceConfidence: Number;
        box: [Number, Number, Number, Number];
        boxRaw: [Number, Number, Number, Number];
        mesh: Array<[Number, Number, Number]>;
        meshRaw: Array<[Number, Number, Number]>;
        annotations: Array<{
            part: String;
            points: Array<[Number, Number, Number]>[];
        }>;
        age: Number;
        gender: String;
        genderConfidence: Number;
        emotion: Array<{
            score: Number;
            emotion: String;
        }>;
        embedding: Array<Number>;
        iris: Number;
        angle: {
            roll: Number;
            yaw: Number;
            pitch: Number;
        };
    }>;
    /** Body results
     *
     * Array of individual results with one object per detected body
     * Each results has:
     * - body id number
     * - body part name
     * - part position with x,y,z coordinates
     * - body part score value
     * - body part presence value
     */
    body: Array<{
        id: Number;
        part: String;
        position: {
            x: Number;
            y: Number;
            z: Number;
        };
        score: Number;
        presence: Number;
    }>;
    /** Hand results
     *
     * Array of individual results with one object per detected hand
     * Each result has:
     * - confidence as value
     * - box as array of [x, y, width, height], normalized to image resolution
     * - boxRaw as array of [x, y, width, height], normalized to range 0..1
     * - landmarks as array of [x, y, z] points of hand, normalized to image resolution
     * - annotations as array of annotated face landmark points
     */
    hand: Array<{
        confidence: Number;
        box: [Number, Number, Number, Number];
        boxRaw: [Number, Number, Number, Number];
        landmarks: Array<[Number, Number, Number]>;
        annotations: Array<{
            part: String;
            points: Array<[Number, Number, Number]>[];
        }>;
    }>;
    /** Gesture results
     *
     * Array of individual results with one object per detected gesture
     * Each result has:
     * - part where gesture was detected
     * - gesture detected
     */
    gesture: Array<{
        part: String;
        gesture: String;
    }>;
    /** Object results
    *
    * Array of individual results with one object per detected gesture
    * Each result has:
    * - score as value
    * - label as detected class name
    * - center as array of [x, y], normalized to image resolution
    * - centerRaw as array of [x, y], normalized to range 0..1
    * - box as array of [x, y, width, height], normalized to image resolution
    * - boxRaw as array of [x, y, width, height], normalized to range 0..1
    */
    object: Array<{
        score: Number;
        strideSize: Number;
        class: Number;
        label: String;
        center: Number[];
        centerRaw: Number[];
        box: Number[];
        boxRaw: Number[];
    }>;
    performance: {
        any: any;
    };
    canvas: OffscreenCanvas | HTMLCanvasElement;
}