human/types/result.d.ts

/**
 * 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
     * - tensor as Tensor object which contains detected face
     */
    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;
        rotation: {
            angle: {
                roll: number;
                yaw: number;
                pitch: number;
            };
            matrix: Array<[number, number, number, number, number, number, number, number, number]>;
        };
        tensor: any;
    }>;
    /** 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: part name and number where gesture was detected: face, iris, body, hand
     * - gesture: gesture detected
     */
    gesture: Array<{
        'face': number;
        gesture: string;
    } | {
        'iris': number;
        gesture: string;
    } | {
        'body': number;
        gesture: string;
    } | {
        'hand': number;
        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;
}