mirror of https://github.com/vladmandic/human
198 lines
6.7 KiB
TypeScript
198 lines
6.7 KiB
TypeScript
/**
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* Type definitions for Human result object
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*/
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import { Tensor } from '../dist/tfjs.esm.js';
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/** Face results
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* Combined results of face detector, face mesh, age, gender, emotion, embedding, iris models
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* Some values may be null if specific model is not enabled
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*
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* Each result has:
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* - id: face id number
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* - score: overal detection confidence score value
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* - boxScore: face box detection confidence score value
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* - faceScore: face keypoints detection confidence score value
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* - box: face bounding box as array of [x, y, width, height], normalized to image resolution
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* - boxRaw: face bounding box as array of [x, y, width, height], normalized to range 0..1
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* - mesh: face keypoints as array of [x, y, z] points of face mesh, normalized to image resolution
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* - meshRaw: face keypoints as array of [x, y, z] points of face mesh, normalized to range 0..1
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* - annotations: annotated face keypoints as array of annotated face mesh points
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* - age: age as value
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* - gender: gender as value
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* - genderScore: gender detection confidence score as value
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* - emotion: emotions as array of possible emotions with their individual scores
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* - embedding: facial descriptor as array of numerical elements
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* - iris: iris distance from current viewpoint as distance value in centimeters for a typical camera
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* field of view of 88 degrees. value should be adjusted manually as needed
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* - rotation: face rotiation that contains both angles and matrix used for 3d transformations
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* - angle: face angle as object with values for roll, yaw and pitch angles
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* - matrix: 3d transofrmation matrix as array of numeric values
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* - gaze: gaze direction as object with values for bearing in radians and relative strength
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* - tensor: face tensor as Tensor object which contains detected face
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*/
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export interface Face {
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id: number;
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score: number;
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boxScore: number;
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faceScore: number;
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box: [number, number, number, number];
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boxRaw: [number, number, number, number];
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mesh: Array<[number, number, number]>;
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meshRaw: Array<[number, number, number]>;
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annotations: Record<string, Array<[number, number, number]>>;
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age?: number;
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gender?: string;
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genderScore?: number;
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emotion?: Array<{
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score: number;
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emotion: string;
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}>;
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embedding?: Array<number>;
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iris?: number;
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rotation?: {
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angle: {
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roll: number;
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yaw: number;
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pitch: number;
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};
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matrix: [number, number, number, number, number, number, number, number, number];
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gaze: {
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bearing: number;
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strength: number;
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};
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};
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image?: typeof Tensor;
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tensor: typeof Tensor;
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}
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/** Body results
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*
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* Each results has:
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* - id: body id number
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* - score: overall detection score
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* - box: bounding box: x, y, width, height normalized to input image resolution
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* - boxRaw: bounding box: x, y, width, height normalized to 0..1
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* - keypoints: array of keypoints
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* - part: body part name
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* - position: body part position with x,y,z coordinates
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* - score: body part score value
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* - presence: body part presence value
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*/
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export interface Body {
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id: number;
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score: number;
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box: [number, number, number, number];
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boxRaw: [number, number, number, number];
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keypoints: Array<{
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part: string;
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position: [number, number, number?];
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positionRaw: [number, number, number?];
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score: number;
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presence?: number;
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}>;
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}
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/** Hand results
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*
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* Each result has:
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* - id: hand id number
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* - score: detection confidence score as value
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* - box: bounding box: x, y, width, height normalized to input image resolution
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* - boxRaw: bounding box: x, y, width, height normalized to 0..1
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* - landmarks: landmarks as array of [x, y, z] points of hand, normalized to image resolution
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* - annotations: annotated landmarks for each hand part
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*/
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export interface Hand {
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id: number;
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score: number;
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box: [number, number, number, number];
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boxRaw: [number, number, number, number];
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keypoints: Array<[number, number, number]>;
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annotations: Record<string, Array<[number, number, number]>>;
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}
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/** Object results
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*
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* Array of individual results with one object per detected gesture
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* Each result has:
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* - id: object id number
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* - score as value
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* - label as detected class name
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* - box: bounding box: x, y, width, height normalized to input image resolution
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* - boxRaw: bounding box: x, y, width, height normalized to 0..1
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* - center: optional center point as array of [x, y], normalized to image resolution
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* - centerRaw: optional center point as array of [x, y], normalized to range 0..1
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*/
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export interface Item {
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id: number;
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score: number;
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class: number;
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label: string;
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box: [number, number, number, number];
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boxRaw: [number, number, number, number];
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}
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/** Gesture results
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*
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* Array of individual results with one object per detected gesture
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* Each result has:
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* - part: part name and number where gesture was detected: face, iris, body, hand
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* - gesture: gesture detected
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*/
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export declare type Gesture = {
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'face': number;
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gesture: string;
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} | {
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'iris': number;
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gesture: string;
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} | {
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'body': number;
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gesture: string;
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} | {
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'hand': number;
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gesture: string;
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};
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/** Person getter
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*
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* Each result has:
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* - id: person id
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* - face: face object
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* - body: body object
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* - hands: array of hand objects
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* - gestures: array of gestures
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* - box: bounding box: x, y, width, height normalized to input image resolution
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* - boxRaw: bounding box: x, y, width, height normalized to 0..1
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*/
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export interface Person {
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id: number;
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face: Face;
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body: Body | null;
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hands: {
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left: Hand | null;
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right: Hand | null;
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};
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gestures: Array<Gesture>;
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box: [number, number, number, number];
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boxRaw?: [number, number, number, number];
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}
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/**
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* Result interface definition for **Human** library
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*
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* Contains all possible detection results
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*/
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export interface Result {
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/** {@link Face}: detection & analysis results */
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face: Array<Face>;
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/** {@link Body}: detection & analysis results */
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body: Array<Body>;
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/** {@link Hand}: detection & analysis results */
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hand: Array<Hand>;
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/** {@link Gesture}: detection & analysis results */
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gesture: Array<Gesture>;
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/** {@link Object}: detection & analysis results */
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object: Array<Item>;
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/** global performance object with timing values for each operation */
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performance: Record<string, unknown>;
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/** optional processed canvas that can be used to draw input on screen */
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readonly canvas?: OffscreenCanvas | HTMLCanvasElement;
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/** timestamp of detection representing the milliseconds elapsed since the UNIX epoch */
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readonly timestamp: number;
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/** getter property that returns unified persons object */
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persons: Array<Person>;
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}
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