mirror of https://github.com/vladmandic/human
133 lines
4.2 KiB
TypeScript
133 lines
4.2 KiB
TypeScript
/**
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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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/** 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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* Array of individual results with one object per detected face
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* Each result has:
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* - overal detection confidence value
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* - box detection confidence value
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* - mesh detection confidence value
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* - box as array of [x, y, width, height], normalized to image resolution
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* - boxRaw as array of [x, y, width, height], normalized to range 0..1
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* - mesh as array of [x, y, z] points of face mesh, normalized to image resolution
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* - meshRaw as array of [x, y, z] points of face mesh, normalized to range 0..1
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* - annotations as array of annotated face mesh points
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* - age as value
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* - gender as value
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* - genderConfidence as value
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* - emotion as array of possible emotions with their individual scores
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* - iris as distance value
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* - angle as object with values for roll, yaw and pitch angles
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*/
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face: Array<{
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confidence: Number;
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boxConfidence: Number;
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faceConfidence: 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: Array<{
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part: String;
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points: Array<[Number, Number, Number]>[];
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}>;
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age: Number;
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gender: String;
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genderConfidence: 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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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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}>;
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/** Body results
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*
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* Array of individual results with one object per detected body
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* Each results has:
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* - body id number
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* - body part name
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* - part position with x,y,z coordinates
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* - body part score value
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* - body part presence value
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*/
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body: Array<{
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id: Number;
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part: String;
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position: {
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x: Number;
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y: Number;
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z: Number;
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};
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score: Number;
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presence: Number;
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}>;
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/** Hand results
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*
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* Array of individual results with one object per detected hand
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* Each result has:
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* - confidence as value
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* - box as array of [x, y, width, height], normalized to image resolution
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* - boxRaw as array of [x, y, width, height], normalized to range 0..1
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* - landmarks as array of [x, y, z] points of hand, normalized to image resolution
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* - annotations as array of annotated face landmark points
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*/
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hand: Array<{
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confidence: Number;
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box: [Number, Number, Number, Number];
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boxRaw: [Number, Number, Number, Number];
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landmarks: Array<[Number, Number, Number]>;
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annotations: Array<{
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part: String;
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points: Array<[Number, Number, Number]>[];
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}>;
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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 where gesture was detected
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* - gesture detected
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*/
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gesture: Array<{
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part: String;
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gesture: String;
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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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* - score as value
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* - label as detected class name
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* - center as array of [x, y], normalized to image resolution
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* - centerRaw as array of [x, y], normalized to range 0..1
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* - box as array of [x, y, width, height], normalized to image resolution
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* - boxRaw as array of [x, y, width, height], normalized to range 0..1
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*/
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object: Array<{
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score: Number;
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strideSize: Number;
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class: Number;
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label: String;
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center: Number[];
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centerRaw: Number[];
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box: Number[];
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boxRaw: Number[];
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}>;
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performance: {
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any: any;
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};
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canvas: OffscreenCanvas | HTMLCanvasElement;
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}
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