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check in latest build
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‎build/NetInput.d.ts

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import { Dimensions, TMediaElement } from './types';
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import * as tf from '@tensorflow/tfjs-core';
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import { Point } from './Point';
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import { TResolvedNetInput } from './types';
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export declare class NetInput {
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private _canvases;
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constructor(medias: Array<TMediaElement>, dims?: Dimensions);
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private initCanvas(media, dims?);
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readonly canvases: HTMLCanvasElement[];
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readonly width: number;
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readonly height: number;
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readonly dims: Dimensions | null;
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private _inputs;
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private _isManaged;
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private _inputDimensions;
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private _paddings;
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constructor(inputs: tf.Tensor4D | Array<TResolvedNetInput>);
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readonly inputs: tf.Tensor3D[];
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readonly isManaged: boolean;
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readonly batchSize: number;
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readonly inputDimensions: number[][];
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readonly paddings: Point[];
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getInputDimensions(batchIdx: number): number[];
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getInputHeight(batchIdx: number): number;
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getInputWidth(batchIdx: number): number;
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getPaddings(batchIdx: number): Point;
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toBatchTensor(inputSize: number, isCenterInputs?: boolean): tf.Tensor4D;
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/**
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* By setting the isManaged flag, all newly created tensors will be automatically
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* automatically disposed after the batch tensor has been created
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*/
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managed(): this;
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dispose(): void;
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}

‎build/NetInput.js

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‎build/NetInput.js.map

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‎build/allFacesFactory.d.ts

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import * as tf from '@tensorflow/tfjs-core';
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import { FaceDetectionNet } from './faceDetectionNet/FaceDetectionNet';
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import { FaceLandmarkNet } from './faceLandmarkNet/FaceLandmarkNet';
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import { FaceRecognitionNet } from './faceRecognitionNet/FaceRecognitionNet';
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import { FullFaceDescription } from './FullFaceDescription';
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import { NetInput } from './NetInput';
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export declare function allFacesFactory(detectionNet: FaceDetectionNet, landmarkNet: FaceLandmarkNet, recognitionNet: FaceRecognitionNet): (input: string | HTMLCanvasElement | HTMLImageElement | HTMLVideoElement | (string | HTMLCanvasElement | HTMLImageElement | HTMLVideoElement)[] | tf.Tensor<tf.Rank> | NetInput, minConfidence: number) => Promise<FullFaceDescription[]>;
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import { TNetInput } from './types';
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export declare function allFacesFactory(detectionNet: FaceDetectionNet, landmarkNet: FaceLandmarkNet, recognitionNet: FaceRecognitionNet): (input: TNetInput, minConfidence: number) => Promise<FullFaceDescription[]>;

‎build/allFacesFactory.js

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‎build/allFacesFactory.js.map

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‎build/commons/getImageTensor.js

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‎build/commons/getImageTensor.js.map

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‎build/commons/isMediaElement.d.ts

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export declare function isMediaElement(input: any): boolean;

‎build/commons/isMediaElement.js

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