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justadudewhohacksjustadudewhohacks
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build dist
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‎dist/Point.d.ts

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@@ -10,4 +10,7 @@ export declare class Point implements IPoint {
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sub(pt: IPoint): Point;
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mul(pt: IPoint): Point;
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div(pt: IPoint): Point;
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abs(): Point;
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magnitude(): number;
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floor(): Point;
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}

‎dist/Point.js

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‎dist/Point.js.map

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‎dist/alignFace.d.ts

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import { FaceLandmarks } from './faceLandmarkNet/FaceLandmarks';
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import { Rect } from './Rect';
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/**
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* Aligns the face landmarks after face detection from the relative positions of the faces
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* bounding box, or it's current shift. This function should be used to align the face images
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* after face detection has been performed, before they are passed to the face recognition net.
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* This will make the computed face descriptor more accurate.
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*
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* @param detection (optional) The bounding box of the face or the face detection result. If
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* no argument was passed the position of the face landmarks are assumed to be relative to
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* it's current shift.
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* @returns The bounding box of the aligned face.
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*/
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export declare function alignFace(faceLandmarks: FaceLandmarks, detection?: Rect): Rect;

‎dist/alignFace.js

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‎dist/alignFace.js.map

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‎dist/commons/getCenterPoint.d.ts

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import { Point } from '../Point';
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export declare function getCenterPoint(pts: Point[]): Point;

‎dist/commons/getCenterPoint.js

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‎dist/commons/getCenterPoint.js.map

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‎dist/extractFaceTensors.d.ts

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import * as tf from '@tensorflow/tfjs-core';
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import { FaceDetection } from './faceDetectionNet/FaceDetection';
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import { NetInput } from './NetInput';
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import { Rect } from './Rect';
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import { TNetInput } from './types';
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/**
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* Extracts the tensors of the image regions containing the detected faces.
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* Returned tensors have to be disposed manually once you don't need them anymore!
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* Useful if you want to compute the face descriptors for the face
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* images. Using this method is faster then extracting a canvas for each face and
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* Useful if you want to compute the face descriptors for the face images.
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* Using this method is faster then extracting a canvas for each face and
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* converting them to tensors individually.
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*
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* @param input The image that face detection has been performed on.
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* @param detections The face detection results for that image.
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* @param detections The face detection results or face bounding boxes for that image.
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* @returns Tensors of the corresponding image region for each detected face.
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*/
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export declare function extractFaceTensors(image: tf.Tensor | NetInput | TNetInput, detections: FaceDetection[]): tf.Tensor4D[];
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export declare function extractFaceTensors(image: tf.Tensor | NetInput | TNetInput, detections: Array<FaceDetection | Rect>): tf.Tensor4D[];

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