86 lines
4.8 KiB
TypeScript
86 lines
4.8 KiB
TypeScript
import { AgeGenderNet } from '../ageGenderNet/AgeGenderNet';
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import { AgeAndGenderPrediction } from '../ageGenderNet/types';
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import { FaceDetection } from '../classes/FaceDetection';
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import { FaceLandmarks68 } from '../classes/FaceLandmarks68';
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import { TNetInput } from '../dom';
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import { FaceExpressionNet } from '../faceExpressionNet/FaceExpressionNet';
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import { FaceExpressions } from '../faceExpressionNet/FaceExpressions';
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import { FaceLandmark68Net } from '../faceLandmarkNet/FaceLandmark68Net';
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import { FaceLandmark68TinyNet } from '../faceLandmarkNet/FaceLandmark68TinyNet';
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import { FaceRecognitionNet } from '../faceRecognitionNet/FaceRecognitionNet';
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import { TinyFaceDetector } from '../tinyFaceDetector/TinyFaceDetector';
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import { TinyFaceDetectorOptions } from '../tinyFaceDetector/TinyFaceDetectorOptions';
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import { TinyYolov2 } from '../tinyYolov2';
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export declare const nets: {
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tinyFaceDetector: TinyFaceDetector;
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tinyYolov2: TinyYolov2;
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faceLandmark68Net: FaceLandmark68Net;
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faceLandmark68TinyNet: FaceLandmark68TinyNet;
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faceRecognitionNet: FaceRecognitionNet;
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faceExpressionNet: FaceExpressionNet;
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ageGenderNet: AgeGenderNet;
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};
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/**
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* Attempts to detect all faces in an image using the Tiny Face Detector.
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*
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* @param input The input image.
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* @param options (optional, default: see TinyFaceDetectorOptions constructor for default parameters).
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* @returns Bounding box of each face with score.
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*/
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export declare const tinyFaceDetector: (input: TNetInput, options: TinyFaceDetectorOptions) => Promise<FaceDetection[]>;
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/**
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* Detects the 68 point face landmark positions of the face shown in an image.
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*
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* @param inputs The face image extracted from the bounding box of a face. Can
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* also be an array of input images, which will be batch processed.
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* @returns 68 point face landmarks or array thereof in case of batch input.
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*/
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export declare const detectFaceLandmarks: (input: TNetInput) => Promise<FaceLandmarks68 | FaceLandmarks68[]>;
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/**
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* Detects the 68 point face landmark positions of the face shown in an image
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* using a tinier version of the 68 point face landmark model, which is slightly
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* faster at inference, but also slightly less accurate.
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*
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* @param inputs The face image extracted from the bounding box of a face. Can
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* also be an array of input images, which will be batch processed.
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* @returns 68 point face landmarks or array thereof in case of batch input.
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*/
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export declare const detectFaceLandmarksTiny: (input: TNetInput) => Promise<FaceLandmarks68 | FaceLandmarks68[]>;
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/**
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* Computes a 128 entry vector (face descriptor / face embeddings) from the face shown in an image,
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* which uniquely represents the features of that persons face. The computed face descriptor can
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* be used to measure the similarity between faces, by computing the euclidean distance of two
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* face descriptors.
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*
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* @param inputs The face image extracted from the aligned bounding box of a face. Can
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* also be an array of input images, which will be batch processed.
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* @returns Face descriptor with 128 entries or array thereof in case of batch input.
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*/
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export declare const computeFaceDescriptor: (input: TNetInput) => Promise<Float32Array | Float32Array[]>;
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/**
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* Recognizes the facial expressions from a face image.
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*
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* @param inputs The face image extracted from the bounding box of a face. Can
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* also be an array of input images, which will be batch processed.
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* @returns Facial expressions with corresponding probabilities or array thereof in case of batch input.
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*/
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export declare const recognizeFaceExpressions: (input: TNetInput) => Promise<FaceExpressions | FaceExpressions[]>;
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/**
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* Predicts age and gender from a face image.
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*
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* @param inputs The face image extracted from the bounding box of a face. Can
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* also be an array of input images, which will be batch processed.
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* @returns Predictions with age, gender and gender probability or array thereof in case of batch input.
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*/
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export declare const predictAgeAndGender: (input: TNetInput) => Promise<AgeAndGenderPrediction | AgeAndGenderPrediction[]>;
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export declare const loadTinyFaceDetectorModel: (url: string) => Promise<void>;
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export declare const loadTinyYolov2Model: (url: string) => Promise<void>;
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export declare const loadFaceLandmarkModel: (url: string) => Promise<void>;
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export declare const loadFaceLandmarkTinyModel: (url: string) => Promise<void>;
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export declare const loadFaceRecognitionModel: (url: string) => Promise<void>;
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export declare const loadFaceExpressionModel: (url: string) => Promise<void>;
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export declare const loadAgeGenderModel: (url: string) => Promise<void>;
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export declare const loadFaceDetectionModel: (url: string) => Promise<void>;
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export declare const locateFaces: typeof TinyFaceDetector;
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export declare const detectLandmarks: (input: TNetInput) => Promise<FaceLandmarks68 | FaceLandmarks68[]>;
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