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justadudewhohacksjustadudewhohacks
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load quantized weights for face detection net
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‎dist/face-api.js

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‎dist/face-api.min.js

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‎dist/faceDetectionNet/FaceDetectionNet.d.ts

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import * as tf from '@tensorflow/tfjs-core';
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import { NetInput } from '../NetInput';
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import { TNetInput } from '../types';
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import { FaceDetection } from './FaceDetection';
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export declare class FaceDetectionNet {
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private _params;
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load(weightsOrUrl: Float32Array | string | undefined): Promise<void>;
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extractWeights(weights: Float32Array): void;
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private forwardTensor(imgTensor);
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forward(input: tf.Tensor | NetInput | TNetInput): {
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boxes: tf.Tensor<tf.Rank.R2>[];
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scores: tf.Tensor<tf.Rank.R1>[];
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};
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locateFaces(input: tf.Tensor | NetInput | TNetInput, minConfidence?: number, maxResults?: number): Promise<FaceDetection[]>;
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}

‎dist/faceDetectionNet/FaceDetectionNet.js

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‎dist/faceDetectionNet/FaceDetectionNet.js.map

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‎dist/faceDetectionNet/boxPredictionLayer.d.ts

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import * as tf from '@tensorflow/tfjs-core';
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import { FaceDetectionNet } from './types';
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export declare function boxPredictionLayer(x: tf.Tensor4D, params: FaceDetectionNet.BoxPredictionParams): {
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import { BoxPredictionParams } from './types';
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export declare function boxPredictionLayer(x: tf.Tensor4D, params: BoxPredictionParams): {
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boxPredictionEncoding: tf.Tensor<tf.Rank>;
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classPrediction: tf.Tensor<tf.Rank>;
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};

‎dist/faceDetectionNet/boxPredictionLayer.js.map

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‎dist/faceDetectionNet/extractParams.d.ts

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import { FaceDetectionNet } from './types';
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export declare function extractParams(weights: Float32Array): FaceDetectionNet.NetParams;
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import { NetParams } from './types';
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export declare function extractParams(weights: Float32Array): NetParams;

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