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Merge pull request justadudewhohacks#41 from justadudewhohacks/disposable
param mappings for remaining nets + make face detection and recognition nets extend NeuralNetwork
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‎build/Rect.d.ts

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@@ -11,5 +11,6 @@ export declare class Rect implements IRect {
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height: number;
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constructor(x: number, y: number, width: number, height: number);
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toSquare(): Rect;
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pad(padX: number, padY: number): Rect;
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floor(): Rect;
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}

‎build/Rect.js

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‎build/Rect.js.map

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‎build/commons/NeuralNetwork.d.ts

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import * as tf from '@tensorflow/tfjs-core';
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import { ParamMapping } from './types';
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export declare class NeuralNetwork<TNetParams> {
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private _name;
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protected _params: TNetParams | undefined;
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protected _paramMappings: ParamMapping[];
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constructor(_name: string);
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readonly params: TNetParams | undefined;
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readonly paramMappings: ParamMapping[];
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getParamFromPath(paramPath: string): tf.Tensor;
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}[];
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variable(): void;
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freeze(): void;
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dispose(): void;
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dispose(throwOnRedispose?: boolean): void;
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load(weightsOrUrl: Float32Array | string | undefined): Promise<void>;
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extractWeights(weights: Float32Array): void;
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private traversePropertyPath(paramPath);
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protected loadQuantizedParams(_: any): Promise<{
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params: TNetParams;
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paramMappings: ParamMapping[];
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}>;
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protected extractParams(_: any): {
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params: TNetParams;
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paramMappings: ParamMapping[];
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};
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}

‎build/commons/NeuralNetwork.js

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‎build/commons/NeuralNetwork.js.map

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‎build/commons/disposeUnusedWeightTensors.d.ts

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import { ParamMapping } from './types';
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export declare function disposeUnusedWeightTensors(weightMap: any, paramMappings: ParamMapping[]): void;

‎build/commons/disposeUnusedWeightTensors.js

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‎build/commons/disposeUnusedWeightTensors.js.map

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‎build/commons/extractWeightEntryFactory.d.ts

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import { ParamMapping } from './types';
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export declare function extractWeightEntryFactory(weightMap: any, paramMappings: ParamMapping[]): <T>(originalPath: string, paramRank: number, mappedPath?: string | undefined) => T;

‎build/commons/extractWeightEntryFactory.js

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‎build/commons/extractWeightEntryFactory.js.map

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‎build/faceDetectionNet/FaceDetectionNet.d.ts

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import * as tf from '@tensorflow/tfjs-core';
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import { NeuralNetwork } from '../commons/NeuralNetwork';
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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): Promise<void>;
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extractWeights(weights: Float32Array): void;
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import { NetParams } from './types';
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export declare class FaceDetectionNet extends NeuralNetwork<NetParams> {
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constructor();
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forwardInput(input: NetInput): {
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boxes: tf.Tensor<tf.Rank.R2>[];
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scores: tf.Tensor<tf.Rank.R1>[];
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scores: tf.Tensor<tf.Rank.R1>[];
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}>;
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locateFaces(input: TNetInput, minConfidence?: number, maxResults?: number): Promise<FaceDetection[]>;
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protected loadQuantizedParams(uri: string | undefined): Promise<{
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params: NetParams;
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paramMappings: {
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originalPath?: string | undefined;
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paramPath: string;
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}[];
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}>;
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protected extractParams(weights: Float32Array): {
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params: NetParams;
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paramMappings: {
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originalPath?: string | undefined;
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paramPath: string;
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}[];
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};
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}

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