34 lines
1.7 KiB
TypeScript
34 lines
1.7 KiB
TypeScript
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import * as tf from '../../dist/tfjs.esm.js';
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import { Dimensions } from '../classes/Dimensions';
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import { ObjectDetection } from '../classes/ObjectDetection';
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import { NetInput } from '../dom/NetInput';
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import { TNetInput } from '../dom/types';
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import { NeuralNetwork } from '../NeuralNetwork';
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import { TinyYolov2Config } from './config';
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import { ITinyYolov2Options } from './TinyYolov2Options';
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import { DefaultTinyYolov2NetParams, MobilenetParams, TinyYolov2NetParams } from './types';
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export declare class TinyYolov2Base extends NeuralNetwork<TinyYolov2NetParams> {
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static DEFAULT_FILTER_SIZES: number[];
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private _config;
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constructor(config: TinyYolov2Config);
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get config(): TinyYolov2Config;
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get withClassScores(): boolean;
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get boxEncodingSize(): number;
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runTinyYolov2(x: tf.Tensor4D, params: DefaultTinyYolov2NetParams): tf.Tensor4D;
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runMobilenet(x: tf.Tensor4D, params: MobilenetParams): tf.Tensor4D;
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forwardInput(input: NetInput, inputSize: number): tf.Tensor4D;
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forward(input: TNetInput, inputSize: number): Promise<tf.Tensor4D>;
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detect(input: TNetInput, forwardParams?: ITinyYolov2Options): Promise<ObjectDetection[]>;
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protected getDefaultModelName(): string;
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protected extractParamsFromWeigthMap(weightMap: tf.NamedTensorMap): {
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params: TinyYolov2NetParams;
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paramMappings: import("../common/types.js").ParamMapping[];
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};
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protected extractParams(weights: Float32Array): {
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params: TinyYolov2NetParams;
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paramMappings: import("../common/types.js").ParamMapping[];
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};
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protected extractBoxes(outputTensor: tf.Tensor4D, inputBlobDimensions: Dimensions, scoreThreshold?: number): Promise<any>;
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private extractPredictedClass;
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}
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