34 lines
1.5 KiB
TypeScript
34 lines
1.5 KiB
TypeScript
import * as tf from '@tensorflow/tfjs-core';
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import { Dimensions } from '../classes/Dimensions';
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import { TResolvedNetInput } from './types';
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export declare class NetInput {
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private _imageTensors;
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private _canvases;
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private _batchSize;
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private _treatAsBatchInput;
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private _inputDimensions;
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private _inputSize;
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constructor(inputs: Array<TResolvedNetInput>, treatAsBatchInput?: boolean);
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readonly imageTensors: Array<tf.Tensor3D | tf.Tensor4D>;
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readonly canvases: HTMLCanvasElement[];
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readonly isBatchInput: boolean;
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readonly batchSize: number;
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readonly inputDimensions: number[][];
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readonly inputSize: number | undefined;
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readonly reshapedInputDimensions: Dimensions[];
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getInput(batchIdx: number): tf.Tensor3D | tf.Tensor4D | HTMLCanvasElement;
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getInputDimensions(batchIdx: number): number[];
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getInputHeight(batchIdx: number): number;
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getInputWidth(batchIdx: number): number;
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getReshapedInputDimensions(batchIdx: number): Dimensions;
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/**
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* Create a batch tensor from all input canvases and tensors
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* with size [batchSize, inputSize, inputSize, 3].
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*
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* @param inputSize Height and width of the tensor.
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* @param isCenterImage (optional, default: false) If true, add an equal amount of padding on
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* both sides of the minor dimension oof the image.
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* @returns The batch tensor.
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*/
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toBatchTensor(inputSize: number, isCenterInputs?: boolean): tf.Tensor4D;
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}
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