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@tensorflow-models/coco-ssd

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Object detection model (coco-ssd) in TensorFlow.js

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/** * @license * Copyright 2018 Google LLC. All Rights Reserved. * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. * ============================================================================= */ /** * IOHandlers that pass through the in-memory ModelArtifacts format. */ import { IOHandler, ModelArtifacts, SaveResult, WeightsManifestEntry } from './types'; /** * Creates an IOHandler that loads model artifacts from memory. * * When used in conjunction with `tf.loadModel`, an instance of `tf.Model` * (Keras-style) can be constructed from the loaded artifacts. * * ```js * const model = await tf.loadModel(tf.io.fromMemory( * modelTopology, weightSpecs, weightData)); * ``` * * @param modelTopology a object containing model topology (i.e., parsed from * the JSON format). * @param weightSpecs An array of `WeightsManifestEntry` objects describing the * names, shapes, types, and quantization of the weight data. * @param weightData A single `ArrayBuffer` containing the weight data, * concatenated in the order described by the weightSpecs. * * @returns A passthrough `IOHandler` that simply loads the provided data. */ export declare function fromMemory(modelTopology: {}, weightSpecs?: WeightsManifestEntry[], weightData?: ArrayBuffer): IOHandler; /** * Creates an IOHandler that passes saved model artifacts to a callback. * * ```js * function handleSave(artifacts) { * // ... do something with the artifacts ... * return {modelArtifactsInfo: {...}, ...}; * } * * const saveResult = model.save(tf.io.withSaveHandler(handleSave)); * ``` * * @param saveHandler A function that accepts a `ModelArtifacts` and returns a * `SaveResult`. */ export declare function withSaveHandler(saveHandler: (artifacts: ModelArtifacts) => Promise<SaveResult>): IOHandler;