/** * @license * Copyright 2021 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. * ============================================================================= */ import * as tflite from '@tensorflow/tfjs-tflite'; import {TaskModelLoader} from '../../task_model'; import {Runtime, Task, TFLiteCustomModelCommonLoadingOption} from '../common'; import {ObjectDetectorTFLite} from './tflite_common'; // The global namespace type. type TFLiteNS = typeof tflite; /** Loading options. */ export interface ODCustomModelTFLiteLoadingOptions extends TFLiteCustomModelCommonLoadingOption, tflite.ObjectDetectorOptions {} /** * Inference options. * * TODO: placeholder for now. */ export interface ODCustomModelTFLiteInferenceOptions {} /** Loader for custom object detection TFLite model. */ export class ObjectDetectionCustomModelTFLiteLoader extends TaskModelLoader< TFLiteNS, ODCustomModelTFLiteLoadingOptions, ODCustomModelTFLite> { readonly metadata = { name: 'Object detection with TFLite models', description: 'An object detector backed by the TFLite Task Library. ' + 'It can work with any models that meet the ' + 'model requirements. Try models from this ' + 'collection.', resourceUrls: { 'TFLite task library': 'https://www.tensorflow.org/lite/' + 'inference_with_metadata/task_library/overview', }, runtime: Runtime.TFLITE, version: '0.0.1-alpha.3', supportedTasks: [Task.OBJECT_DETECTION], }; readonly packageUrls = [[`https://cdn.jsdelivr.net/npm/@tensorflow/tfjs-tflite@${ this.metadata.version}/dist/tf-tflite.min.js`]]; readonly sourceModelGlobalNamespace = 'tflite'; protected async transformSourceModel( sourceModelGlobal: TFLiteNS, loadingOptions?: ODCustomModelTFLiteLoadingOptions): Promise { const tfliteObjectDetector = await sourceModelGlobal.ObjectDetector.create( loadingOptions.model, loadingOptions); return new ODCustomModelTFLite(tfliteObjectDetector); } } /** * A custom TFLite object detection model loaded from a model url or an * `ArrayBuffer` in memory. * * The underlying object detector is built on top of the [TFLite Task * Library](https://www.tensorflow.org/lite/inference_with_metadata/task_library/overview). * As a result, the custom model needs to meet the [metadata * requirements](https://www.tensorflow.org/lite/inference_with_metadata/task_library/object_detector#model_compatibility_requirements). * * Usage: * * ```js * // Load the model from a custom url with other options (optional). * const model = await tfTask.ObjectDetection.CustomModel.TFLite.load({ * model: * 'https://tfhub.dev/tensorflow/lite-model/ssd_mobilenet_v1/1/metadata/2?lite-format=tflite', * }); * * // Run inference on an image. * const img = document.querySelector('img'); * const result = await model.predict(img); * console.log(result.objects); * * // Clean up. * model.cleanUp(); * ``` * * Refer to `tfTask.ObjectDetector` for the `predict` and `cleanUp` method. * * @docextratypes [ * {description: 'Options for `load`', symbol: * 'ODCustomModelTFLiteLoadingOptions'}, * {description: 'Options for `predict`', symbol: * 'ODCustomModelTFLiteInferenceOptions'} * ] * * * @doc {heading: 'Object Detection', subheading: 'Models'} */ export class ODCustomModelTFLite extends ObjectDetectorTFLite {} export const objectDetectorCustomModelTfliteLoader = new ObjectDetectionCustomModelTFLiteLoader();