react-native-fast-tflite/lib/module/loadTensorflowModel.js

High-performance TensorFlow Lite library for React Native, built with Nitro Modules

import { Image } from 'react-native';
import { NitroModules } from 'react-native-nitro-modules';

// In React Native, `require(..)` returns a number.

const assetLoader = NitroModules.createHybridObject('AssetLoader');
const tfliteModule = NitroModules.createHybridObject('TfliteModule');

/**
 * Load a Tensorflow Lite Model from the given `.tflite` asset.
 *
 * * If you are passing in a `.tflite` model from your app's bundle using `require(..)`, make sure to add `tflite` as an asset extension to `metro.config.js`!
 * * If you are passing in a `{ url: ... }`, make sure the URL points directly to a `.tflite` model. This can either be a web URL (`http://..`/`https://..`), or a local file (`file://..`).
 *
 * @param source The `.tflite` model in form of either a `require(..)` statement or a `{ url: string }`.
 * @param delegates The delegates to use for computations. Uses the standard CPU delegate per default. The `core-ml` or `metal` delegates are GPU-accelerated, but don't work on every model.
 * @returns The loaded Model.
 */
export async function loadTensorflowModel(source, delegates) {
  let uri;
  if (typeof source === 'number') {
    console.log(`Loading Tensorflow Lite Model ${source}`);
    const asset = Image.resolveAssetSource(source);
    uri = asset.uri;
    console.log(`Resolved Model path: ${asset.uri}`);
  } else if (typeof source === 'object' && 'url' in source) {
    uri = source.url;
  } else {
    throw new Error('TFLite: Invalid source passed! Source should be either a React Native require(..) or a `{ url: string }` object!');
  }
  const data = await assetLoader.loadAsset(uri);
  return tfliteModule.createModel(data, delegates);
}
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