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

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

import { useEffect, useState } from 'react';
import { loadTensorflowModel } from './loadTensorflowModel';
/**
 * Load a Tensorflow Lite Model from the given `.tflite` asset into a React State.
 *
 * * 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 state of the Model.
 */
export function useTensorflowModel(source, delegates) {
  const [state, setState] = useState({
    model: undefined,
    state: 'loading'
  });
  useEffect(() => {
    const load = async () => {
      try {
        setState({
          model: undefined,
          state: 'loading'
        });
        const m = await loadTensorflowModel(source, delegates);
        setState({
          model: m,
          state: 'loaded'
        });
        console.log('Model loaded!');
      } catch (e) {
        console.error(`Failed to load Tensorflow Model ${source}!`, e);
        setState({
          model: undefined,
          state: 'error',
          error: e
        });
      }
    };
    load();
    // JSON.stringify compares delegates by value so inline array literals
    // (e.g. ['core-ml', 'default']) don't cause the effect to re-run every render
    // eslint-disable-next-line react-hooks/exhaustive-deps
  }, [source, JSON.stringify(delegates)]);
  return state;
}
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