react-native-executorch/lib/module/hooks/computer_vision/useInstanceSegmentation.js

An easy way to run AI models in React Native with ExecuTorch

"use strict";

import { InstanceSegmentationModule } from '../../modules/computer_vision/InstanceSegmentationModule';
import { useModuleFactory } from '../useModuleFactory';

/**
 * React hook for managing an Instance Segmentation model instance.
 * @typeParam C - A {@link InstanceSegmentationModelSources} config specifying which model to load.
 * @param props - Configuration object containing `model` config and optional `preventLoad` flag.
 * @returns An object with model state (`error`, `isReady`, `isGenerating`, `downloadProgress`), a typed `forward` function, `getAvailableInputSizes` helper, and a `runOnFrame` worklet for VisionCamera integration.
 * @example
 * ```ts
 * const { isReady, isGenerating, forward, error, downloadProgress, getAvailableInputSizes, runOnFrame } =
 *   useInstanceSegmentation({
 *     model: {
 *       modelName: 'yolo26n-seg',
 *       modelSource: 'https://huggingface.co/.../yolo26n-seg.pte',
 *     },
 *   });
 *
 * if (!isReady) {
 *   return <Text>Loading: {(downloadProgress * 100).toFixed(0)}%</Text>;
 * }
 *
 * const results = await forward('path/to/image.jpg', {
 *   confidenceThreshold: 0.5,
 *   inputSize: 640,
 * });
 * ```
 * @category Hooks
 */
export const useInstanceSegmentation = ({
  model,
  preventLoad = false
}) => {
  const {
    error,
    isReady,
    isGenerating,
    downloadProgress,
    runForward,
    instance,
    runOnFrame
  } = useModuleFactory({
    factory: (config, onProgress) => InstanceSegmentationModule.fromModelName(config, onProgress),
    config: model,
    deps: [model.modelName, model.modelSource],
    preventLoad
  });
  const forward = (imageSource, options) => runForward(inst => inst.forward(imageSource, options));
  const getAvailableInputSizes = () => instance?.getAvailableInputSizes();
  return {
    error,
    isReady,
    isGenerating,
    downloadProgress,
    forward,
    getAvailableInputSizes,
    runOnFrame
  };
};
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