react-native-vision-camera/lib/module/frame-processors/runAsync.js

A powerful, high-performance React Native Camera library.

import { WorkletsProxy } from '../dependencies/WorkletsProxy';
import { FrameProcessorsUnavailableError } from './FrameProcessorsUnavailableError';
import { throwErrorOnJS } from './throwErrorOnJS';

/**
 * A synchronized Shared Value to indicate whether the async context is currently executing
 */
let isAsyncContextBusy;
/**
 * Runs the given function on the async context, and sets {@linkcode isAsyncContextBusy} to false after it finished executing.
 */
let runOnAsyncContext;
try {
  const Worklets = WorkletsProxy.Worklets;
  isAsyncContextBusy = Worklets.createSharedValue(false);
  const asyncContext = Worklets.createContext('VisionCamera.async');
  runOnAsyncContext = asyncContext.createRunAsync((frame, func) => {
    'worklet';

    try {
      // Call long-running function
      func();
    } catch (e) {
      // Re-throw error on JS Thread
      throwErrorOnJS(e);
    } finally {
      // Potentially delete Frame if we were the last ref
      const internal = frame;
      internal.decrementRefCount();

      // free up async context again, new calls can be made
      isAsyncContextBusy.value = false;
    }
  });
} catch (e) {
  // react-native-worklets-core is not installed!
  // Just use dummy implementations that will throw when the user tries to use Frame Processors.
  isAsyncContextBusy = {
    value: false
  };
  runOnAsyncContext = () => {
    throw new FrameProcessorsUnavailableError(e);
  };
}

/**
 * Runs the given {@linkcode func} asynchronously on a separate thread,
 * allowing the Frame Processor to continue executing without dropping a Frame.
 *
 * Only one {@linkcode runAsync} call will execute at the same time,
 * so {@linkcode runAsync} is **not parallel**, **but asynchronous**.
 *
 *
 * For example, if your Camera is running at 60 FPS (16ms per frame), and a
 * heavy ML face detection Frame Processor Plugin takes 500ms to execute,
 * you have two options:
 * - Run the plugin normally (synchronously in `useFrameProcessor`)
 * but drop a lot of Frames, as we can only run at 2 FPS (500ms per frame)
 * - Call the plugin inside {@linkcode runAsync} to allow the Camera to still
 * run at 60 FPS, but offload the heavy ML face detection plugin to the
 * asynchronous context, where it will run at 2 FPS.
 *
 * @note {@linkcode runAsync} cannot be used to draw to a Frame in a Skia Frame Processor.
 * @param frame The current Frame of the Frame Processor.
 * @param func The function to execute.
 * @worklet
 * @example
 *
 * ```ts
 * const frameProcessor = useFrameProcessor((frame) => {
 *   'worklet'
 *   console.log('New Frame arrived!')
 *
 *   runAsync(frame, () => {
 *     'worklet'
 *     const faces = detectFaces(frame)
 *     const face = faces[0]
 *     console.log(`Detected a new face: ${face}`)
 *   })
 * })
 * ```
 */
export function runAsync(frame, func) {
  'worklet';

  if (isAsyncContextBusy.value) {
    // async context is currently busy, we cannot schedule new work in time.
    // drop this frame/runAsync call.
    return;
  }

  // Increment ref count by one
  const internal = frame;
  internal.incrementRefCount();
  isAsyncContextBusy.value = true;

  // Call in separate background context
  runOnAsyncContext(frame, func);
}
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