react-native-vision-camera/docs/docs/guides/FRAME_PROCESSORS_CREATE_OVERVIEW.mdx

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---
id: frame-processors-plugins-overview
title: Creating Frame Processor Plugins
sidebar_label: Overview
---
import useBaseUrl from '@docusaurus/useBaseUrl';
import Tabs from '@theme/Tabs';
import TabItem from '@theme/TabItem';
## Overview
Frame Processor Plugins are **native functions** which can be directly called from a JS Frame Processor. (See ["Frame Processors"](frame-processors))
They **receive a frame from the Camera** as an input and can return any kind of output. For example, a `scanQRCodes` function returns an array of detected QR code strings in the frame:
```tsx {4-5}
function App() {
const frameProcessor = useFrameProcessor((frame) => {
'worklet'
const qrCodes = scanQRCodes(frame)
console.log(`QR Codes in Frame: ${qrCodes}`)
}, [])
return (
<Camera frameProcessor={frameProcessor} {...cameraProps} />
)
}
```
To achieve **maximum performance**, the `scanQRCodes` function is written in a native language (e.g. Objective-C), but it will be directly called from the VisionCamera Frame Processor JavaScript-Runtime.
### Types
Similar to a TurboModule, the Frame Processor Plugin Registry API automatically manages type conversion from JS <-> native. They are converted into the most efficient data-structures, as seen here:
| JS Type | Objective-C/Swift Type | Java/Kotlin Type |
|----------------------|-------------------------------|----------------------------|
| `number` | `NSNumber*` (double) | `Double` |
| `boolean` | `NSNumber*` (boolean) | `Boolean` |
| `string` | `NSString*` | `String` |
| `[]` | `NSArray*` | `ReadableNativeArray` |
| `{}` | `NSDictionary*` | `ReadableNativeMap` |
| `undefined` / `null` | `nil` | `null` |
| `(any, any) => void` | [`RCTResponseSenderBlock`][4] | `(Object, Object) -> void` |
| [`Frame`][1] | [`Frame*`][2] | [`ImageProxy`][3] |
### Return values
Return values will automatically be converted to JS values, assuming they are representable in the ["Types" table](#types). So the following Java Frame Processor Plugin:
```java
@Override
public Object callback(ImageProxy image, Object[] params) {
return "cat";
}
```
Returns a `string` in JS:
```js
export function detectObject(frame: Frame): string {
'worklet'
const result = __detectObject(frame)
console.log(result) // <-- "cat"
}
```
You can also manipulate the buffer and return it (or a copy of it) by returning a [`Frame`][2]/[`ImageProxy`][3] instance:
```java
@Override
public Object callback(ImageProxy image, Object[] params) {
ImageProxy resizedImage = new ImageProxy(/* ... */);
return resizedImage;
}
```
Which returns a [`Frame`](https://github.com/mrousavy/react-native-vision-camera/blob/main/src/Frame.ts) in JS:
```js
const frameProcessor = useFrameProcessor((frame) => {
'worklet';
// creates a new `Frame` that's 720x480
const resizedFrame = resize(frame, 720, 480)
// by downscaling the frame, the `detectObjects` function runs faster.
const objects = detectObjects(resizedFrame)
console.log(objects)
}, [])
```
### Parameters
Frame Processors can also accept parameters, following the same type convention as [return values](#return-values):
```ts
const frameProcessor = useFrameProcessor((frame) => {
'worklet'
const codes = scanCodes(frame, ['qr', 'barcode'])
}, [])
```
Or with multiple ("variadic") parameters:
```ts
const frameProcessor = useFrameProcessor((frame) => {
'worklet'
const codes = scanCodes(frame, true, 'hello-world', 42)
}, [])
```
### Exceptions
To let the user know that something went wrong you can use Exceptions:
```java
@Override
public Object callback(ImageProxy image, Object[] params) {
if (params[0] instanceof String) {
// ...
} else {
throw new Exception("First argument has to be a string!");
}
}
```
Which will throw a JS-error:
```ts
const frameProcessor = useFrameProcessor((frame) => {
'worklet'
try {
const codes = scanCodes(frame, true)
} catch (e) {
console.log(`Error: ${e.message}`)
}
}, [])
```
## What's possible?
You can run any native code you want in a Frame Processor Plugin. Just like in the native iOS and Android Camera APIs, you will receive a frame (`CMSampleBuffer` on iOS, `ImageProxy` on Android) which you can use however you want. In other words; **everything is possible**.
## Implementations
### Long-running Frame Processors
If your Frame Processor takes longer than a single frame interval to execute, or runs asynchronously, you can create a **copy of the frame** and dispatch the actual frame processing to a **separate thread**.
For example, a realtime video chat application might use WebRTC to send the frames to the server. I/O operations (networking) are asynchronous, and we don't _need_ to wait for the upload to succeed before pushing the next frame, so we copy the frame and perform the upload on another Thread.
```java
@Override
public Object callback(ImageProxy image, Object[] params) {
String serverURL = (String)params[0];
ImageProxy imageCopy = new ImageProxy(/* ... */);
uploaderQueue.runAsync(() -> {
WebRTC.uploadImage(imageCopy, serverURL);
imageCopy.close();
});
return null;
}
```
### Async Frame Processors with Event Emitters
You might also run some very complex AI algorithms which are not fast enough to smoothly run at **30 FPS** (**33ms**). To not drop any frames you can create a custom "frame queue" which processes the copied frames and calls back into JS via a React event emitter. For this you'll have to create a Native Module that handles the asynchronous native -> JS communication, see ["Sending events to JavaScript" (Android)](https://reactnative.dev/docs/native-modules-android#sending-events-to-javascript) and ["Sending events to JavaScript" (iOS)](https://reactnative.dev/docs/native-modules-ios#sending-events-to-javascript).
This might look like this for the user:
```tsx
function App() {
const frameProcessor = useFrameProcessor((frame) => {
'worklet'
SomeAI.process(frame) // does not block frame processor, runs async
}, [])
useEffect(() => {
SomeAI.addListener((results) => {
// gets called asynchronously, goes through the React Event Emitter system
console.log(`AI results: ${results}`)
})
}, [])
return (
<Camera frameProcessor={frameProcessor} {...cameraProps} />
)
}
```
This way you can handle queueing up the frames yourself and asynchronously call back into JS at some later point in time using event emitters.
### Benchmarking Frame Processor Plugins
Your Frame Processor Plugins have to be fast. VisionCamera automatically detects slow Frame Processors and outputs relevant information in the native console (Xcode: **Debug Area**, Android Studio: **Logcat**):
<div align="center">
<img src={useBaseUrl("img/slow-log.png")} width="80%" />
</div>
<div align="center">
<img src={useBaseUrl("img/slow-log-2.png")} width="80%" />
</div>
<br />
#### 🚀 Create your first Frame Processor Plugin for [iOS](frame-processors-plugins-ios) or [Android](frame-processors-plugins-android)!
[1]: https://github.com/mrousavy/react-native-vision-camera/blob/main/src/Frame.ts
[2]: https://github.com/mrousavy/react-native-vision-camera/blob/main/ios/Frame%20Processor/Frame.h
[3]: https://developer.android.com/reference/androidx/camera/core/ImageProxy
[4]: https://github.com/facebook/react-native/blob/9a43eac7a32a6ba3164a048960101022a92fcd5a/React/Base/RCTBridgeModule.h#L20-L24