react-native-vision-camera/package/src/FrameProcessorPlugins.ts

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import type { Frame, FrameInternal } from './Frame'
import type { FrameProcessor } from './CameraProps'
import { CameraRuntimeError } from './CameraError'
// only import typescript types
import type TWorklets from 'react-native-worklets-core'
import { CameraModule } from './NativeCameraModule'
import { assertJSIAvailable } from './JSIHelper'
type BasicParameterType = string | number | boolean | undefined
type ParameterType = BasicParameterType | BasicParameterType[] | Record<string, BasicParameterType | undefined>
interface FrameProcessorPlugin {
/**
* Call the native Frame Processor Plugin with the given Frame and options.
* @param frame The Frame from the Frame Processor.
* @param options (optional) Additional options. Options will be converted to a native dictionary
* @returns (optional) A value returned from the native Frame Processor Plugin (or undefined)
*/
call: (frame: Frame, options?: Record<string, ParameterType>) => ParameterType
}
interface TVisionCameraProxy {
setFrameProcessor: (viewTag: number, frameProcessor: FrameProcessor) => void
removeFrameProcessor: (viewTag: number) => void
/**
* Creates a new instance of a native Frame Processor Plugin.
* The Plugin has to be registered on the native side, otherwise this returns `undefined`.
* @param name The name of the Frame Processor Plugin. This has to be the same name as on the native side.
* @param options (optional) Options, as a native dictionary, passed to the constructor/init-function of the native plugin.
* @example
* ```ts
* const plugin = VisionCameraProxy.initFrameProcessorPlugin('scanFaces', { model: 'fast' })
* if (plugin == null) throw new Error("Failed to load scanFaces plugin!")
* ```
*/
initFrameProcessorPlugin: (name: string, options?: Record<string, ParameterType>) => FrameProcessorPlugin | undefined
}
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const errorMessage = 'Frame Processors are not available, react-native-worklets-core is not installed!'
let hasWorklets = false
let isAsyncContextBusy = { value: false }
let runOnAsyncContext = (_frame: Frame, _func: () => void): void => {
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throw new CameraRuntimeError('system/frame-processors-unavailable', errorMessage)
}
try {
assertJSIAvailable()
// eslint-disable-next-line @typescript-eslint/no-var-requires
const { Worklets } = require('react-native-worklets-core') as typeof TWorklets
isAsyncContextBusy = Worklets.createSharedValue(false)
const asyncContext = Worklets.createContext('VisionCamera.async')
runOnAsyncContext = Worklets.createRunInContextFn((frame: Frame, func: () => void) => {
'worklet'
try {
// Call long-running function
func()
} finally {
// Potentially delete Frame if we were the last ref
const internal = frame as FrameInternal
internal.decrementRefCount()
isAsyncContextBusy.value = false
}
}, asyncContext)
hasWorklets = true
} catch (e) {
// Worklets are not installed, so Frame Processors are disabled.
}
let proxy: TVisionCameraProxy = {
initFrameProcessorPlugin: () => {
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throw new CameraRuntimeError('system/frame-processors-unavailable', errorMessage)
},
removeFrameProcessor: () => {
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throw new CameraRuntimeError('system/frame-processors-unavailable', errorMessage)
},
setFrameProcessor: () => {
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throw new CameraRuntimeError('system/frame-processors-unavailable', errorMessage)
},
}
if (hasWorklets) {
// Install native Frame Processor Runtime Manager
const result = CameraModule.installFrameProcessorBindings() as unknown
if (result !== true)
throw new CameraRuntimeError('system/frame-processors-unavailable', 'Failed to install Frame Processor JSI bindings!')
// @ts-expect-error global is untyped, it's a C++ host-object
proxy = global.VisionCameraProxy as TVisionCameraProxy
// eslint-disable-next-line @typescript-eslint/no-unnecessary-condition
if (proxy == null) {
throw new CameraRuntimeError(
'system/frame-processors-unavailable',
'Failed to install VisionCameraProxy. Are Frame Processors properly enabled?',
)
}
}
export const VisionCameraProxy: TVisionCameraProxy = {
initFrameProcessorPlugin: proxy.initFrameProcessorPlugin,
removeFrameProcessor: proxy.removeFrameProcessor,
setFrameProcessor: proxy.setFrameProcessor,
// TODO: Remove this in the next version
// @ts-expect-error
getFrameProcessorPlugin: (name, options) => {
console.warn(
'"getFrameProcessorPlugin" has been renamed to "initFrameProcessorPlugin". This function will be removed in the next release.',
)
return proxy.initFrameProcessorPlugin(name, options)
},
}
declare global {
// eslint-disable-next-line no-var
var __frameProcessorRunAtTargetFpsMap: Record<string, number | undefined> | undefined
}
function getLastFrameProcessorCall(frameProcessorFuncId: string): number {
'worklet'
return global.__frameProcessorRunAtTargetFpsMap?.[frameProcessorFuncId] ?? 0
}
function setLastFrameProcessorCall(frameProcessorFuncId: string, value: number): void {
'worklet'
if (global.__frameProcessorRunAtTargetFpsMap == null) global.__frameProcessorRunAtTargetFpsMap = {}
global.__frameProcessorRunAtTargetFpsMap[frameProcessorFuncId] = value
}
feat: Sync Frame Processors (plus `runAsync` and `runAtTargetFps`) (#1472) Before, Frame Processors ran on a separate Thread. After, Frame Processors run fully synchronous and always at the same FPS as the Camera. Two new functions have been introduced: * `runAtTargetFps(fps: number, func: () => void)`: Runs the given code as often as the given `fps`, effectively throttling it's calls. * `runAsync(frame: Frame, func: () => void)`: Runs the given function on a separate Thread for Frame Processing. A strong reference to the Frame is held as long as the function takes to execute. You can use `runAtTargetFps` to throttle calls to a specific API (e.g. if your Camera is running at 60 FPS, but you only want to run face detection at ~25 FPS, use `runAtTargetFps(25, ...)`.) You can use `runAsync` to run a heavy algorithm asynchronous, so that the Camera is not blocked while your algorithm runs. This is useful if your main sync processor draws something, and your async processor is doing some image analysis on the side. You can also combine both functions. Examples: ```js const frameProcessor = useFrameProcessor((frame) => { 'worklet' console.log("I'm running at 60 FPS!") }, []) ``` ```js const frameProcessor = useFrameProcessor((frame) => { 'worklet' console.log("I'm running at 60 FPS!") runAtTargetFps(10, () => { 'worklet' console.log("I'm running at 10 FPS!") }) }, []) ``` ```js const frameProcessor = useFrameProcessor((frame) => { 'worklet' console.log("I'm running at 60 FPS!") runAsync(frame, () => { 'worklet' console.log("I'm running on another Thread, I can block for longer!") }) }, []) ``` ```js const frameProcessor = useFrameProcessor((frame) => { 'worklet' console.log("I'm running at 60 FPS!") runAtTargetFps(10, () => { 'worklet' runAsync(frame, () => { 'worklet' console.log("I'm running on another Thread at 10 FPS, I can block for longer!") }) }) }, []) ```
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/**
* Runs the given function at the given target FPS rate.
*
* For example, if you want to run a heavy face detection algorithm
* only once per second, you can use `runAtTargetFps(1, ...)` to
* throttle it to 1 FPS.
*
* @param fps The target FPS rate at which the given function should be executed
* @param func The function to execute.
* @returns The result of the function if it was executed, or `undefined` otherwise.
* @example
*
* ```ts
* const frameProcessor = useFrameProcessor((frame) => {
* 'worklet'
* console.log('New Frame')
* runAtTargetFps(5, () => {
feat: Sync Frame Processors (plus `runAsync` and `runAtTargetFps`) (#1472) Before, Frame Processors ran on a separate Thread. After, Frame Processors run fully synchronous and always at the same FPS as the Camera. Two new functions have been introduced: * `runAtTargetFps(fps: number, func: () => void)`: Runs the given code as often as the given `fps`, effectively throttling it's calls. * `runAsync(frame: Frame, func: () => void)`: Runs the given function on a separate Thread for Frame Processing. A strong reference to the Frame is held as long as the function takes to execute. You can use `runAtTargetFps` to throttle calls to a specific API (e.g. if your Camera is running at 60 FPS, but you only want to run face detection at ~25 FPS, use `runAtTargetFps(25, ...)`.) You can use `runAsync` to run a heavy algorithm asynchronous, so that the Camera is not blocked while your algorithm runs. This is useful if your main sync processor draws something, and your async processor is doing some image analysis on the side. You can also combine both functions. Examples: ```js const frameProcessor = useFrameProcessor((frame) => { 'worklet' console.log("I'm running at 60 FPS!") }, []) ``` ```js const frameProcessor = useFrameProcessor((frame) => { 'worklet' console.log("I'm running at 60 FPS!") runAtTargetFps(10, () => { 'worklet' console.log("I'm running at 10 FPS!") }) }, []) ``` ```js const frameProcessor = useFrameProcessor((frame) => { 'worklet' console.log("I'm running at 60 FPS!") runAsync(frame, () => { 'worklet' console.log("I'm running on another Thread, I can block for longer!") }) }, []) ``` ```js const frameProcessor = useFrameProcessor((frame) => { 'worklet' console.log("I'm running at 60 FPS!") runAtTargetFps(10, () => { 'worklet' runAsync(frame, () => { 'worklet' console.log("I'm running on another Thread at 10 FPS, I can block for longer!") }) }) }, []) ```
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* 'worklet'
* const faces = detectFaces(frame)
* console.log(`Detected a new face: ${faces[0]}`)
feat: Sync Frame Processors (plus `runAsync` and `runAtTargetFps`) (#1472) Before, Frame Processors ran on a separate Thread. After, Frame Processors run fully synchronous and always at the same FPS as the Camera. Two new functions have been introduced: * `runAtTargetFps(fps: number, func: () => void)`: Runs the given code as often as the given `fps`, effectively throttling it's calls. * `runAsync(frame: Frame, func: () => void)`: Runs the given function on a separate Thread for Frame Processing. A strong reference to the Frame is held as long as the function takes to execute. You can use `runAtTargetFps` to throttle calls to a specific API (e.g. if your Camera is running at 60 FPS, but you only want to run face detection at ~25 FPS, use `runAtTargetFps(25, ...)`.) You can use `runAsync` to run a heavy algorithm asynchronous, so that the Camera is not blocked while your algorithm runs. This is useful if your main sync processor draws something, and your async processor is doing some image analysis on the side. You can also combine both functions. Examples: ```js const frameProcessor = useFrameProcessor((frame) => { 'worklet' console.log("I'm running at 60 FPS!") }, []) ``` ```js const frameProcessor = useFrameProcessor((frame) => { 'worklet' console.log("I'm running at 60 FPS!") runAtTargetFps(10, () => { 'worklet' console.log("I'm running at 10 FPS!") }) }, []) ``` ```js const frameProcessor = useFrameProcessor((frame) => { 'worklet' console.log("I'm running at 60 FPS!") runAsync(frame, () => { 'worklet' console.log("I'm running on another Thread, I can block for longer!") }) }, []) ``` ```js const frameProcessor = useFrameProcessor((frame) => { 'worklet' console.log("I'm running at 60 FPS!") runAtTargetFps(10, () => { 'worklet' runAsync(frame, () => { 'worklet' console.log("I'm running on another Thread at 10 FPS, I can block for longer!") }) }) }, []) ```
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* })
* })
* ```
*/
export function runAtTargetFps<T>(fps: number, func: () => T): T | undefined {
'worklet'
// @ts-expect-error
// eslint-disable-next-line @typescript-eslint/no-unsafe-assignment
const funcId = func.__workletHash ?? '1'
const targetIntervalMs = 1000 / fps // <-- 60 FPS => 16,6667ms interval
const now = performance.now()
const diffToLastCall = now - getLastFrameProcessorCall(funcId)
feat: Sync Frame Processors (plus `runAsync` and `runAtTargetFps`) (#1472) Before, Frame Processors ran on a separate Thread. After, Frame Processors run fully synchronous and always at the same FPS as the Camera. Two new functions have been introduced: * `runAtTargetFps(fps: number, func: () => void)`: Runs the given code as often as the given `fps`, effectively throttling it's calls. * `runAsync(frame: Frame, func: () => void)`: Runs the given function on a separate Thread for Frame Processing. A strong reference to the Frame is held as long as the function takes to execute. You can use `runAtTargetFps` to throttle calls to a specific API (e.g. if your Camera is running at 60 FPS, but you only want to run face detection at ~25 FPS, use `runAtTargetFps(25, ...)`.) You can use `runAsync` to run a heavy algorithm asynchronous, so that the Camera is not blocked while your algorithm runs. This is useful if your main sync processor draws something, and your async processor is doing some image analysis on the side. You can also combine both functions. Examples: ```js const frameProcessor = useFrameProcessor((frame) => { 'worklet' console.log("I'm running at 60 FPS!") }, []) ``` ```js const frameProcessor = useFrameProcessor((frame) => { 'worklet' console.log("I'm running at 60 FPS!") runAtTargetFps(10, () => { 'worklet' console.log("I'm running at 10 FPS!") }) }, []) ``` ```js const frameProcessor = useFrameProcessor((frame) => { 'worklet' console.log("I'm running at 60 FPS!") runAsync(frame, () => { 'worklet' console.log("I'm running on another Thread, I can block for longer!") }) }, []) ``` ```js const frameProcessor = useFrameProcessor((frame) => { 'worklet' console.log("I'm running at 60 FPS!") runAtTargetFps(10, () => { 'worklet' runAsync(frame, () => { 'worklet' console.log("I'm running on another Thread at 10 FPS, I can block for longer!") }) }) }, []) ```
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if (diffToLastCall >= targetIntervalMs) {
setLastFrameProcessorCall(funcId, now)
feat: Sync Frame Processors (plus `runAsync` and `runAtTargetFps`) (#1472) Before, Frame Processors ran on a separate Thread. After, Frame Processors run fully synchronous and always at the same FPS as the Camera. Two new functions have been introduced: * `runAtTargetFps(fps: number, func: () => void)`: Runs the given code as often as the given `fps`, effectively throttling it's calls. * `runAsync(frame: Frame, func: () => void)`: Runs the given function on a separate Thread for Frame Processing. A strong reference to the Frame is held as long as the function takes to execute. You can use `runAtTargetFps` to throttle calls to a specific API (e.g. if your Camera is running at 60 FPS, but you only want to run face detection at ~25 FPS, use `runAtTargetFps(25, ...)`.) You can use `runAsync` to run a heavy algorithm asynchronous, so that the Camera is not blocked while your algorithm runs. This is useful if your main sync processor draws something, and your async processor is doing some image analysis on the side. You can also combine both functions. Examples: ```js const frameProcessor = useFrameProcessor((frame) => { 'worklet' console.log("I'm running at 60 FPS!") }, []) ``` ```js const frameProcessor = useFrameProcessor((frame) => { 'worklet' console.log("I'm running at 60 FPS!") runAtTargetFps(10, () => { 'worklet' console.log("I'm running at 10 FPS!") }) }, []) ``` ```js const frameProcessor = useFrameProcessor((frame) => { 'worklet' console.log("I'm running at 60 FPS!") runAsync(frame, () => { 'worklet' console.log("I'm running on another Thread, I can block for longer!") }) }, []) ``` ```js const frameProcessor = useFrameProcessor((frame) => { 'worklet' console.log("I'm running at 60 FPS!") runAtTargetFps(10, () => { 'worklet' runAsync(frame, () => { 'worklet' console.log("I'm running on another Thread at 10 FPS, I can block for longer!") }) }) }, []) ```
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// Last Frame Processor call is already so long ago that we want to make a new call
return func()
feat: Sync Frame Processors (plus `runAsync` and `runAtTargetFps`) (#1472) Before, Frame Processors ran on a separate Thread. After, Frame Processors run fully synchronous and always at the same FPS as the Camera. Two new functions have been introduced: * `runAtTargetFps(fps: number, func: () => void)`: Runs the given code as often as the given `fps`, effectively throttling it's calls. * `runAsync(frame: Frame, func: () => void)`: Runs the given function on a separate Thread for Frame Processing. A strong reference to the Frame is held as long as the function takes to execute. You can use `runAtTargetFps` to throttle calls to a specific API (e.g. if your Camera is running at 60 FPS, but you only want to run face detection at ~25 FPS, use `runAtTargetFps(25, ...)`.) You can use `runAsync` to run a heavy algorithm asynchronous, so that the Camera is not blocked while your algorithm runs. This is useful if your main sync processor draws something, and your async processor is doing some image analysis on the side. You can also combine both functions. Examples: ```js const frameProcessor = useFrameProcessor((frame) => { 'worklet' console.log("I'm running at 60 FPS!") }, []) ``` ```js const frameProcessor = useFrameProcessor((frame) => { 'worklet' console.log("I'm running at 60 FPS!") runAtTargetFps(10, () => { 'worklet' console.log("I'm running at 10 FPS!") }) }, []) ``` ```js const frameProcessor = useFrameProcessor((frame) => { 'worklet' console.log("I'm running at 60 FPS!") runAsync(frame, () => { 'worklet' console.log("I'm running on another Thread, I can block for longer!") }) }, []) ``` ```js const frameProcessor = useFrameProcessor((frame) => { 'worklet' console.log("I'm running at 60 FPS!") runAtTargetFps(10, () => { 'worklet' runAsync(frame, () => { 'worklet' console.log("I'm running on another Thread at 10 FPS, I can block for longer!") }) }) }, []) ```
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}
return undefined
feat: Sync Frame Processors (plus `runAsync` and `runAtTargetFps`) (#1472) Before, Frame Processors ran on a separate Thread. After, Frame Processors run fully synchronous and always at the same FPS as the Camera. Two new functions have been introduced: * `runAtTargetFps(fps: number, func: () => void)`: Runs the given code as often as the given `fps`, effectively throttling it's calls. * `runAsync(frame: Frame, func: () => void)`: Runs the given function on a separate Thread for Frame Processing. A strong reference to the Frame is held as long as the function takes to execute. You can use `runAtTargetFps` to throttle calls to a specific API (e.g. if your Camera is running at 60 FPS, but you only want to run face detection at ~25 FPS, use `runAtTargetFps(25, ...)`.) You can use `runAsync` to run a heavy algorithm asynchronous, so that the Camera is not blocked while your algorithm runs. This is useful if your main sync processor draws something, and your async processor is doing some image analysis on the side. You can also combine both functions. Examples: ```js const frameProcessor = useFrameProcessor((frame) => { 'worklet' console.log("I'm running at 60 FPS!") }, []) ``` ```js const frameProcessor = useFrameProcessor((frame) => { 'worklet' console.log("I'm running at 60 FPS!") runAtTargetFps(10, () => { 'worklet' console.log("I'm running at 10 FPS!") }) }, []) ``` ```js const frameProcessor = useFrameProcessor((frame) => { 'worklet' console.log("I'm running at 60 FPS!") runAsync(frame, () => { 'worklet' console.log("I'm running on another Thread, I can block for longer!") }) }, []) ``` ```js const frameProcessor = useFrameProcessor((frame) => { 'worklet' console.log("I'm running at 60 FPS!") runAtTargetFps(10, () => { 'worklet' runAsync(frame, () => { 'worklet' console.log("I'm running on another Thread at 10 FPS, I can block for longer!") }) }) }, []) ```
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}
/**
* Runs the given function asynchronously, while keeping a strong reference to the Frame.
*
* For example, if you want to run a heavy face detection algorithm
* while still drawing to the screen at 60 FPS, you can use `runAsync(...)`
* to offload the face detection algorithm to a separate thread.
*
* @param frame The current Frame of the Frame Processor.
* @param func The function to execute.
* @example
*
* ```ts
* const frameProcessor = useFrameProcessor((frame) => {
* 'worklet'
* console.log('New Frame')
* runAsync(frame, () => {
* 'worklet'
* const faces = detectFaces(frame)
* const face = [faces0]
* console.log(`Detected a new face: ${face}`)
* })
* })
* ```
*/
export function runAsync(frame: Frame, func: () => void): void {
'worklet'
feat: Draw onto `Frame` as if it was a Skia Canvas (#1479) * Create Shaders.ts * Add `previewType` and `enableFpsGraph` * Add RN Skia native dependency * Add Skia Preview View on iOS * Pass 1 * Update FrameHostObject.mm * Wrap Canvas * Lockfiles * fix: Fix stuff * chore: Upgrade RNWorklets * Add `previewType` to set the Preview * feat: Add Example * Update project.pbxproj * `enableFpsGraph` * Cache the `std::shared_ptr<FrameHostObject>` * Update CameraView+RecordVideo.swift * Update SkiaMetalCanvasProvider.mm * Android: Integrate Skia Dependency * fix: Use new Prefix * Add example for rendering shader * chore: Upgrade CameraX * Remove KTX * Enable `viewBinding` * Revert "Enable `viewBinding`" This reverts commit f2a603f53b33ea4311a296422ffd1a910ce03f9e. * Revert "chore: Upgrade CameraX" This reverts commit 8dc832cf8754490d31a6192e6c1a1f11cdcd94fe. * Remove unneeded `ProcessCameraProvider.getInstance()` call * fix: Add REA hotfix patch * fix: Fix FrameHostObject dead in runAsync * fix: Make `runAsync` run truly async by dropping new Frames while executing * chore: Upgrade RN Worklets to latest * chore: Upgrade RN Skia * Revert "Remove KTX" This reverts commit 253f586633f7af2da992d2279fc206dc62597129. * Make Skia optional in CMake * Fix import * Update CMakeLists.txt * Update build.gradle * Update CameraView.kt * Update CameraView.kt * Update CameraView.kt * Update Shaders.ts * Center Blur * chore: Upgrade RN Worklets * feat: Add `toByteArray()`, `orientation`, `isMirrored` and `timestamp` to `Frame` (#1487) * feat: Implement `orientation` and `isMirrored` on Frame * feat: Add `toArrayBuffer()` func * perf: Do faster buffer copy * feat: Implement `toArrayBuffer()` on Android * feat: Add `orientation` and `isMirrored` to Android * feat: Add `timestamp` to Frame * Update Frame.ts * Update JImageProxy.h * Update FrameHostObject.cpp * Update FrameHostObject.cpp * Update CameraPage.tsx * fix: Format Swift
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if (isAsyncContextBusy.value) {
// async context is currently busy, we cannot schedule new work in time.
// drop this frame/runAsync call.
return
feat: Draw onto `Frame` as if it was a Skia Canvas (#1479) * Create Shaders.ts * Add `previewType` and `enableFpsGraph` * Add RN Skia native dependency * Add Skia Preview View on iOS * Pass 1 * Update FrameHostObject.mm * Wrap Canvas * Lockfiles * fix: Fix stuff * chore: Upgrade RNWorklets * Add `previewType` to set the Preview * feat: Add Example * Update project.pbxproj * `enableFpsGraph` * Cache the `std::shared_ptr<FrameHostObject>` * Update CameraView+RecordVideo.swift * Update SkiaMetalCanvasProvider.mm * Android: Integrate Skia Dependency * fix: Use new Prefix * Add example for rendering shader * chore: Upgrade CameraX * Remove KTX * Enable `viewBinding` * Revert "Enable `viewBinding`" This reverts commit f2a603f53b33ea4311a296422ffd1a910ce03f9e. * Revert "chore: Upgrade CameraX" This reverts commit 8dc832cf8754490d31a6192e6c1a1f11cdcd94fe. * Remove unneeded `ProcessCameraProvider.getInstance()` call * fix: Add REA hotfix patch * fix: Fix FrameHostObject dead in runAsync * fix: Make `runAsync` run truly async by dropping new Frames while executing * chore: Upgrade RN Worklets to latest * chore: Upgrade RN Skia * Revert "Remove KTX" This reverts commit 253f586633f7af2da992d2279fc206dc62597129. * Make Skia optional in CMake * Fix import * Update CMakeLists.txt * Update build.gradle * Update CameraView.kt * Update CameraView.kt * Update CameraView.kt * Update Shaders.ts * Center Blur * chore: Upgrade RN Worklets * feat: Add `toByteArray()`, `orientation`, `isMirrored` and `timestamp` to `Frame` (#1487) * feat: Implement `orientation` and `isMirrored` on Frame * feat: Add `toArrayBuffer()` func * perf: Do faster buffer copy * feat: Implement `toArrayBuffer()` on Android * feat: Add `orientation` and `isMirrored` to Android * feat: Add `timestamp` to Frame * Update Frame.ts * Update JImageProxy.h * Update FrameHostObject.cpp * Update FrameHostObject.cpp * Update CameraPage.tsx * fix: Format Swift
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}
feat: Sync Frame Processors (plus `runAsync` and `runAtTargetFps`) (#1472) Before, Frame Processors ran on a separate Thread. After, Frame Processors run fully synchronous and always at the same FPS as the Camera. Two new functions have been introduced: * `runAtTargetFps(fps: number, func: () => void)`: Runs the given code as often as the given `fps`, effectively throttling it's calls. * `runAsync(frame: Frame, func: () => void)`: Runs the given function on a separate Thread for Frame Processing. A strong reference to the Frame is held as long as the function takes to execute. You can use `runAtTargetFps` to throttle calls to a specific API (e.g. if your Camera is running at 60 FPS, but you only want to run face detection at ~25 FPS, use `runAtTargetFps(25, ...)`.) You can use `runAsync` to run a heavy algorithm asynchronous, so that the Camera is not blocked while your algorithm runs. This is useful if your main sync processor draws something, and your async processor is doing some image analysis on the side. You can also combine both functions. Examples: ```js const frameProcessor = useFrameProcessor((frame) => { 'worklet' console.log("I'm running at 60 FPS!") }, []) ``` ```js const frameProcessor = useFrameProcessor((frame) => { 'worklet' console.log("I'm running at 60 FPS!") runAtTargetFps(10, () => { 'worklet' console.log("I'm running at 10 FPS!") }) }, []) ``` ```js const frameProcessor = useFrameProcessor((frame) => { 'worklet' console.log("I'm running at 60 FPS!") runAsync(frame, () => { 'worklet' console.log("I'm running on another Thread, I can block for longer!") }) }, []) ``` ```js const frameProcessor = useFrameProcessor((frame) => { 'worklet' console.log("I'm running at 60 FPS!") runAtTargetFps(10, () => { 'worklet' runAsync(frame, () => { 'worklet' console.log("I'm running on another Thread at 10 FPS, I can block for longer!") }) }) }, []) ```
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// Increment ref count by one
const internal = frame as FrameInternal
internal.incrementRefCount()
feat: Sync Frame Processors (plus `runAsync` and `runAtTargetFps`) (#1472) Before, Frame Processors ran on a separate Thread. After, Frame Processors run fully synchronous and always at the same FPS as the Camera. Two new functions have been introduced: * `runAtTargetFps(fps: number, func: () => void)`: Runs the given code as often as the given `fps`, effectively throttling it's calls. * `runAsync(frame: Frame, func: () => void)`: Runs the given function on a separate Thread for Frame Processing. A strong reference to the Frame is held as long as the function takes to execute. You can use `runAtTargetFps` to throttle calls to a specific API (e.g. if your Camera is running at 60 FPS, but you only want to run face detection at ~25 FPS, use `runAtTargetFps(25, ...)`.) You can use `runAsync` to run a heavy algorithm asynchronous, so that the Camera is not blocked while your algorithm runs. This is useful if your main sync processor draws something, and your async processor is doing some image analysis on the side. You can also combine both functions. Examples: ```js const frameProcessor = useFrameProcessor((frame) => { 'worklet' console.log("I'm running at 60 FPS!") }, []) ``` ```js const frameProcessor = useFrameProcessor((frame) => { 'worklet' console.log("I'm running at 60 FPS!") runAtTargetFps(10, () => { 'worklet' console.log("I'm running at 10 FPS!") }) }, []) ``` ```js const frameProcessor = useFrameProcessor((frame) => { 'worklet' console.log("I'm running at 60 FPS!") runAsync(frame, () => { 'worklet' console.log("I'm running on another Thread, I can block for longer!") }) }, []) ``` ```js const frameProcessor = useFrameProcessor((frame) => { 'worklet' console.log("I'm running at 60 FPS!") runAtTargetFps(10, () => { 'worklet' runAsync(frame, () => { 'worklet' console.log("I'm running on another Thread at 10 FPS, I can block for longer!") }) }) }, []) ```
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isAsyncContextBusy.value = true
feat: Draw onto `Frame` as if it was a Skia Canvas (#1479) * Create Shaders.ts * Add `previewType` and `enableFpsGraph` * Add RN Skia native dependency * Add Skia Preview View on iOS * Pass 1 * Update FrameHostObject.mm * Wrap Canvas * Lockfiles * fix: Fix stuff * chore: Upgrade RNWorklets * Add `previewType` to set the Preview * feat: Add Example * Update project.pbxproj * `enableFpsGraph` * Cache the `std::shared_ptr<FrameHostObject>` * Update CameraView+RecordVideo.swift * Update SkiaMetalCanvasProvider.mm * Android: Integrate Skia Dependency * fix: Use new Prefix * Add example for rendering shader * chore: Upgrade CameraX * Remove KTX * Enable `viewBinding` * Revert "Enable `viewBinding`" This reverts commit f2a603f53b33ea4311a296422ffd1a910ce03f9e. * Revert "chore: Upgrade CameraX" This reverts commit 8dc832cf8754490d31a6192e6c1a1f11cdcd94fe. * Remove unneeded `ProcessCameraProvider.getInstance()` call * fix: Add REA hotfix patch * fix: Fix FrameHostObject dead in runAsync * fix: Make `runAsync` run truly async by dropping new Frames while executing * chore: Upgrade RN Worklets to latest * chore: Upgrade RN Skia * Revert "Remove KTX" This reverts commit 253f586633f7af2da992d2279fc206dc62597129. * Make Skia optional in CMake * Fix import * Update CMakeLists.txt * Update build.gradle * Update CameraView.kt * Update CameraView.kt * Update CameraView.kt * Update Shaders.ts * Center Blur * chore: Upgrade RN Worklets * feat: Add `toByteArray()`, `orientation`, `isMirrored` and `timestamp` to `Frame` (#1487) * feat: Implement `orientation` and `isMirrored` on Frame * feat: Add `toArrayBuffer()` func * perf: Do faster buffer copy * feat: Implement `toArrayBuffer()` on Android * feat: Add `orientation` and `isMirrored` to Android * feat: Add `timestamp` to Frame * Update Frame.ts * Update JImageProxy.h * Update FrameHostObject.cpp * Update FrameHostObject.cpp * Update CameraPage.tsx * fix: Format Swift
2023-02-21 07:00:48 -07:00
feat: Sync Frame Processors (plus `runAsync` and `runAtTargetFps`) (#1472) Before, Frame Processors ran on a separate Thread. After, Frame Processors run fully synchronous and always at the same FPS as the Camera. Two new functions have been introduced: * `runAtTargetFps(fps: number, func: () => void)`: Runs the given code as often as the given `fps`, effectively throttling it's calls. * `runAsync(frame: Frame, func: () => void)`: Runs the given function on a separate Thread for Frame Processing. A strong reference to the Frame is held as long as the function takes to execute. You can use `runAtTargetFps` to throttle calls to a specific API (e.g. if your Camera is running at 60 FPS, but you only want to run face detection at ~25 FPS, use `runAtTargetFps(25, ...)`.) You can use `runAsync` to run a heavy algorithm asynchronous, so that the Camera is not blocked while your algorithm runs. This is useful if your main sync processor draws something, and your async processor is doing some image analysis on the side. You can also combine both functions. Examples: ```js const frameProcessor = useFrameProcessor((frame) => { 'worklet' console.log("I'm running at 60 FPS!") }, []) ``` ```js const frameProcessor = useFrameProcessor((frame) => { 'worklet' console.log("I'm running at 60 FPS!") runAtTargetFps(10, () => { 'worklet' console.log("I'm running at 10 FPS!") }) }, []) ``` ```js const frameProcessor = useFrameProcessor((frame) => { 'worklet' console.log("I'm running at 60 FPS!") runAsync(frame, () => { 'worklet' console.log("I'm running on another Thread, I can block for longer!") }) }, []) ``` ```js const frameProcessor = useFrameProcessor((frame) => { 'worklet' console.log("I'm running at 60 FPS!") runAtTargetFps(10, () => { 'worklet' runAsync(frame, () => { 'worklet' console.log("I'm running on another Thread at 10 FPS, I can block for longer!") }) }) }, []) ```
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// Call in separate background context
runOnAsyncContext(frame, func)
feat: Sync Frame Processors (plus `runAsync` and `runAtTargetFps`) (#1472) Before, Frame Processors ran on a separate Thread. After, Frame Processors run fully synchronous and always at the same FPS as the Camera. Two new functions have been introduced: * `runAtTargetFps(fps: number, func: () => void)`: Runs the given code as often as the given `fps`, effectively throttling it's calls. * `runAsync(frame: Frame, func: () => void)`: Runs the given function on a separate Thread for Frame Processing. A strong reference to the Frame is held as long as the function takes to execute. You can use `runAtTargetFps` to throttle calls to a specific API (e.g. if your Camera is running at 60 FPS, but you only want to run face detection at ~25 FPS, use `runAtTargetFps(25, ...)`.) You can use `runAsync` to run a heavy algorithm asynchronous, so that the Camera is not blocked while your algorithm runs. This is useful if your main sync processor draws something, and your async processor is doing some image analysis on the side. You can also combine both functions. Examples: ```js const frameProcessor = useFrameProcessor((frame) => { 'worklet' console.log("I'm running at 60 FPS!") }, []) ``` ```js const frameProcessor = useFrameProcessor((frame) => { 'worklet' console.log("I'm running at 60 FPS!") runAtTargetFps(10, () => { 'worklet' console.log("I'm running at 10 FPS!") }) }, []) ``` ```js const frameProcessor = useFrameProcessor((frame) => { 'worklet' console.log("I'm running at 60 FPS!") runAsync(frame, () => { 'worklet' console.log("I'm running on another Thread, I can block for longer!") }) }, []) ``` ```js const frameProcessor = useFrameProcessor((frame) => { 'worklet' console.log("I'm running at 60 FPS!") runAtTargetFps(10, () => { 'worklet' runAsync(frame, () => { 'worklet' console.log("I'm running on another Thread at 10 FPS, I can block for longer!") }) }) }, []) ```
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}