Class: ObjectDetectionModule<T>
Defined in: modules/computer_vision/ObjectDetectionModule.ts:59
Generic object detection module with type-safe label maps.
Extends
VisionLabeledModule<Detection<ResolveLabels<T>>[],ResolveLabels<T>>
Type Parameters
T
T extends ObjectDetectionModelName | LabelEnum
Either a built-in model name (e.g. 'ssdlite-320-mobilenet-v3-large')
or a custom LabelEnum label map.
Properties
generateFromFrame()
generateFromFrame: (
frameData, ...args) =>any
Defined in: modules/BaseModule.ts:56
Process a camera frame directly for real-time inference.
This method is bound to a native JSI function after calling load(),
making it worklet-compatible and safe to call from VisionCamera's
frame processor thread.
Performance characteristics:
- Zero-copy path: When using
frame.getNativeBuffer()from VisionCamera v5, frame data is accessed directly without copying (fastest, recommended). - Copy path: When using
frame.toArrayBuffer(), pixel data is copied from native to JS, then accessed from native code (slower, fallback).
Usage with VisionCamera:
const frameOutput = useFrameOutput({
pixelFormat: 'rgb',
onFrame(frame) {
'worklet';
// Zero-copy approach (recommended)
const nativeBuffer = frame.getNativeBuffer();
const result = model.generateFromFrame(
{ nativeBuffer: nativeBuffer.pointer, width: frame.width, height: frame.height },
...args
);
nativeBuffer.release();
frame.dispose();
}
});
Parameters
frameData
Frame data object with either nativeBuffer (zero-copy) or data (ArrayBuffer)
args
...any[]
Additional model-specific arguments (e.g., threshold, options)
Returns
any
Model-specific output (e.g., detections, classifications, embeddings)
See
Frame for frame data format details
Inherited from
VisionLabeledModule.generateFromFrame
labelMap
protectedreadonlylabelMap:ResolveLabels
Defined in: modules/computer_vision/VisionLabeledModule.ts:16
Inherited from
VisionLabeledModule.labelMap
nativeModule
nativeModule:
any=null
Defined in: modules/BaseModule.ts:17
Internal
Native module instance (JSI Host Object)
Inherited from
VisionLabeledModule.nativeModule
Accessors
runOnFrame
Get Signature
get runOnFrame(): (
frame, ...args) =>TOutput|null
Defined in: modules/computer_vision/VisionModule.ts:61
Synchronous worklet function for real-time VisionCamera frame processing.
Only available after the model is loaded. Returns null if not loaded.
Use this for VisionCamera frame processing in worklets.
For async processing, use forward() instead.
Example
const model = new ClassificationModule();
await model.load({ modelSource: MODEL });
// Use the functional form of setState to store the worklet — passing it
// directly would cause React to invoke it immediately as an updater fn.
const [runOnFrame, setRunOnFrame] = useState(null);
setRunOnFrame(() => model.runOnFrame);
const frameOutput = useFrameOutput({
onFrame(frame) {
'worklet';
if (!runOnFrame) return;
const result = runOnFrame(frame);
frame.dispose();
}
});
Returns
(frame, ...args) => TOutput | null
Inherited from
VisionLabeledModule.runOnFrame
Methods
delete()
delete():
void
Defined in: modules/BaseModule.ts:100
Unloads the model from memory and releases native resources.
Always call this method when you're done with a model to prevent memory leaks.
Returns
void
Inherited from
VisionLabeledModule.delete
forward()
forward(
input,detectionThreshold?):Promise<Detection<ResolveLabels<T, {rf-detr-nano: {labelMap: typeofCocoLabel;preprocessorConfig: {normMean:Triple<number>;normStd:Triple<number>; }; };ssdlite-320-mobilenet-v3-large: {labelMap: typeofCocoLabel;preprocessorConfig:undefined; }; }>>[]>
Defined in: modules/computer_vision/ObjectDetectionModule.ts:118
Executes the model's forward pass to detect objects within the provided image.
Parameters
input
A string image source (file path, URI, or Base64) or a PixelData object.
string | PixelData
detectionThreshold?
number = 0.7
Minimum confidence score for a detection to be included. Default is 0.7.
Returns
Promise<Detection<ResolveLabels<T, { rf-detr-nano: { labelMap: typeof CocoLabel; preprocessorConfig: { normMean: Triple<number>; normStd: Triple<number>; }; }; ssdlite-320-mobilenet-v3-large: { labelMap: typeof CocoLabel; preprocessorConfig: undefined; }; }>>[]>
A Promise resolving to an array of Detection objects.
Overrides
VisionLabeledModule.forward
forwardET()
protectedforwardET(inputTensor):Promise<TensorPtr[]>
Defined in: modules/BaseModule.ts:80
Internal
Runs the model's forward method with the given input tensors. It returns the output tensors that mimic the structure of output from ExecuTorch.
Parameters
inputTensor
Array of input tensors.
Returns
Promise<TensorPtr[]>
Array of output tensors.
Inherited from
VisionLabeledModule.forwardET
getInputShape()
getInputShape(
methodName,index):Promise<number[]>
Defined in: modules/BaseModule.ts:91
Gets the input shape for a given method and index.
Parameters
methodName
string
method name
index
number
index of the argument which shape is requested
Returns
Promise<number[]>
The input shape as an array of numbers.
Inherited from
VisionLabeledModule.getInputShape
load()
load():
Promise<void>
Defined in: modules/computer_vision/VisionLabeledModule.ts:25
Load the model and prepare it for inference.
Returns
Promise<void>
Inherited from
VisionLabeledModule.load
fromCustomConfig()
staticfromCustomConfig<L>(modelSource,config,onDownloadProgress?):Promise<ObjectDetectionModule<L>>
Defined in: modules/computer_vision/ObjectDetectionModule.ts:125
Type Parameters
L
L extends Readonly<Record<string, string | number>>
Parameters
modelSource
config
onDownloadProgress?
(progress) => void
Returns
Promise<ObjectDetectionModule<L>>
fromModelName()
staticfromModelName<C>(config,onDownloadProgress?):Promise<ObjectDetectionModule<ModelNameOf<C>>>
Defined in: modules/computer_vision/ObjectDetectionModule.ts:73
Creates an object detection instance for a built-in model.
Type Parameters
C
C extends ObjectDetectionModelSources
Parameters
config
C
A ObjectDetectionModelSources object specifying which model to load and where to fetch it from.
onDownloadProgress?
(progress) => void
Optional callback to monitor download progress, receiving a value between 0 and 1.
Returns
Promise<ObjectDetectionModule<ModelNameOf<C>>>
A Promise resolving to an ObjectDetectionModule instance typed to the chosen model's label map.