ObjectDetectionModule

TypeScript API implementation of the useObjectDetection hook.

Reference

import {
  ObjectDetectionModule,
  SSDLITE_320_MOBILENET_V3_LARGE,
} from 'react-native-executorch';

const imageUri = 'path/to/image.png';

const module = new ObjectDetectionModule();

// Loading the model
await module.load(SSDLITE_320_MOBILENET_V3_LARGE);

// Running the model
const detections = await module.forward(imageUri);

Methods

Method	Type	Description
load	(modelSource: ResourceSource, onDownloadProgressCallback: (_: number) => void () => {}): Promise<void>	Loads the model, where modelSource is a string that specifies the location of the model binary. To track the download progress, supply a callback function onDownloadProgressCallback.
forward	(input: string, detectionThreshold: number = 0.7): Promise<Detection[]>	Executes the model's forward pass, where input can be a fetchable resource or a Base64-encoded string. detectionThreshold can be supplied to alter the sensitivity of the detection.
delete	(): void	Release the memory held by the module. Calling forward afterwards is invalid.

Type definitions

type ResourceSource = string | number | object;

interface Bbox {
  x1: number;
  x2: number;
  y1: number;
  y2: number;
}

interface Detection {
  bbox: Bbox;
  label: keyof typeof CocoLabel;
  score: number;
}

Loading the model

To load the model, create a new instance of the module and use the load method on it. It accepts the modelSource which is a string that specifies the location of the model binary. For more information, take a look at loading models page. This method returns a promise, which can resolve to an error or void.

Running the model

To run the model, you can use the forward method on the module object. It accepts one argument, which is the image. The image can be a remote URL, a local file URI, or a base64-encoded image. The method returns a promise, which can resolve either to an error or an array of Detection objects. Each object contains coordinates of the bounding box, the label of the detected object, and the confidence score.

Managing memory

The module is a regular JavaScript object, and as such its lifespan will be managed by the garbage collector. In most cases this should be enough, and you should not worry about freeing the memory of the module yourself, but in some cases you may want to release the memory occupied by the module before the garbage collector steps in. In this case use the method delete() on the module object you will no longer use, and want to remove from the memory. Note that you cannot use forward after delete unless you load the module again.