React Native ML Kit — Object Detection

@nitro-mlkit/object-detection · on-device Google ML Kit via Nitro Modules — JSI, no bridge.

⚠️ Beta (0.1.0-beta.x). Android verified on-device; iOS builds & links but device runtime is pending — see Platform status.

High-performance, on-device object detection & tracking for React Native, built with Nitro Modules (JSI, no bridge).

Powered by Google ML Kit. Detects prominent objects in an image with bounding boxes and coarse category labels. All on-device.

Installation

npm install @nitro-mlkit/object-detection@beta react-native-nitro-modules

No config plugin (it's an autolinked Expo module). Just install and npx expo prebuild. Not available in Expo Go.

Usage

import { NitroObjects } from "@nitro-mlkit/object-detection";

const objects = await NitroObjects.detect(imageUri);
// → [{ bounds:{x,y,width,height}, trackingId, labels:[{text,confidence,index}] }]

// Native batch — one JSI call
const results = await NitroObjects.detectBatch(uris, 4 /* concurrency */);

NitroObjects.isAvailable(); // boolean

Uses SINGLE_IMAGE_MODE with multiple objects + coarse classification. ML Kit's default classifier covers broad categories (Fashion good, Home good, Food, Place, Plant); it targets prominent objects, not faces/people.

Platform status

| Platform | Min | Status | | -------- | --- | ------ | | Android | API 21+ | ✅ Verified on-device (Pixel 9, API 36): detect runs in ~200 ms | | iOS | 15.5+ | ⚠️ Swift impl written; on-device build & run pending¹ | | tvOS/macOS | — | 🔜 Planned |

¹ ML Kit's iOS pods ship no arm64 Simulator slice; validate on a physical device.

Part of nitro-mlkit

The full ML Kit suite on Nitro — see the other @nitro-mlkit/* packages.

License

MIT © Gonzalo Polo