# React Native Camera: Expo vs VisionCamera — What You Need to Know

We're now in the world of AI development (aka vibe coding), and everyone is now wanting to deploy new apps that before they couldn't do to either time constraints or education limitations. I've built out a couple of mobile apps in the past, one I'm actively working on to help train hockey players, and I learned very quickly about performance bottlenecks simply because I chose the wrong stack to build with.

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<div data-node-type="callout-text">In this article, I'm specifically going to focus on React Native since so many developers will default to that because there's a larger amount of developers that innately know JavaScript. So keep that in mind before you start talking about building with Flutter or Swift.</div>
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When building mobile applications with **React Native**, accessing the camera is often a key requirement. Whether you're capturing photos, scanning barcodes, or running real-time AI inference on video frames, the choice of camera library can make or break your app’s performance.

There are two primary approaches:

* Use the `expo-camera` module (for managed workflow projects)
    
* Use `react-native-vision-camera` (for bare workflow/native modules)
    

In this article, we’ll break down the pros and cons of each option and help you decide which one is right for your project.

---

## 🧪 Quick Comparison

| Feature | `expo-camera` | `react-native-vision-camera` |
| --- | --- | --- |
| Setup Complexity | 🟢 Very easy | 🔴 Requires native module setup |
| Expo Go Compatibility | 🟢 Yes | 🔴 No (requires EAS build or bare workflow) |
| Real-Time Frame Access | 🔴 Limited | 🟢 Native-level fast access |
| Manual Camera Controls | 🔴 Basic | 🟢 Full (ISO, FPS, shutter, zoom, etc.) |
| Multi-Camera Support (ultrawide, depth) | 🔴 No | 🟢 Yes |
| ML/AI Processing Support | 🔴 Poor | 🟢 Excellent (via Frame Processors) |
| Ecosystem + Plugins | 🔴 Limited | 🟢 Robust (barcode, face detection, etc.) |

---

## 🚀 Option 1: `expo-camera`

### ✅ Why Use It?

* You're building a quick prototype or MVP
    
* You want to stay inside the Expo Managed Workflow
    
* Your needs are simple: take photos, record video, maybe scan a barcode
    

### ❌ Why Avoid It?

* You don’t get direct access to raw video frames
    
* Advanced camera controls are absent
    
* Real-time ML tasks (e.g., object detection, image classification) are slow or unsupported
    

### 📦 Installation (Expo)

```bash
npx expo install expo-camera
```

### 🔧 Basic Usage

```plaintext
import { Camera } from 'expo-camera';

const MyCamera = () => {
  const [permission, requestPermission] = Camera.useCameraPermissions();

  if (!permission?.granted) {
    return <Button onPress={requestPermission} title="Grant Camera Access" />;
  }

  return <Camera style={{ flex: 1 }} />;
};
```

---

## 🔥 Option 2: react-native-vision-camera

If you want full control of the camera and need performance, this is the tool to use.

### ✅ Why Use It?

* You need fast access to camera frames for AI or AR.
    
* You want to integrate advanced features (HDR, frame rate control, manual focus)
    
* You’re okay configuring native modules
    

### ❌ Why Avoid It?

* You need a managed Expo workflow
    
* You’re avoiding native builds entirely
    

### 📦 Installation

```bash
npm install react-native-vision-camera
npx pod-install
```

*Note: You must also configure native permissions for Android and iOS, and request runtime permissions.*

### ⚙️ Sample Code

```plaintext
import { Camera, useCameraDevices } from 'react-native-vision-camera';

const MyCamera = () => {
  const devices = useCameraDevices();
  const device = devices.back;

  if (device == null) return <LoadingSpinner />;

  return (
    <Camera
      style={{ flex: 1 }}
      device={device}
      isActive={true}
    />
  );
};
```

---

## 🧠 VisionCamera Frame Processors

This is where vision-camera really shines. You can tap into every video frame and run real-time tasks like face detection, QR scanning, or AI inference using TFLite or custom native modules.

```plaintext
const frameProcessor = useFrameProcessor((frame) => {
  'worklet';
  const faces = scanFaces(frame); // Native plugin
  console.log(faces);
}, []);
```

---

## 🧠 Technical Breakdown: Why VisionCamera Is Superior

When performance, flexibility, or advanced use cases are involved, `react-native-vision-camera` clearly outperforms `expo-camera`. Here's why:

---

### 1\. Frame Access & Native Performance

* `expo-camera` limitation: Does **not expose raw camera frames** to JavaScript or native modules.
    
    * Result: No real-time ML, AR, or video filters.
        
* `react-native-vision-camera` advantage: Offers **Frame Processors**, written in **C++/Java/Objective-C** and executed on a **dedicated thread**, not the JS thread.
    
    * Result: Run **real-time computer vision tasks** (e.g. object detection, barcode scanning) with **low latency and zero dropped frames**.
        

---

### 2\. Direct Access to Native Camera APIs

* **Expo** wraps native APIs and only exposes what the team provides.
    
* **VisionCamera** interfaces **directly with CameraX (Android) and AVCaptureSession (iOS)**.
    
    * You get:
        
        * Full **manual control** over ISO, shutter speed, zoom, focus, white balance.
            
        * Support for **ultra-wide lenses**, **telephoto**, **HDR**, **depth sensors**.
            
        * Fine-grain access to **stream formats** like raw or YUV.
            

---

### 3\. No JavaScript Thread Bottlenecks

* `expo-camera` sends preview frames and camera actions over the **JS bridge**:
    
    * This introduces **lag** and **frame drops**.
        
* **VisionCamera**:
    
    * Uses **GPU-backed native rendering** for the preview.
        
    * Fully decouples camera logic from the JS thread.
        
    * **Preview stays fluid** even while running compute-heavy tasks in parallel.
        

---

### 4\. Plugin Ecosystem & Custom Native Extensions

* VisionCamera supports a **modular plugin system**, enabling:
    
    * Custom **Frame Processors** (e.g., scanFaces, detectBarcodes, trackMotion).
        
    * Direct integration with **TensorFlow Lite**, **MediaPipe**, or even **OpenCV**.
        
    * Native code execution inside the camera pipeline for **peak performance**.
        

---

### 5\. Real-Time ML/AI Processing

* AI camera apps demand **low latency**.
    
* **With Expo:**
    
    * Capture → JS bridge → process in JS → render = 🚫 too slow.
        
* **With VisionCamera:**
    
    * Frames processed natively within **2–5ms**.
        
    * Consistent **30–60 FPS inference** supported.
        
    * Enables use cases like gesture detection, object recognition, pose estimation, etc.
        

---

## 🔧 TL;DR – If You're Doing Anything Advanced:

| Requirement | `expo-camera` | `react-native-vision-camera` |
| --- | --- | --- |
| Real-time ML/AI | 🔴 No | 🟢 Yes (via Frame Processors) |
| Manual camera control | 🔴 Minimal | 🟢 Full native control |
| High FPS (60+) | 🔴 Limited | 🟢 Supported |
| Multi-camera (e.g. ultrawide) | 🔴 No | 🟢 Yes |
| Native plugin support | 🔴 None | 🟢 Custom native extensions |

---

## 🚀 Conclusion

If you need a basic camera for photos or videos and want fast setup, `expo-camera` is fine.

But for serious apps — especially those involving **AI**, **AR**, **advanced camera controls**, or **high-performance UX** — `react-native-vision-camera` is the right tool.

> ⚠️ Just be ready to go beyond Expo Go and configure native builds — it's worth it.

## 💡 Final Recommendation

Use Case Library Simple photo/video features, fast setup expo-camera Real-time ML, AR, advanced controls needed react-native-vision-camera Need to stay inside Expo Go expo-camera Willing to eject for better performance react-native-vision-camera

---

## 🧱 Wrap-Up

This is obviously written specifically for those that are working on an active project in Gauntlet AI Cohort 2. If any of you have any questions on this, feel free to hmu.

---

## 🧰 Helpful Links

* [VisionCamera GitHub](https://github.com/mrousavy/react-native-vision-camera)
    
* [Expo Camera Docs](https://docs.expo.dev/versions/latest/sdk/camera/)
    
* [VisionCamera Frame Processor Docs](https://react-native-vision-camera.com/docs/guides/frame-processors)
    

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*Let me know if you want to dive deeper into performance benchmarks or set up a real-time ML example using VisionCamera + TensorFlow Lite!*