TFLiteCamera is a library that provides an easy-to-use interface for integrating TensorFlow Lite image classification models with the device camera. With TFLiteCamera, developers can quickly build applications that perform real-time image classification on-device, without the need for internet connectivity.
Features
- Capture real-time images from device camera
- Perform image classification using TensorFlow Lite models
- No internet connectivity required for inference
- Efficient resource utilization for real-time performance
- Easy integration with existing Android and iOS projects
Installation
To install TFLiteCamera in your project, follow these steps:
Android
1. Add the following line to your project’s `build.gradle` file:
implementation 'com.example:tflitecamera:1.0.0'
iOS
1. Add the following line to your project’s `Podfile`:
pod 'TFLiteCamera', '~> 1.0.0'
2. Run the following command in the terminal:
pod install
Usage
Using TFLiteCamera in your application is straightforward. Follow the steps below:
1. Initialize TFLiteCamera
To begin, initialize the TFLiteCamera instance within your activity or view controller:
TFLiteCamera tfliteCamera = new TFLiteCamera(context);
2. Connect Camera Preview
Next, connect the camera preview to your layout XML file:
<com.example.tflitecamera.TFLiteCameraView
android:id="@+id/cameraView"
android:layout_width="match_parent"
android:layout_height="match_parent" />
3. Start Camera Preview
To start the camera preview, call the following method in your activity’s `onResume()` method or equivalent:
tfliteCamera.startCameraPreview(cameraView);
4. Perform Image Classification
Finally, implement the image classification logic by calling the `classifyImage()` method:
tfliteCamera.classifyImage(new TFLiteCamera.OnImageClassifiedListener() {
@Override
public void onImageClassified(String result) {
// Handle classification result
}
});
Compatibility
TFLiteCamera is compatible with the following platforms:
- Android 5.0 (API level 21) and above
- iOS 10 and above
Resources
For more information on using TFLiteCamera, refer to the following resources: