The document describes how to use TensorFlow Lite with a GPU delegate for model inference in a continuous loop. It includes initializing the interpreter with GPU support, running inference in a coroutine, and updating the UI with results. Additionally, it mentions the importance of cleaning up the delegate after operations.

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12. import org.tensorflow.lite.Interpreter
import org.tensorflow.lite.experimental.GpuDelegate
// Initialize interpreter with GPU delegate
protected val delegate = GpuDelegate()
protected var options = (Interpreter.Options()).addDelegate(delegate)
protected var interpreter = Interpreter(model, options)
// Run inference
while (true)
{
writeToInput(input)
interpreter.run(input, output)
readFromOutput(output)
}
// Clean up
delegate.close()
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31. CoroutineScope(Dispatchers.Main).launch {
var data = ""
CoroutineScope(Dispatchers.Default).async {
// Background Thread에서 모델 추론 실행
}.await()
// 모델 추론 결과 UI 업데이트
}
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