如何使用 Java 函數將人工智慧整合到行動和嵌入式設備？

// Gradle
implementation "com.google.cloud:google-cloud-functions-framework-java:2.0.2"
implementation "com.google.cloud:google-cloud-functions-framework-java-worker:2.0.2"

import com.google.cloud.functions.HttpFunction;
import com.google.cloud.functions.HttpRequest;
import com.google.cloud.functions.HttpResponse;

public class ImageClassifier implements HttpFunction {

  @Override
  public void service(HttpRequest request, HttpResponse response) throws IOException {
    // 解析请求体中的图像数据
    byte[] image = request.getInputStream().readAllBytes();

    // 根据需要准备图像数据（例如预处理、调整大小）

    // 使用 TensorFlow Lite 模型进行图像分类
    TensorFlowLiteInterpreter interpreter = new TensorFlowLiteInterpreter(modelFile);
    Tensor input = Tensor.create(new float[] { image });
    Tensor output = Tensor.create(new float[NUM_CLASSES]);
    interpreter.run(input, output);
    int predictedClass = maxIndex(output.getFloatArray());

    // 将预测结果写入响应
    String result = String.format("Predicted class: %s", CLASS_NAMES[predictedClass]);
    response.setContentType("text/plain");
    response.getWriter().println(result);
  }
}