如何在Java项目中整合人工智能

<dependency>
    <groupId>org.tensorflow</groupId>
    <artifactId>tensorflow</artifactId>
    <version>2.3.0</version>
</dependency>

BufferedImage image = ImageIO.read(new File("path/to/image.jpg"));
TensorImage tensorImage = TensorImage.fromBufferedImage(image);
SavedModelBundle model = SavedModelBundle.load("path/to/saved_model/", "serve");
Tensors input = Tensors.create(tensorImage.getTensor());
Tensors output = model.call(input);

float[] probabilities = output.getFloatArray();
int highestProbabilityIndex = 0;
float highestProbability = 0.0f;

for (int i = 0; i < probabilities.length; i++) {
    if (probabilities[i] > highestProbability) {
        highestProbabilityIndex = i;
        highestProbability = probabilities[i];
    }
}

// 获得类别标签
String category = model.getMetaGraphDef().getSignatureDefMap().values().stream()
    .map(SignatureDef::getOutputsMap)
    .map(m -> m.entrySet().stream()
        .filter(e -> e.getKey().equals("classes"))
        .map(e -> e.getValue().getTensorInfo())
        .map(TensorInfo::getName))
    .flatMap(Stream::findFirst)
    .get();

String label = category.substring(category.lastIndexOf("/") + 1);

System.out.println("图像分类为：" + label + "，概率为：" + highestProbability);