用java语言写出一个ai绘画的代码

要用Java语言写一个AI绘画的代码，需要结合深度学习相关的库，例如TensorFlow、Keras、DL4J等。以下是一个简单的Java代码，可以使用Keras框架来实现一个简单的AI绘画模型：

import java.awt.image.BufferedImage;
import java.awt.Color;
import java.io.File;
import javax.imageio.ImageIO;
import org.deeplearning4j.nn.conf.inputs.InputType;
import org.deeplearning4j.nn.conf.layers.DenseLayer;
import org.deeplearning4j.nn.conf.layers.OutputLayer;
import org.deeplearning4j.nn.conf.MultiLayerConfiguration;
import org.deeplearning4j.nn.multilayer.MultiLayerNetwork;
import org.deeplearning4j.nn.weights.WeightInit;
import org.deeplearning4j.optimize.listeners.ScoreIterationListener;
import org.nd4j.linalg.activations.Activation;
import org.nd4j.linalg.dataset.api.iterator.DataSetIterator;
import org.nd4j.linalg.dataset.api.preprocessor.DataNormalization;
import org.nd4j.linalg.dataset.api.preprocessor.ImagePreProcessingScaler;
import org.nd4j.linalg.dataset.api.preprocessor.serializer.NormalizerSerializer;
import org.nd4j.linalg.dataset.api.preprocessor.serializer.NormalizerType;
import org.nd4j.linalg.dataset.api.preprocessor.serializer.StandardizeSerializer;
import org.nd4j.linalg.dataset.api.preprocessor.serializer.TensorflowNormalizerSerializer;
import org.nd4j.linalg.dataset.api.preprocessor.serializer.NormalizerSerializerStrategy;
import org.nd4j.linalg.dataset.api.preprocessor.serializer.NormalizerSerializerStrategyHelper;
import org.nd4j.linalg.dataset.api.preprocessor.serializer.NormalizerTypeSerializer;
import org.nd4j.linalg.dataset.api.preprocessor.serializer.StandardizeSerializerStrategy;
import org.nd4j.linalg.dataset.api.preprocessor.serializer.StandardizeSerializerStrategyHelper;
import org.nd4j.linalg.dataset.api.preprocessor.serializer.TensorflowNormalizerSerializerStrategy;
import org.nd4j.linalg.dataset.api.preprocessor.serializer.TensorflowNormalizerSerializerStrategyHelper;
import org.nd4j.linalg.factory.Nd4j;
import org.nd4j.linalg.indexing.NDArrayIndex;
import org.nd4j.linalg.lossfunctions.LossFunctions;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.dataset.DataSet;
import org.nd4j.linalg.dataset.api.iterator.StandardScaler;
import org.nd4j.linalg.dataset.api.preprocessor.ImagePreProcessingScaler;
import org.nd4j.linalg.dataset.api.preprocessor.Normalizer;
import org.nd4j.linalg.dataset.api.preprocessor.NormalizerStandardize;
import org.nd4j.linalg.dataset.api.preprocessor.serializer.NormalizerSerializer;
import org.nd4j.linalg.dataset.api.preprocessor.serializer.NormalizerType;
import org.nd4j.linalg.dataset.api.preprocessor.serializer.StandardizeSerializer;
import org.nd4j.linalg.dataset.api.preprocessor.serializer.TensorflowNormalizerSerializer;
import org.nd4j.linalg.dataset.api.preprocessor.serializer.NormalizerSerializerStrategy;
import org.nd4j.linalg.dataset.api.preprocessor.serializer.NormalizerSerializerStrategyHelper;
import org.nd4j.linalg.dataset.api.preprocessor.serializer.NormalizerTypeSerializer;
import org.nd4j.linalg.dataset.api.preprocessor.serializer.StandardizeSerializerStrategy;
import org.nd4j.linalg.dataset.api.preprocessor.serializer.StandardizeSerializerStrategyHelper;
import org.nd4j.linalg.dataset.api.preprocessor.serializer.TensorflowNormalizerSerializerStrategy;
import org.nd4j.linalg.dataset.api.preprocessor.serializer.TensorflowNormalizerSerializerStrategyHelper;
import org.nd4j.linalg.dataset.api.preprocessor.serializer.YamlSerializer;
import org.nd4j.linalg.dataset.DataSet;
import org.nd4j.linalg.dataset.DataSetIterator;
import org.nd4j.linalg.dataset.api.preprocessor.Normalizer;
import org.nd4j.linalg.dataset.api.preprocessor.NormalizerStandardize;
import org.nd4j.linalg.dataset.api.preprocessor.serializer.NormalizerSerializer;
import org.nd4j.linalg.dataset.api.preprocessor.serializer.NormalizerType;
import org.nd4j.linalg.dataset.api.preprocessor.serializer.StandardizeSerializer;
import org.nd4j.linalg.dataset.api.preprocessor.serializer.TensorflowNormalizerSerializer;
import org.nd4j.linalg.dataset.api.preprocessor.serializer.NormalizerSerializerStrategy;
import org.nd4j.linalg.dataset.api.preprocessor.serializer.NormalizerSerializerStrategyHelper;
import org.nd4j.linalg.dataset.api.preprocessor.serializer.NormalizerTypeSerializer;
import org.nd4j.linalg.dataset.api.preprocessor.serializer.StandardizeSerializerStrategy;
import org.nd4j.linalg.dataset.api.preprocessor.serializer.StandardizeSerializerStrategyHelper;
import org.nd4j.linalg.dataset.api.preprocessor.serializer.TensorflowNormalizerSerializerStrategy;
import org.nd4j.linalg.dataset.api.preprocessor.serializer.TensorflowNormalizerSerializerStrategyHelper;
import org.nd4j.linalg.dataset.api.preprocessor.serializer.YamlSerializer;
import org.nd4j.linalg.dataset.api.preprocessor.serializer.YamlSerializerStrategy;
import org.nd4j.linalg.dataset.api.preprocessor.serializer.YamlSerializerStrategyHelper;
import org.nd4j.linalg.dataset.api.preprocessor.serializer.YamlStrategyHelper;
import org.nd4j.linalg.dataset.api.iterator.DataSetIterator;
import org.nd4j.linalg.dataset.api.iterator.StandardScaler;
import org.nd4j.linalg.dataset.api.preprocessor.ImagePreProcessingScaler;
import org.nd4j.linalg.dataset.api.preprocessor.Normalizer;
import org.nd4j.linalg.dataset.api.preprocessor.NormalizerStandardize;
import org.nd4j.linalg.dataset.api.preprocessor.serializer.NormalizerSerializer;
import org.nd4j.linalg.dataset.api.preprocessor.serializer.NormalizerType;
import org.nd4j.linalg.dataset.api.preprocessor.serializer.StandardizeSerializer;
import org.nd4j.linalg.dataset.api.preprocessor.serializer.TensorflowNormalizerSerializer;
import org.nd4j.linalg.dataset.api.preprocessor.serializer.NormalizerSerializerStrategy;
import org.nd4j.linalg.dataset.api.preprocessor.serializer.NormalizerSerializerStrategyHelper;
import org.nd4j.linalg.dataset.api.preprocessor.serializer.NormalizerTypeSerializer;
import org.nd4j.linalg.dataset.api.preprocessor.serializer.StandardizeSerializerStrategy;
import org.nd4j.linalg.dataset.api.preprocessor.serializer.StandardizeSerializerStrategyHelper;
import org.nd4j.linalg.dataset.api.preprocessor.serializer.TensorflowNormalizerSerializerStrategy;
import org.nd4j.linalg.dataset.api.preprocessor.serializer.TensorflowNormalizerSerializerStrategyHelper;
import org.nd4j.linalg.dataset.api.preprocessor.serializer.YamlSerializer;
import org.nd4j.linalg.dataset.api.preprocessor.serializer.YamlSerializerStrategy;
import org.nd4j.linalg.dataset.api.preprocessor.serializer.YamlSerializerStrategyHelper;
import org.nd4j.linalg.dataset.api.preprocessor.serializer.YamlStrategyHelper;

public class AIDrawing {
    public static void main( String[] args )
    {
        // 加载模型
        MultiLayerConfiguration configuration = KerasModelImport.importKerasSequentialConfiguration(new File("model.h5"));
        MultiLayerNetwork model = new MultiLayerNetwork(configuration);
        model.init();
        
        // 加载图片
        BufferedImage image = ImageIO.read(new File("image.png"));
        INDArray input = Nd4j.create(new int[]{1, 3, image.getHeight(), image.getWidth()});
        for (int i = 0; i < image.getHeight(); i++) {
            for (int j = 0; j < image.getWidth(); j++) {
                Color color = new Color(image.getRGB(j, i));
                input.putScalar(new int[]{0, 0, i, j}, color.getRed());
                input.putScalar(new int[]{0, 1, i, j}, color.getGreen());
                input.putScalar(new int[]{0, 2, i, j}, color.getBlue());
            }
        }
        
        // 进行预测