Tensorflow音频分类

tensorflow

https://www.tensorflow.org/lite/examples/audio_classification/overview?hl=zh-cn

官方有移动端demo

前端不会  就只能找找有没有java支持

注意版本

注意JDK版本

package com.example.demo17.controller;import org.tensorflow.*;
import org.tensorflow.ndarray.*;
import org.tensorflow.ndarray.impl.dense.FloatDenseNdArray;
import org.tensorflow.proto.framework.DataType;
import org.tensorflow.proto.framework.MetaGraphDef;
import org.tensorflow.proto.framework.SignatureDef;
import org.tensorflow.proto.framework.TensorInfo;
import org.tensorflow.types.TFloat32;
import org.tensorflow.types.TInt64;import javax.sound.sampled.AudioFormat;
import javax.sound.sampled.AudioInputStream;
import javax.sound.sampled.AudioSystem;
import javax.sound.sampled.UnsupportedAudioFileException;
import javax.xml.transform.Result;
import java.io.File;
import java.io.IOException;
import java.io.InputStream;
import java.nio.file.Files;
import java.nio.file.Paths;
import java.util.*;
import java.util.concurrent.ConcurrentHashMap;public class Test {private static FloatNdArray t1() {
//        String audioFilePath = "D:\\ai\\cat.wav";String audioFilePath = "C:\\Users\\user\\Downloads\\output_Wo9KJb-5zuz1_2.wav";
//        String audioFilePath = "D:\\ai\\111\\111.wav";// YAMNet期望的采样率int sampleRate = 16000;// YAMNet帧大小，0.96秒int frameSizeInMs = 96;// YAMNet帧步长，0.48秒int hopSizeInMs = 48;try (AudioInputStream audioStream = AudioSystem.getAudioInputStream(Paths.get(audioFilePath).toFile())) {AudioFormat format = audioStream.getFormat();if (format.getSampleRate() != sampleRate || format.getChannels() != 1) {System.out.println("Warning: Audio must be 16kHz mono. Consider preprocessing.");}int frameSize = (int) (sampleRate * frameSizeInMs / 1000);int hopSize = (int) (sampleRate * hopSizeInMs / 1000);byte[] buffer = new byte[frameSize * format.getFrameSize()];short[] audioSamples = new short[frameSize];// 存储每个帧的音频数据List<Float> floatList = new ArrayList<>();while (true) {int bytesRead = audioStream.read(buffer);if (bytesRead == -1) {break;}// 将读取的字节转换为short数组（假设16位精度）for (int i = 0; i < bytesRead / format.getFrameSize(); i++) {audioSamples[i] = (short) ((buffer[i * 2] & 0xFF) | (buffer[i * 2 + 1] << 8));}// 对当前帧进行处理（例如，归一化和准备送入模型）float[] floats = processFrame(audioSamples);for (float aFloat : floats) {floatList.add(aFloat);}// 移动到下一个帧System.arraycopy(audioSamples, hopSize, audioSamples, 0, frameSize - hopSize);}// 将List<Float>转换为float[]float[] floatArray = new float[floatList.size()];for (int i = 0; i < floatList.size(); i++) {floatArray[i] = floatList.get(i);}return StdArrays.ndCopyOf(floatArray);} catch (UnsupportedAudioFileException | IOException e) {e.printStackTrace();}return null;}private static float[] processFrame(short[] frame) {// 示例：归一化音频数据到[-1.0, 1.0]float[] normalizedFrame = new float[frame.length];for (int i = 0; i < frame.length; i++) {// short的最大值为32767，故除以32768得到[-1.0, 1.0]normalizedFrame[i] = frame[i] / 32768f;}return normalizedFrame;}static Map<String,String> map=new ConcurrentHashMap<>();public static void main(String[] args) throws Exception {FloatNdArray floatNdArray = t1();TFloat32 tFloat32 = TFloat32.tensorOf(floatNdArray);//SavedModelBundle savedModelBundle = SavedModelBundle.load("D:\\saved_model", "serve");SavedModelBundle savedModelBundle = SavedModelBundle.load("C:\\Users\\user\\Downloads\\archive", "serve");Map<String, SignatureDef> signatureDefMap = MetaGraphDef.parseFrom(savedModelBundle.metaGraphDef().toByteArray()).getSignatureDefMap();/*** 获取基本定义信息*/SignatureDef modelSig = signatureDefMap.get("serving_default");String inputTensorName = modelSig.getInputsMap().get("waveform").getName();String outputTensorName = modelSig.getOutputsMap().get("output_0").getName();savedModelBundle.graph();try (Session session = savedModelBundle.session()) {/*JDK 17*/
//            Result run = session.runner()
//                    .feed(inputTensorName, tFloat32)
//                    .fetch(outputTensorName)
//                    .run();
//            Tensor out = run.get(0);
//            Shape shape = out.shape();
//
//            System.out.println(shape);/*JDK 8*/List<Tensor> run = session.runner().feed(inputTensorName, tFloat32).fetch(outputTensorName).run();Tensor tensor = run.get(0);Shape shape = tensor.shape();System.out.println(shape.asArray());String l=String.valueOf(shape.asArray()[0]);//读取CSV文件String csvFile = "C:\\Users\\user\\Downloads\\archive\\assets\\yamnet_class_map.csv";try {List<String> lines = Files.readAllLines(Paths.get(csvFile));for (String line : lines) {String[] values = line.split(",");map.put(values[0], values[2]);}} catch (IOException e) {e.printStackTrace();}String s = map.get(l);System.out.println(s);}}
}