//package org.jeecg.modules.dry.util;
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//
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//import ai.djl.Device;
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//import ai.djl.Model;
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//import ai.djl.inference.Predictor;
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//import ai.djl.modality.Classifications;
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//import ai.djl.modality.cv.Image;
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//import ai.djl.modality.cv.ImageFactory;
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//import ai.djl.modality.cv.transform.*;
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//import ai.djl.modality.cv.translator.ImageClassificationTranslator;
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//import ai.djl.translate.Translator;
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//import lombok.extern.slf4j.Slf4j;
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//import org.springframework.core.io.Resource;
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//import org.springframework.core.io.support.PathMatchingResourcePatternResolver;
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//import org.springframework.core.io.support.ResourcePatternResolver;
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//import org.springframework.stereotype.Component;
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//
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//import javax.imageio.ImageIO;
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//import javax.imageio.stream.ImageOutputStream;
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//import java.awt.*;
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//import java.awt.image.BufferedImage;
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//import java.io.*;
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//import java.util.ArrayList;
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//import java.util.List;
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//
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//@Slf4j
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//@Component
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//public class HerbUtil {
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//
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// //规定输入尺寸
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// private static final int INPUT_SIZE = 224;
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//
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// private static final int TARGET_SIZE = 256;
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//
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// //标签文件 一种类别名字占一行
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// private List<String> herbNames;
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//
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// //用于识别
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// Predictor<Image, Classifications> predictor;
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//
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// //模型
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// private Model model;
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//
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// public HerbUtil() {
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// //加载标签到herbNames中
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// this.loadHerbNames();
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// //初始化模型工作
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// this.init();
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//
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//
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//
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// }
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//
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// public List<Classifications.Classification> predict(InputStream inputStream) {
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// List<Classifications.Classification> result = new ArrayList<>();
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// Image input = this.resizeImage(inputStream);
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// try {
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// Classifications output = predictor.predict(input);
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// System.out.println("推测为：" + output.best().getClassName()
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// + ", 概率：" + output.best().getProbability());
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// System.out.println(output);
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// result = output.topK();
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// } catch (Exception e) {
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// log.error("药材识别异常！！");
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// log.error(input.toString());
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// log.error(predictor.toString());
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// e.printStackTrace();
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// }
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// return result;
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// }
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//
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// private void loadHerbNames() {
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// BufferedReader reader = null;
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// herbNames = new ArrayList<>();
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// try {
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// InputStream in = HerbUtil.class.getClassLoader().getResourceAsStream("class.txt");
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// reader = new BufferedReader(new InputStreamReader(in));
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// String name = null;
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// while ((name = reader.readLine()) != null) {
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// herbNames.add(name);
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// }
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// System.out.println(herbNames);
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// } catch (Exception e) {
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// e.printStackTrace();
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// } finally {
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// if (reader != null) {
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// try {
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// reader.close();
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// } catch (IOException e) {
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// e.printStackTrace();
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// }
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// }
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// }
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// }
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//
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// private void init() {
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// Translator<Image, Classifications> translator = ImageClassificationTranslator.builder()
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// //下面的transform根据自己的改
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// .addTransform(new CenterCrop(INPUT_SIZE,INPUT_SIZE))
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//
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// .addTransform(new ToTensor())
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// .addTransform(new Normalize(
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// new float[] {0.485f, 0.456f, 0.406f},
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// new float[] {0.229f, 0.224f, 0.225f}))
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//
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// //载入所有标签进去
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// .optSynset(herbNames)
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// //最终显示概率最高的5个
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// .optTopK(5)
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// .build();
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// //随便起名
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// Model model = Model.newInstance("model", Device.cpu());
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// try {
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//// ResourcePatternResolver resolver = new PathMatchingResourcePatternResolver();
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//// Resource[] resources = resolver.getResources("../pytorch/model34.pt");
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// // Resource resource = resources[0];
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// File f = new File("../pytorch/model34.pt");
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//
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// InputStream inputStream = new FileInputStream(f);
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// // InputStream inputStream = HerbUtil.class.getClassLoader().getResourceAsStream("model34.pt");
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// if (inputStream == null) {
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// throw new RuntimeException("找不到模型文件");
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// }
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// model.load(inputStream);
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//
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// predictor = model.newPredictor(translator);
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// } catch (Exception e) {
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// e.printStackTrace();
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// }
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// }
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//
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// private Image resizeImage(InputStream inputStream) {
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// BufferedImage input = null;
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// try {
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// input = ImageIO.read(inputStream);
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// } catch (IOException e) {
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// e.printStackTrace();
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// }
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// int iw = input.getWidth(), ih = input.getHeight();
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// int w = 256, h = 256;
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// double scale = Math.max(1. * w / iw, 1. * h / ih);
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// int nw = (int) (iw * scale), nh = (int) (ih * scale);
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// java.awt.Image img;
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// //只有太长或太宽才会保留横纵比，填充颜色
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// // boolean needResize = 1. * iw / ih > 1.4 || 1. * ih / iw > 1.4;
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// // if (needResize) {
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// img = input.getScaledInstance(nw, nh, BufferedImage.SCALE_SMOOTH);
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// // } else {
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// // img = input.getScaledInstance(INPUT_SIZE, INPUT_SIZE, BufferedImage.SCALE_SMOOTH);
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// // }
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// BufferedImage out = new BufferedImage(nw, nh, BufferedImage.TYPE_INT_RGB);
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// Graphics g = out.getGraphics();
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// //先将整个224*224区域填充128 128 128颜色
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// g.setColor(new Color(255, 255, 255));
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// g.fillRect(0, 0, nw, nh);
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// out.getGraphics().drawImage(img, 0, 0, null);
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// ByteArrayOutputStream outputStream = new ByteArrayOutputStream();
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// try {
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// ImageOutputStream imageOutputStream = ImageIO.createImageOutputStream(outputStream);
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// ImageIO.write(out, "jpg", imageOutputStream);
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// //去D盘看效果
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// ImageIO.write(out, "jpg", new File("E:\\out.jpg"));
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// InputStream is = new ByteArrayInputStream(outputStream.toByteArray());
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// return ImageFactory.getInstance().fromInputStream(is);
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// } catch (IOException e) {
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// e.printStackTrace();
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// throw new RuntimeException("图片转换失败");
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// }
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// }
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//}
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