From 92e356d1ee1b877bc17d3aee3a137c234f01c477 Mon Sep 17 00:00:00 2001
From: bsw215583320 <baoshiwei121@163.com>
Date: 星期三, 20 十二月 2023 16:04:59 +0800
Subject: [PATCH] 增加药材识别神经网络模型及接口
---
jeecg-module-dry/jeecg-module-dry-api/pom.xml | 15 +++
jeecg-module-dry/jeecg-module-dry-start/src/main/resources/model.pt | 0
jeecg-module-dry/jeecg-module-dry-api/src/main/java/org/jeecg/modules/dry/util/HerbUtil.java | 156 +++++++++++++++++++++++++++++++++++++++
jeecg-module-dry/jeecg-module-dry-start/src/main/resources/model1.pt | 0
jeecg-module-dry/jeecg-module-dry-biz/src/main/java/org/jeecg/modules/dry/controller/DryRealTimeDataController.java | 27 ++++++
jeecg-module-dry/jeecg-module-dry-start/src/main/resources/class.txt | 20 +++++
6 files changed, 218 insertions(+), 0 deletions(-)
diff --git a/jeecg-module-dry/jeecg-module-dry-api/pom.xml b/jeecg-module-dry/jeecg-module-dry-api/pom.xml
index 3ad456f..8bce88b 100644
--- a/jeecg-module-dry/jeecg-module-dry-api/pom.xml
+++ b/jeecg-module-dry/jeecg-module-dry-api/pom.xml
@@ -47,6 +47,21 @@
<artifactId>milo-spring-boot-starter</artifactId>
<version>3.0.4</version>
</dependency>
+ <dependency>
+ <groupId>ai.djl.pytorch</groupId>
+ <artifactId>pytorch-engine</artifactId>
+ <version>0.16.0</version>
+ </dependency>
+ <dependency>
+ <groupId>ai.djl.pytorch</groupId>
+ <artifactId>pytorch-native-auto</artifactId>
+ <version>1.9.1</version>
+ </dependency>
+ <dependency>
+ <groupId>ai.djl.pytorch</groupId>
+ <artifactId>pytorch-jni</artifactId>
+ <version>1.9.1-0.16.0</version>
+ </dependency>
</dependencies>
<build>
<plugins>
diff --git a/jeecg-module-dry/jeecg-module-dry-api/src/main/java/org/jeecg/modules/dry/util/HerbUtil.java b/jeecg-module-dry/jeecg-module-dry-api/src/main/java/org/jeecg/modules/dry/util/HerbUtil.java
new file mode 100644
index 0000000..eba00b2
--- /dev/null
+++ b/jeecg-module-dry/jeecg-module-dry-api/src/main/java/org/jeecg/modules/dry/util/HerbUtil.java
@@ -0,0 +1,156 @@
+package org.jeecg.modules.dry.util;
+
+import ai.djl.Device;
+import ai.djl.Model;
+import ai.djl.inference.Predictor;
+import ai.djl.modality.Classifications;
+import ai.djl.modality.cv.Image;
+import ai.djl.modality.cv.ImageFactory;
+import ai.djl.modality.cv.transform.*;
+import ai.djl.modality.cv.translator.ImageClassificationTranslator;
+import ai.djl.translate.Translator;
+import org.springframework.stereotype.Component;
+
+import javax.imageio.ImageIO;
+import javax.imageio.stream.ImageOutputStream;
+import java.awt.*;
+import java.awt.image.BufferedImage;
+import java.io.*;
+import java.util.ArrayList;
+import java.util.List;
+
+@Component
+public class HerbUtil {
+
+ //瑙勫畾杈撳叆灏哄
+ private static final int INPUT_SIZE = 224;
+
+ private static final int TARGET_SIZE = 256;
+
+ //鏍囩鏂囦欢 涓�绉嶇被鍒悕瀛楀崰涓�琛�
+ private List<String> herbNames;
+
+ //鐢ㄤ簬璇嗗埆
+ Predictor<Image, Classifications> predictor;
+
+ //妯″瀷
+ private Model model;
+
+ public HerbUtil() {
+ //鍔犺浇鏍囩鍒癶erbNames涓�
+ this.loadHerbNames();
+ //鍒濆鍖栨ā鍨嬪伐浣�
+ this.init();
+
+
+
+ }
+
+ public List<Classifications.Classification> predict(InputStream inputStream) {
+ List<Classifications.Classification> result = new ArrayList<>();
+ Image input = this.resizeImage(inputStream);
+ try {
+ Classifications output = predictor.predict(input);
+ System.out.println("鎺ㄦ祴涓猴細" + output.best().getClassName()
+ + ", 姒傜巼锛�" + output.best().getProbability());
+ System.out.println(output);
+ result = output.topK();
+ } catch (Exception e) {
+ e.printStackTrace();
+ }
+ return result;
+ }
+
+ private void loadHerbNames() {
+ BufferedReader reader = null;
+ herbNames = new ArrayList<>();
+ try {
+ InputStream in = HerbUtil.class.getClassLoader().getResourceAsStream("class.txt");
+ reader = new BufferedReader(new InputStreamReader(in));
+ String name = null;
+ while ((name = reader.readLine()) != null) {
+ herbNames.add(name);
+ }
+ System.out.println(herbNames);
+ } catch (Exception e) {
+ e.printStackTrace();
+ } finally {
+ if (reader != null) {
+ try {
+ reader.close();
+ } catch (IOException e) {
+ e.printStackTrace();
+ }
+ }
+ }
+ }
+
+ private void init() {
+ Translator<Image, Classifications> translator = ImageClassificationTranslator.builder()
+ //涓嬮潰鐨則ransform鏍规嵁鑷繁鐨勬敼
+ .addTransform(new CenterCrop(INPUT_SIZE,INPUT_SIZE))
+
+ .addTransform(new ToTensor())
+ .addTransform(new Normalize(
+ new float[] {0.485f, 0.456f, 0.406f},
+ new float[] {0.229f, 0.224f, 0.225f}))
+
+ //杞藉叆鎵�鏈夋爣绛捐繘鍘�
+ .optSynset(herbNames)
+ //鏈�缁堟樉绀烘鐜囨渶楂樼殑5涓�
+ .optTopK(5)
+ .build();
+ //闅忎究璧峰悕
+ Model model = Model.newInstance("model", Device.cpu());
+ try {
+ InputStream inputStream = HerbUtil.class.getClassLoader().getResourceAsStream("model1.pt");
+ if (inputStream == null) {
+ throw new RuntimeException("鎵句笉鍒版ā鍨嬫枃浠�");
+ }
+ model.load(inputStream);
+
+ predictor = model.newPredictor(translator);
+ } catch (Exception e) {
+ e.printStackTrace();
+ }
+ }
+
+ private Image resizeImage(InputStream inputStream) {
+ BufferedImage input = null;
+ try {
+ input = ImageIO.read(inputStream);
+ } catch (IOException e) {
+ e.printStackTrace();
+ }
+ int iw = input.getWidth(), ih = input.getHeight();
+ int w = 256, h = 256;
+ double scale = Math.max(1. * w / iw, 1. * h / ih);
+ int nw = (int) (iw * scale), nh = (int) (ih * scale);
+ java.awt.Image img;
+ //鍙湁澶暱鎴栧お瀹芥墠浼氫繚鐣欐í绾垫瘮锛屽～鍏呴鑹�
+ // boolean needResize = 1. * iw / ih > 1.4 || 1. * ih / iw > 1.4;
+ // if (needResize) {
+ img = input.getScaledInstance(nw, nh, BufferedImage.SCALE_SMOOTH);
+ // } else {
+ // img = input.getScaledInstance(INPUT_SIZE, INPUT_SIZE, BufferedImage.SCALE_SMOOTH);
+ // }
+ BufferedImage out = new BufferedImage(nw, nh, BufferedImage.TYPE_INT_RGB);
+ Graphics g = out.getGraphics();
+ //鍏堝皢鏁翠釜224*224鍖哄煙濉厖128 128 128棰滆壊
+ g.setColor(new Color(255, 255, 255));
+ g.fillRect(0, 0, nw, nh);
+ out.getGraphics().drawImage(img, 0, 0, null);
+ ByteArrayOutputStream outputStream = new ByteArrayOutputStream();
+ try {
+ ImageOutputStream imageOutputStream = ImageIO.createImageOutputStream(outputStream);
+ ImageIO.write(out, "jpg", imageOutputStream);
+ //鍘籇鐩樼湅鏁堟灉
+ ImageIO.write(out, "jpg", new File("E:\\out.jpg"));
+ InputStream is = new ByteArrayInputStream(outputStream.toByteArray());
+ return ImageFactory.getInstance().fromInputStream(is);
+ } catch (IOException e) {
+ e.printStackTrace();
+ throw new RuntimeException("鍥剧墖杞崲澶辫触");
+ }
+ }
+}
\ No newline at end of file
diff --git a/jeecg-module-dry/jeecg-module-dry-biz/src/main/java/org/jeecg/modules/dry/controller/DryRealTimeDataController.java b/jeecg-module-dry/jeecg-module-dry-biz/src/main/java/org/jeecg/modules/dry/controller/DryRealTimeDataController.java
index 46ee064..a6dbf31 100644
--- a/jeecg-module-dry/jeecg-module-dry-biz/src/main/java/org/jeecg/modules/dry/controller/DryRealTimeDataController.java
+++ b/jeecg-module-dry/jeecg-module-dry-biz/src/main/java/org/jeecg/modules/dry/controller/DryRealTimeDataController.java
@@ -1,6 +1,7 @@
package org.jeecg.modules.dry.controller;
+import ai.djl.modality.Classifications;
import io.swagger.annotations.Api;
import io.swagger.annotations.ApiOperation;
import lombok.extern.slf4j.Slf4j;
@@ -8,11 +9,16 @@
import org.jeecg.modules.dry.service.*;
+import org.jeecg.modules.dry.util.HerbUtil;
import org.jeecg.modules.dry.vo.CommandMessageVo;
import org.jeecg.modules.dry.vo.RealTimeDataVo;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.web.bind.annotation.*;
+import org.springframework.web.multipart.MultipartFile;
+
+import java.io.InputStream;
+import java.util.List;
@Api(tags = "瀹炴椂鏁版嵁澶勭悊鎺у埗鍣�")
@@ -23,6 +29,9 @@
@Autowired
private IDryRealTimeDataService dryRealTimeDataService;
+
+ @Autowired
+ private HerbUtil herbUtil;
@ApiOperation(value="娴嬭瘯", notes="杩斿洖Hello")
@@ -66,4 +75,22 @@
public Result<?> sendCommand(@RequestBody CommandMessageVo msgVo) {
return dryRealTimeDataService.sendSocketMsg(msgVo);
}
+
+
+ @ApiOperation(value = "鑽潗璇嗗埆")
+ @PostMapping("/identify")
+ public Result<?> identify(@RequestParam("file") MultipartFile file) throws Exception {
+ try {
+ if (file.isEmpty()) {
+ throw new RuntimeException("涓婁紶鏂囦欢涓嶈兘涓虹┖");
+ }
+ InputStream inputStream = file.getInputStream();
+ List<Classifications.Classification> predict = herbUtil.predict(inputStream);
+ return Result.ok(predict);
+ } catch (Exception e) {
+ e.printStackTrace();
+ return Result.error("AI璇嗗埆鏈嶅姟寮傚父");
+ }
+ }
+
}
diff --git a/jeecg-module-dry/jeecg-module-dry-start/src/main/resources/class.txt b/jeecg-module-dry/jeecg-module-dry-start/src/main/resources/class.txt
new file mode 100644
index 0000000..6a15e51
--- /dev/null
+++ b/jeecg-module-dry/jeecg-module-dry-start/src/main/resources/class.txt
@@ -0,0 +1,20 @@
+baihe
+baihuasheshecao
+danggui
+dangshen
+fangfeng
+gancao
+gouqi
+huaihua
+huangqi
+jinyinhua
+juhua
+machixian
+mohanlian
+nuodaogen
+sangbaipi
+sangzhipian
+shudihuang
+yinyanghuo
+zaojiaoci
+zisugeng
diff --git a/jeecg-module-dry/jeecg-module-dry-start/src/main/resources/model.pt b/jeecg-module-dry/jeecg-module-dry-start/src/main/resources/model.pt
new file mode 100644
index 0000000..cd39814
--- /dev/null
+++ b/jeecg-module-dry/jeecg-module-dry-start/src/main/resources/model.pt
Binary files differ
diff --git a/jeecg-module-dry/jeecg-module-dry-start/src/main/resources/model1.pt b/jeecg-module-dry/jeecg-module-dry-start/src/main/resources/model1.pt
new file mode 100644
index 0000000..dfca629
--- /dev/null
+++ b/jeecg-module-dry/jeecg-module-dry-start/src/main/resources/model1.pt
Binary files differ
--
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