修改为100个点为标志

拍照位置修改

.gitignore

@@ -31,3 +31,7 @@ build/
 
 ### VS Code ###
 .vscode/
+
+log/
+logs/
+*.onnx

src/main/java/com/example/lxcameraapi/controller/CategoryController.java

@@ -12,8 +12,14 @@ import org.springframework.web.bind.annotation.RestController;
 
 import javax.annotation.Resource;
 import java.io.IOException;
+import java.time.LocalDate;
+import java.time.LocalDateTime;
+import java.time.format.DateTimeFormatter;
 import java.util.*;
 
+import static com.example.lxcameraapi.controller.HikController.DATE_FORMATTER;
+import static com.example.lxcameraapi.controller.HikController.TIME_FORMATTER;
+
 @RestController
 @RequestMapping("/category")
 public class CategoryController {
@@ -45,6 +51,10 @@ public class CategoryController {
 
     @GetMapping("/getBoxCountByCategory")
     public int getBoxCountByCategory(String streetId,String category) throws IOException {
+
+        String path =streetId+"\\"
+                + LocalDate.now().format(DATE_FORMATTER)
+                +"\\"+category+"_"+ LocalDateTime.now().format(TIME_FORMATTER) +"_";
         List<AppConfig.Camera> cameras = appConfig.getLxCamera();
         int i = 0;
         Map<Integer, String> map = new HashMap();
@@ -58,9 +68,9 @@ public class CategoryController {
                 for (AppConfig.Camera c : cameras) {
                     if (Objects.equals(c.getId(), cameraId)) {
                         String sn = UUID.randomUUID().toString();
-                        LxPointCloudSaveImage.saveImage(c.getIp(), "D:\\data\\" + sn + ".pcd");
+                        LxPointCloudSaveImage.saveImage(c.getIp(), path+ sn + ".pcd");
                         PcdPojo pojo = new PcdPojo();
-                        pojo.setPcd1("D:\\data\\" + sn + ".pcd");
+                        pojo.setPcd1(path + sn + ".pcd");
                         pojo.setConfigPath(c.getConvertConfPath());
                         try {
                             pojo.setPCDInfo(pojo);
@@ -77,9 +87,9 @@ public class CategoryController {
             for (AppConfig.Camera c : cameras) {
                 if (streetId.equals(c.getStreetId())) {
                     String sn = UUID.randomUUID().toString();
-                    LxPointCloudSaveImage.saveImage(c.getIp(), "D:\\data\\" + sn + ".pcd");
+                    LxPointCloudSaveImage.saveImage(c.getIp(), path + sn + ".pcd");
                     PcdPojo pojo = new PcdPojo();
-                    pojo.setPcd1("D:\\data\\" + sn + ".pcd");
+                    pojo.setPcd1(path + sn + ".pcd");
                     pojo.setConfigPath(c.getConvertConfPath());
                     try {
                         pojo.setPCDInfo(pojo);
@@ -95,4 +105,5 @@ public class CategoryController {
 
         return i;
     }
+
 }

src/main/java/com/example/lxcameraapi/controller/HikController.java

@@ -48,7 +48,7 @@ public class HikController {
     }
 
     // 标定
-    @GetMapping("/calibration")
+    @GetMapping("/calibrationOpencv")
     @ResponseBody
     public String calibration(int direction) throws IOException {
        // System.load(new File(System.getProperty("user.dir")+"\\libs\\opencv\\opencv_java480.dll").getAbsolutePath());
@@ -182,8 +182,8 @@ public class HikController {
         return pojo;
     }
 
-    private static final DateTimeFormatter DATE_FORMATTER = DateTimeFormatter.ofPattern("yyyy-MM-dd");
+    public static final DateTimeFormatter DATE_FORMATTER = DateTimeFormatter.ofPattern("yyyy-MM-dd");
-    private static final DateTimeFormatter TIME_FORMATTER = DateTimeFormatter.ofPattern("HHmmssSSS");
+    public static final DateTimeFormatter TIME_FORMATTER = DateTimeFormatter.ofPattern("HHmmssSSS");
 
     @Resource
     ONNXServiceNew onnxServiceNew;
@@ -221,7 +221,7 @@ public class HikController {
         return pojo;
     }
     // 识别
-    @GetMapping("/distinguishOnnx")
+    @GetMapping("/distinguish")
     @ResponseBody
     public Pojo distinguishOnnx(String streetNumber,int direction, String category) throws IOException {
         String picPath =  appConfig.getPicPath();

src/main/java/com/example/lxcameraapi/service/IndustrialCamera/algorithm/ONNXServiceNew.java

@@ -50,14 +50,14 @@ public class ONNXServiceNew {
 
         System.load(new File(System.getProperty("user.dir")+"\\libs\\opencv\\opencv_java480.dll").getAbsolutePath());
         ortMap.put("a", new AppConfig.YoloModelConfig());
-        ortMap.get("a").setImageSize(2048);
+        ortMap.get("a").setImageSize(1024);
         ortMap.get("a").setConfThreshold(0.5f);
-        ortMap.get("a").setNames(new String[]{"0"});
+        ortMap.get("a").setNames(new String[]{"0143","0153","0173","0177","0191","0253","0256","0266","0268","0286","0302","0304","0305","0307","0320","0326","0336","0339","0343","0352","0458","0461","0462","0473","0477","0486","0490","0492","0930","1101","1102","1104","1262","1269","1302","1308","1359","1366","1622","1625","1919","1976","20","2165","2188","2210","2224","2445","2476","2611","2730","2731","2910","2914","2943","3027","3028","3029","3212","3226","3344","3501","3509","3538","3725","3741","3751","3754","3763","3766","3808"});
 
-        int imageSize = 2048;
+        int imageSize = 1024;
-        String imagePath = "D:\\data\\1776157002220.png";
+        String imagePath = "D:\\PycharmProjects\\yolo\\puer\\train\\2210\\aug_5_1_ed7e63af-f9f5-4c49-baee-12f635aa7b5c.jpg.jpg";
 
-        String modelPath = "D:\\data\\best.onnx";
+        String modelPath = "D:\\PycharmProjects\\yolo\\runs\\classify\\train14\\weights\\best.onnx";
 //        List<String> name = Arrays.asList("0143", "0153", "0173", "0177", "0191", "0253", "0256", "0266", "0268", "0286", "0302", "0304", "0305", "0307", "0320", "0326", "0336", "0339", "0343", "0352", "0458", "0461", "0462", "0473", "0477", "0486", "0490", "0492", "0930", "1101", "1102", "1104", "1262", "1269", "1302", "1308", "1359", "1366", "1622", "1625", "1919", "1976", "20", "2165", "2188", "2210", "2224", "2445", "2476", "2611", "2730", "2731", "2910", "2914", "2943", "3027", "3028", "3029", "3212", "3226", "3344", "3501", "3509", "3538", "3725", "3741", "3751", "3754", "3763", "3766", "3808");
 
         OrtSession.SessionOptions sessionOptions = null;
@@ -72,7 +72,7 @@ public class ONNXServiceNew {
             sessionOptions = new OrtSession.SessionOptions();
             session = environment.createSession(modelPath, sessionOptions);
             ortSessions.put("a", session);
-            List<BoundingBox> boxes = onnxServiceNew.detect(imagePath, "a");
+            ClassifyEntity  classifyEntity = onnxServiceNew.classifyOnee(imagePath, "a");
 
 //            classifyEntity.setIndex(predictedClassId);
 //            classifyEntity.setName(config.getNames()[predictedClassId]);
@@ -84,7 +84,7 @@ public class ONNXServiceNew {
 
 //            DrawBoundingBox.drawBoundingBoxesOnImage(imagePath, "D:\\data\\2024-04-24_08-55-42-492data.BMP.jpg", filteredDetections);
 
-            System.out.println(boxes);
+            System.out.println(classifyEntity);
 //            System.out.println(name.get(predictedClassId));
         } catch (OrtException e) {
             throw new RuntimeException(e);
@@ -481,7 +481,9 @@ public class ONNXServiceNew {
             float[] outputData;
             if (output instanceof float[][][]) {
                 // 三维数组 float[][][]
-                outputData = ((float[][][]) output)[0];
+                // 三维数组 float[][][]，取最后维度的 [0] 得到一维
+                float[][][] arr3d = (float[][][]) output;
+                outputData = arr3d[arr3d.length - 1][0];
             } else if (output instanceof float[][]) {
                 // 二维数组 float[][]
                 outputData = ((float[][]) output)[0];
@@ -556,13 +558,14 @@ public class ONNXServiceNew {
             Object output = result.get(0).getValue();
             float[] outputData;
             if (output instanceof float[][][]) {
-                // 三维数组 float[][][]
+                // 三维数组 float[][][]，取最后维度的 [0] 得到一维
-                outputData = ((float[][][]) output)[0];
+                float[][][] arr3d = (float[][][]) output;
+                outputData = arr3d[arr3d.length - 1][0];
             } else if (output instanceof float[][]) {
-                // 二维数组 float[][]
+                // 二维数组 float[][]，取 [0] 得到一维
                 outputData = ((float[][]) output)[0];
             } else if (output instanceof float[]) {
-                // 一维数组 float[]
+                // 一维数组 float[]，直接使用
                 outputData = (float[]) output;
             } else {
                 throw new RuntimeException("Unexpected output type: " + output.getClass().getName());
@@ -597,6 +600,85 @@ public class ONNXServiceNew {
         }
     }
 
+
+    /**
+     * yolo11计算图片最佳的模版
+     *
+     * @param imagePath 输入的图片位置
+     * @return
+     * @throws OrtException
+     */
+    public ClassifyEntity classifyOnee(String imagePath, String type) throws OrtException {
+
+        OrtSession session = getSession(type);
+        AppConfig.YoloModelConfig config = getConfig(type);
+        // 处理图像
+        float[] imageData = new float[0];
+        try {
+            imageData = processImageFromURL(imagePath, config.getImageSize());
+        } catch (IOException ex) {
+            throw new RuntimeException(ex);
+        }
+
+        // 构建输入张量
+        long[] shape = new long[]{1, 3, config.getImageSize(), config.getImageSize()};  // batch_size, channels, height, width
+        OnnxTensor inputTensor = null;
+        OrtSession.Result result = null;
+        try {
+            inputTensor = OnnxTensor.createTensor(environment, FloatBuffer.wrap(imageData), shape);
+
+            HashMap<String, OnnxTensor> stringOnnxTensorHashMap = new HashMap<>();
+            stringOnnxTensorHashMap.put(session.getInputInfo().keySet().iterator().next(), inputTensor);
+
+            // 执行推理
+            result = session.run(stringOnnxTensorHashMap);
+            // 获取第一个输出（大多数情况下只有一个输出）
+            // 动态判断输出形状，避免 ClassCastException
+            Object output = result.get(0).getValue();
+            float[] outputData;
+            if (output instanceof float[][][]) {
+                // 三维数组 float[][][]，取最后维度的 [0] 得到一维
+                float[][][] arr3d = (float[][][]) output;
+                outputData = arr3d[arr3d.length - 1][0];
+            } else if (output instanceof float[][]) {
+                // 二维数组 float[][]，取 [0] 得到一维
+                outputData = ((float[][]) output)[0];
+            } else if (output instanceof float[]) {
+                // 一维数组 float[]，直接使用
+                outputData = (float[]) output;
+            } else {
+                throw new RuntimeException("Unexpected output type: " + output.getClass().getName());
+            }
+
+            // 获取最大概率对应的类别 ID
+            int predictedClassId = argmax(outputData, 0.8);
+            ClassifyEntity classifyEntity = new ClassifyEntity();
+            classifyEntity.setIndex(predictedClassId);
+            if (predictedClassId!=-1){
+                log.info("识别模版：{}",config.getNames()[predictedClassId]);
+                classifyEntity.setName(config.getNames()[predictedClassId]);
+                classifyEntity.setConfidence(outputData[predictedClassId]);
+            }else {
+                log.info("未识别模版");
+            }
+            //            classifyEntity.setClassProb(String.format("%.4f", outputData[i]));
+
+
+            //            float[] output = (float[]) result.get(0).getValue();
+
+            //            DrawBoundingBox.drawBoundingBoxesOnImage(imagePath, "D:\\data\\2024-04-24_08-55-42-492data.BMP.jpg", filteredDetections);
+
+            return classifyEntity;
+        } finally {
+            if (inputTensor != null) {
+                inputTensor.close();
+            }
+            if (result != null) {
+                result.close();
+            }
+        }
+    }
+
     /**
      * yolo11计算图片有多少个识别到的模版
      *

src/main/java/com/example/lxcameraapi/service/IndustrialCamera/algorithm/PointCloudProcessor.java

@@ -432,21 +432,21 @@ public class PointCloudProcessor {
 
     public static void main(String[] args) {
        // LxPointCloudSaveImage.saveImage("192.168.1.82", "E:\\1.pcd", 1);
+        PointCloudProcessor slicing = new PointCloudProcessor();
 
         System.load(new File(System.getProperty("user.dir")+"\\libs\\opencv\\opencv_java480.dll").getAbsolutePath());
         PcdPojo pojo = new PcdPojo();
-        pojo.setPcd1("E:\\1\\1ij.pcd");
+        pojo.setPcd1("D:\\xwechat_files\\wxid_ttkf0xgmyihv22_2388\\msg\\file\\2026-04\\2巷道\\F83C51127695\\15_14_46_241_camera2.pcd");
-        pojo.setConfigPath("E:\\工作\\淮阴\\pz6.json");
+        pojo.setConfigPath("D:\\xwechat_files\\wxid_ttkf0xgmyihv22_2388\\msg\\file\\2026-04\\2巷道\\F83C51127695\\cj.json");
+        String pz = "D:\\xwechat_files\\wxid_ttkf0xgmyihv22_2388\\msg\\file\\2026-04\\2巷道\\F83C51127695\\pz.json";
+
         try {
             pojo.setPCDInfo(pojo);
         } catch (IOException e) {
             throw new RuntimeException(e);
         }
-        try {
+        System.out.println(slicing.slicing(pojo, slicing.getBoxPositionConf(pz)));
-            saveImage(pojo, "E:\\工作\\淮阴\\03bcfe74-2b4b-41e5-a9f1-09d60090f01b.png");
+        ;
-        } catch (Exception e) {
-            throw new RuntimeException(e);
-        }
     }
 
     /**
@@ -647,7 +647,7 @@ public class PointCloudProcessor {
             for (int j = 0; j < boxPositionConfs.get(i).getPosition().size(); j++) {
 
                 int position = j + 1 + (i) * boxPositionConfs.get(i).getPosition().size();
-                if (map.getOrDefault(position, 0) > 200) {
+                if (map.getOrDefault(position, 0) > 100) {
                     count += 1;
                 }
             }