src/main/java/com/kamco/cd/training/postgres/core/ModelTestMetricsJobCoreService.java

@@ -1,6 +1,7 @@
 package com.kamco.cd.training.postgres.core;
 
 import com.kamco.cd.training.postgres.repository.train.ModelTestMetricsJobRepository;
+import com.kamco.cd.training.train.dto.ModelTrainMetricsDto.ResponsePathDto;
 import java.util.List;
 import lombok.RequiredArgsConstructor;
 import org.springframework.stereotype.Service;
@@ -18,7 +19,7 @@ public class ModelTestMetricsJobCoreService {
   }
 
   // Test 로직 시작
-  public List<Long> getTestMetricSaveNotYetModelIds() {
+  public List<ResponsePathDto> getTestMetricSaveNotYetModelIds() {
     return modelTestMetricsJobRepository.getTestMetricSaveNotYetModelIds();
   }
 

src/main/java/com/kamco/cd/training/postgres/core/ModelTrainMetricsJobCoreService.java

@@ -1,6 +1,7 @@
 package com.kamco.cd.training.postgres.core;
 
 import com.kamco.cd.training.postgres.repository.train.ModelTrainMetricsJobRepository;
+import com.kamco.cd.training.train.dto.ModelTrainMetricsDto.ResponsePathDto;
 import java.util.List;
 import lombok.RequiredArgsConstructor;
 import org.springframework.stereotype.Service;
@@ -12,7 +13,7 @@ public class ModelTrainMetricsJobCoreService {
 
   private final ModelTrainMetricsJobRepository modelTrainMetricsJobRepository;
 
-  public List<Long> getTrainMetricSaveNotYetModelIds() {
+  public List<ResponsePathDto> getTrainMetricSaveNotYetModelIds() {
     return modelTrainMetricsJobRepository.getTrainMetricSaveNotYetModelIds();
   }
 

src/main/java/com/kamco/cd/training/postgres/repository/train/ModelTestMetricsJobRepositoryCustom.java

@@ -1,12 +1,13 @@
 package com.kamco.cd.training.postgres.repository.train;
 
+import com.kamco.cd.training.train.dto.ModelTrainMetricsDto.ResponsePathDto;
 import java.util.List;
 
 public interface ModelTestMetricsJobRepositoryCustom {
 
   void updateModelMetricsTrainSaveYn(Long modelId, String stepNo);
 
-  List<Long> getTestMetricSaveNotYetModelIds();
+  List<ResponsePathDto> getTestMetricSaveNotYetModelIds();
 
   void insertModelMetricsTest(List<Object[]> batchArgs);
 }

src/main/java/com/kamco/cd/training/postgres/repository/train/ModelTestMetricsJobRepositoryImpl.java

@@ -4,6 +4,8 @@ import static com.kamco.cd.training.postgres.entity.QModelMasterEntity.modelMast
 
 import com.kamco.cd.training.common.enums.TrainStatusType;
 import com.kamco.cd.training.postgres.entity.ModelMetricsTestEntity;
+import com.kamco.cd.training.train.dto.ModelTrainMetricsDto.ResponsePathDto;
+import com.querydsl.core.types.Projections;
 import com.querydsl.jpa.impl.JPAQueryFactory;
 import java.util.List;
 import org.springframework.data.jpa.repository.support.QuerydslRepositorySupport;
@@ -36,9 +38,11 @@ public class ModelTestMetricsJobRepositoryImpl extends QuerydslRepositorySupport
   }
 
   @Override
-  public List<Long> getTestMetricSaveNotYetModelIds() {
+  public List<ResponsePathDto> getTestMetricSaveNotYetModelIds() {
     return queryFactory
-        .select(modelMasterEntity.id)
+        .select(
+            Projections.constructor(
+                ResponsePathDto.class, modelMasterEntity.id, modelMasterEntity.responsePath))
         .from(modelMasterEntity)
         .where(
             modelMasterEntity.step2EndDttm.isNotNull(),

src/main/java/com/kamco/cd/training/postgres/repository/train/ModelTrainMetricsJobRepositoryCustom.java

@@ -1,10 +1,11 @@
 package com.kamco.cd.training.postgres.repository.train;
 
+import com.kamco.cd.training.train.dto.ModelTrainMetricsDto.ResponsePathDto;
 import java.util.List;
 
 public interface ModelTrainMetricsJobRepositoryCustom {
 
-  List<Long> getTrainMetricSaveNotYetModelIds();
+  List<ResponsePathDto> getTrainMetricSaveNotYetModelIds();
 
   void insertModelMetricsTrain(List<Object[]> batchArgs);
 

src/main/java/com/kamco/cd/training/postgres/repository/train/ModelTrainMetricsJobRepositoryImpl.java

@@ -4,6 +4,8 @@ import static com.kamco.cd.training.postgres.entity.QModelMasterEntity.modelMast
 
 import com.kamco.cd.training.common.enums.TrainStatusType;
 import com.kamco.cd.training.postgres.entity.ModelMetricsTrainEntity;
+import com.kamco.cd.training.train.dto.ModelTrainMetricsDto.ResponsePathDto;
+import com.querydsl.core.types.Projections;
 import com.querydsl.jpa.impl.JPAQueryFactory;
 import java.util.List;
 import org.springframework.data.jpa.repository.support.QuerydslRepositorySupport;
@@ -23,9 +25,11 @@ public class ModelTrainMetricsJobRepositoryImpl extends QuerydslRepositorySuppor
   }
 
   @Override
-  public List<Long> getTrainMetricSaveNotYetModelIds() {
+  public List<ResponsePathDto> getTrainMetricSaveNotYetModelIds() {
     return queryFactory
-        .select(modelMasterEntity.id)
+        .select(
+            Projections.constructor(
+                ResponsePathDto.class, modelMasterEntity.id, modelMasterEntity.responsePath))
         .from(modelMasterEntity)
         .where(
             modelMasterEntity.step1EndDttm.isNotNull(),
@@ -41,7 +45,7 @@ public class ModelTrainMetricsJobRepositoryImpl extends QuerydslRepositorySuppor
   public void insertModelMetricsTrain(List<Object[]> batchArgs) {
     String sql =
         """
-            insert into tb_model_matrics_train
+            insert into tb_model_metrics_train
             (model_id, epoch, iteration, loss, lr, duration_time)
             values (?, ?, ?, ?, ?, ?)
         """;
@@ -66,7 +70,7 @@ public class ModelTrainMetricsJobRepositoryImpl extends QuerydslRepositorySuppor
   public void insertModelMetricsValidation(List<Object[]> batchArgs) {
     String sql =
         """
-            insert into tb_model_matrics_validation
+            insert into tb_model_metrics_validation
             (model_id, epoch, a_acc, m_fscore, m_precision, m_recall, m_iou, m_acc, changed_fscore, changed_precision, changed_recall,
              unchanged_fscore, unchanged_precision, unchanged_recall
              )

src/main/java/com/kamco/cd/training/train/dto/ModelTrainMetricsDto.java

@@ -0,0 +1,21 @@
+package com.kamco.cd.training.train.dto;
+
+import io.swagger.v3.oas.annotations.media.Schema;
+import lombok.AllArgsConstructor;
+import lombok.Getter;
+import lombok.NoArgsConstructor;
+import lombok.Setter;
+
+public class ModelTrainMetricsDto {
+
+  @Schema(name = "ResponsePathDto", description = "AI 결과 저장된 path 경로 정보")
+  @Getter
+  @Setter
+  @NoArgsConstructor
+  @AllArgsConstructor
+  public static class ResponsePathDto {
+
+    private Long modelId;
+    private String responsePath;
+  }
+}

src/main/java/com/kamco/cd/training/train/service/ModelTestMetricsJobService.java

@@ -1,6 +1,7 @@
 package com.kamco.cd.training.train.service;
 
 import com.kamco.cd.training.postgres.core.ModelTestMetricsJobCoreService;
+import com.kamco.cd.training.train.dto.ModelTrainMetricsDto.ResponsePathDto;
 import java.io.BufferedReader;
 import java.io.IOException;
 import java.nio.charset.StandardCharsets;
@@ -35,66 +36,67 @@ public class ModelTestMetricsJobService {
     return "local".equalsIgnoreCase(profile);
   }
 
-  //  @Scheduled(cron = "0 0/10 * * * *")
+  //    @Scheduled(cron = "0 * * * * *")
   public void findTestValidMetricCsvFiles() {
-    if (isLocalProfile()) {
+    //    if (isLocalProfile()) {
-      return;
+    //      return;
-    }
+    //    }
 
-    List<Long> modelIds =
+    List<ResponsePathDto> modelIds =
-        modelTestMetricsJobCoreService
+        modelTestMetricsJobCoreService.getTestMetricSaveNotYetModelIds();
-            .getTestMetricSaveNotYetModelIds(); // TODO: uid, uuid ? 가져오기로 해야함
 
     if (modelIds.isEmpty()) {
       return;
     }
 
-    String localPath = "C:\\data\\upload\\test.csv";
+    for (ResponsePathDto modelInfo : modelIds) {
-    try (BufferedReader reader =
-        Files.newBufferedReader(Paths.get(localPath), StandardCharsets.UTF_8); ) {
 
-      log.info("### localPath={}", localPath);
+      String testPath = modelInfo.getResponsePath() + "/metrics/test.csv";
-      CSVParser parser = CSVFormat.DEFAULT.withFirstRecordAsHeader().parse(reader);
+      try (BufferedReader reader =
+          Files.newBufferedReader(Paths.get(testPath), StandardCharsets.UTF_8); ) {
 
-      List<Object[]> batchArgs = new ArrayList<>();
+        CSVParser parser = CSVFormat.DEFAULT.withFirstRecordAsHeader().parse(reader);
 
-      for (CSVRecord record : parser) {
+        List<Object[]> batchArgs = new ArrayList<>();
 
-        String model = record.get("model");
+        for (CSVRecord record : parser) {
-        long TP = Long.parseLong(record.get("TP"));
-        long FP = Long.parseLong(record.get("FP"));
-        long FN = Long.parseLong(record.get("FN"));
-        float precision = Float.parseFloat(record.get("precision"));
-        float recall = Float.parseFloat(record.get("recall"));
-        float f1_score = Float.parseFloat(record.get("f1_score"));
-        float accuracy = Float.parseFloat(record.get("accuracy"));
-        float iou = Float.parseFloat(record.get("iou"));
-        long detection_count = Long.parseLong(record.get("detection_count"));
-        long gt_count = Long.parseLong(record.get("gt_count"));
 
-        batchArgs.add(
+          String model = record.get("model");
-            new Object[] {
+          long TP = Long.parseLong(record.get("TP"));
-              modelIds.getFirst(),
+          long FP = Long.parseLong(record.get("FP"));
-              model,
+          long FN = Long.parseLong(record.get("FN"));
-              TP,
+          float precision = Float.parseFloat(record.get("precision"));
-              FP,
+          float recall = Float.parseFloat(record.get("recall"));
-              FN,
+          float f1_score = Float.parseFloat(record.get("f1_score"));
-              precision,
+          float accuracy = Float.parseFloat(record.get("accuracy"));
-              recall,
+          float iou = Float.parseFloat(record.get("iou"));
-              f1_score,
+          long detection_count = Long.parseLong(record.get("detection_count"));
-              accuracy,
+          long gt_count = Long.parseLong(record.get("gt_count"));
-              iou,
+
-              detection_count,
+          batchArgs.add(
-              gt_count
+              new Object[] {
-            });
+                modelInfo.getModelId(),
+                model,
+                TP,
+                FP,
+                FN,
+                precision,
+                recall,
+                f1_score,
+                accuracy,
+                iou,
+                detection_count,
+                gt_count
+              });
+        }
+
+        modelTestMetricsJobCoreService.insertModelMetricsTest(batchArgs);
+
+      } catch (IOException e) {
+        throw new RuntimeException(e);
       }
 
-      modelTestMetricsJobCoreService.insertModelMetricsTest(batchArgs);
+      modelTestMetricsJobCoreService.updateModelMetricsTrainSaveYn(modelInfo.getModelId(), "step2");
-
-    } catch (IOException e) {
-      throw new RuntimeException(e);
     }
-
-    modelTestMetricsJobCoreService.updateModelMetricsTrainSaveYn(modelIds.getFirst(), "step2");
   }
 }

src/main/java/com/kamco/cd/training/train/service/ModelTrainMetricsJobService.java

@@ -1,6 +1,7 @@
 package com.kamco.cd.training.train.service;
 
 import com.kamco.cd.training.postgres.core.ModelTrainMetricsJobCoreService;
+import com.kamco.cd.training.train.dto.ModelTrainMetricsDto.ResponsePathDto;
 import java.io.BufferedReader;
 import java.io.IOException;
 import java.nio.charset.StandardCharsets;
@@ -35,96 +36,97 @@ public class ModelTrainMetricsJobService {
     return "local".equalsIgnoreCase(profile);
   }
 
-  //    @Scheduled(cron = "0 0/10 * * * *")
+  // @Scheduled(cron = "0 * * * * *")
   public void findTrainValidMetricCsvFiles() {
-    if (isLocalProfile()) {
+    //    if (isLocalProfile()) {
-      return;
+    //      return;
-    }
+    //    }
 
-    List<Long> modelIds =
+    List<ResponsePathDto> modelIds =
-        modelTrainMetricsJobCoreService
+        modelTrainMetricsJobCoreService.getTrainMetricSaveNotYetModelIds();
-            .getTrainMetricSaveNotYetModelIds(); // TODO: uid, uuid ? 가져오기로 해야함
 
     if (modelIds.isEmpty()) {
       return;
     }
 
-    String localPath = "C:\\data\\upload\\train.csv";
+    for (ResponsePathDto modelInfo : modelIds) {
-    try (BufferedReader reader =
-        Files.newBufferedReader(Paths.get(localPath), StandardCharsets.UTF_8); ) {
 
-      log.info("### localPath={}", localPath);
+      String trainPath = modelInfo.getResponsePath() + "/metrics/train.csv";
-      CSVParser parser = CSVFormat.DEFAULT.withFirstRecordAsHeader().parse(reader);
+      try (BufferedReader reader =
+          Files.newBufferedReader(Paths.get(trainPath), StandardCharsets.UTF_8); ) {
 
-      List<Object[]> batchArgs = new ArrayList<>();
+        CSVParser parser = CSVFormat.DEFAULT.withFirstRecordAsHeader().parse(reader);
 
-      for (CSVRecord record : parser) {
+        List<Object[]> batchArgs = new ArrayList<>();
 
-        int epoch = Integer.parseInt(record.get("Epoch"));
+        for (CSVRecord record : parser) {
-        long iteration = Long.parseLong(record.get("Iteration"));
-        double Loss = Double.parseDouble(record.get("Loss"));
-        double LR = Double.parseDouble(record.get("LR"));
-        float time = Float.parseFloat(record.get("Time"));
 
-        batchArgs.add(new Object[] {modelIds.getFirst(), epoch, iteration, Loss, LR, time});
+          int epoch = Integer.parseInt(record.get("Epoch")) + 1; // TODO : 나중에 AI 개발 완료되면 -1 하기
+          long iteration = Long.parseLong(record.get("Iteration"));
+          double Loss = Double.parseDouble(record.get("Loss"));
+          double LR = Double.parseDouble(record.get("LR"));
+          float time = Float.parseFloat(record.get("Time"));
+
+          batchArgs.add(new Object[] {modelInfo.getModelId(), epoch, iteration, Loss, LR, time});
+        }
+
+        modelTrainMetricsJobCoreService.insertModelMetricsTrain(batchArgs);
+
+      } catch (IOException e) {
+        throw new RuntimeException(e);
       }
 
-      modelTrainMetricsJobCoreService.insertModelMetricsTrain(batchArgs);
+      String validationPath = modelInfo.getResponsePath() + "/metrics/val.csv";
+      try (BufferedReader reader =
+          Files.newBufferedReader(Paths.get(validationPath), StandardCharsets.UTF_8); ) {
 
-    } catch (IOException e) {
+        CSVParser parser = CSVFormat.DEFAULT.withFirstRecordAsHeader().parse(reader);
-      throw new RuntimeException(e);
-    }
 
-    String validationPath = "C:\\data\\upload\\val.csv";
+        List<Object[]> batchArgs = new ArrayList<>();
-    try (BufferedReader reader =
-        Files.newBufferedReader(Paths.get(validationPath), StandardCharsets.UTF_8); ) {
 
-      log.info("### validationPath={}", validationPath);
+        for (CSVRecord record : parser) {
-      CSVParser parser = CSVFormat.DEFAULT.withFirstRecordAsHeader().parse(reader);
 
-      List<Object[]> batchArgs = new ArrayList<>();
+          int epoch = Integer.parseInt(record.get("Epoch"));
+          float aAcc = Float.parseFloat(record.get("aAcc"));
+          float mFscore = Float.parseFloat(record.get("mFscore"));
+          float mPrecision = Float.parseFloat(record.get("mPrecision"));
+          float mRecall = Float.parseFloat(record.get("mRecall"));
+          float mIoU = Float.parseFloat(record.get("mIoU"));
+          float mAcc = Float.parseFloat(record.get("mAcc"));
+          float changed_fscore = Float.parseFloat(record.get("changed_fscore"));
+          float changed_precision = Float.parseFloat(record.get("changed_precision"));
+          float changed_recall = Float.parseFloat(record.get("changed_recall"));
+          float unchanged_fscore = Float.parseFloat(record.get("unchanged_fscore"));
+          float unchanged_precision = Float.parseFloat(record.get("unchanged_precision"));
+          float unchanged_recall = Float.parseFloat(record.get("unchanged_recall"));
 
-      for (CSVRecord record : parser) {
+          batchArgs.add(
+              new Object[] {
+                modelInfo.getModelId(),
+                epoch,
+                aAcc,
+                mFscore,
+                mPrecision,
+                mRecall,
+                mIoU,
+                mAcc,
+                changed_fscore,
+                changed_precision,
+                changed_recall,
+                unchanged_fscore,
+                unchanged_precision,
+                unchanged_recall
+              });
+        }
 
-        int epoch = Integer.parseInt(record.get("Epoch"));
+        modelTrainMetricsJobCoreService.insertModelMetricsValidation(batchArgs);
-        float aAcc = Float.parseFloat(record.get("aAcc"));
-        float mFscore = Float.parseFloat(record.get("mFscore"));
-        float mPrecision = Float.parseFloat(record.get("mPrecision"));
-        float mRecall = Float.parseFloat(record.get("mRecall"));
-        float mIoU = Float.parseFloat(record.get("mIoU"));
-        float mAcc = Float.parseFloat(record.get("mAcc"));
-        float changed_fscore = Float.parseFloat(record.get("changed_fscore"));
-        float changed_precision = Float.parseFloat(record.get("changed_precision"));
-        float changed_recall = Float.parseFloat(record.get("changed_recall"));
-        float unchanged_fscore = Float.parseFloat(record.get("unchanged_fscore"));
-        float unchanged_precision = Float.parseFloat(record.get("unchanged_precision"));
-        float unchanged_recall = Float.parseFloat(record.get("unchanged_recall"));
 
-        batchArgs.add(
+      } catch (IOException e) {
-            new Object[] {
+        throw new RuntimeException(e);
-              modelIds.getFirst(),
-              epoch,
-              aAcc,
-              mFscore,
-              mPrecision,
-              mRecall,
-              mIoU,
-              mAcc,
-              changed_fscore,
-              changed_precision,
-              changed_recall,
-              unchanged_fscore,
-              unchanged_precision,
-              unchanged_recall
-            });
       }
 
-      modelTrainMetricsJobCoreService.insertModelMetricsValidation(batchArgs);
+      modelTrainMetricsJobCoreService.updateModelMetricsTrainSaveYn(
-
+          modelInfo.getModelId(), "step1");
-    } catch (IOException e) {
-      throw new RuntimeException(e);
     }
-
-    modelTrainMetricsJobCoreService.updateModelMetricsTrainSaveYn(modelIds.getFirst(), "step1");
   }
 }