feat : 생성형 이미지 생성을 위한 정보 csv 파일로 저장 및 포스터 변경

backend/src/main/java/org/capstone2024/onlyu/controller/FlaskController.java

@@ -30,7 +30,7 @@ public FlaskController(FlaskService flaskService){
     @RequestMapping(value = "/start", method = RequestMethod.POST)
     public PredictResult start(@RequestPart("data") StartDto startDto,
             @RequestPart("file") MultipartFile image){
-        Map<String, Object> predict_color_res = flaskService.predict_color_flask(image);
+        Map<String, Object> predict_color_res = flaskService.predict_color_flask(image, startDto);
         Map<String, Object> predict_shape_res = flaskService.predict_shape_flask();
 
         PredictResult predict_result = new PredictResult();

backend/src/main/java/org/capstone2024/onlyu/dto/StartDto.java

@@ -9,4 +9,5 @@
 public class StartDto {
     String email;
     String gender;
+    Boolean gan_permission = false;
 }

backend/src/main/java/org/capstone2024/onlyu/service/FlaskService.java

@@ -1,7 +1,10 @@
 package org.capstone2024.onlyu.service;
 
+import com.fasterxml.jackson.core.JsonProcessingException;
+import com.fasterxml.jackson.databind.ObjectMapper;
 import lombok.RequiredArgsConstructor;
 import lombok.extern.slf4j.Slf4j;
+import org.capstone2024.onlyu.dto.StartDto;
 import org.springframework.http.HttpEntity;
 import org.springframework.http.HttpHeaders;
 import org.springframework.http.MediaType;
@@ -22,14 +25,23 @@
 public class FlaskService {
 
     @Transactional
-    public Map<String, Object> predict_color_flask(MultipartFile image){
+    public Map<String, Object> predict_color_flask(MultipartFile image, StartDto startDto){
         RestTemplate restTemplate = new RestTemplate();
         HttpHeaders headers = new HttpHeaders();
         headers.setContentType(MediaType.MULTIPART_FORM_DATA);
         String url = "http://127.0.0.1:5050/predict_color";
 
         MultiValueMap<String, Object> body = new LinkedMultiValueMap<>();
         body.add("image", image.getResource());
+
+        ObjectMapper objectMapper = new ObjectMapper();
+        String startDtoJson;
+        try {
+            startDtoJson = objectMapper.writeValueAsString(startDto);
+        } catch (JsonProcessingException e) {
+            throw new RuntimeException(e);
+        }
+        body.add("data", startDtoJson);
         HttpEntity<MultiValueMap<String, Object>> requestEntity = new HttpEntity<>(body, headers);
         return restTemplate.postForObject(url, requestEntity, Map.class);
     }

frontend/src/pages/Feature/camera.jsx

@@ -56,6 +56,7 @@ function Camera() {
     const data = {
       email: email,
       gender: gender,
+      gan_permission: createImageChecked,
     };
 
     formdata.append(

info.csv

@@ -0,0 +1 @@
+email, gender, gan_permission, image_path

main.py

@@ -10,13 +10,15 @@
 import shutil
 import base64
 
-from flask import Flask, request, jsonify
+from flask import Flask, request
+import json
 
 import shape_detect.controller
 
 app = Flask(__name__)
 
 image_path = os.path.join(os.path.dirname(__file__), "predict_image")
+info_path = os.path.join(os.path.dirname(__file__), "info.csv")
 filename = ""
 pc_model : PersonalColorModel = joblib.load('./model_v2.pkl')
 ss = joblib.load("./scaler_v2.pkl")
@@ -33,11 +35,13 @@ def hello_world():
 def predict_color():
     global features, pc_model, ss, current_image_path
     # 이미지 저장
+
     f = request.files['image']
+    data = json.loads(request.form.get("data"))
 
     type = f.filename[f.filename.rfind("."):]
 
-    folder_path = os.path.join(image_path, f.filename.replace(".", "_"))
+    folder_path = os.path.join(image_path, data["email"])
     f_path = os.path.join(folder_path, "origin_img" + type)
 
     if os.path.exists(folder_path):
@@ -47,6 +51,11 @@ def predict_color():
 
     f.save(f_path)
 
+    # 생성형 이미지를 위한 정보 저장
+    df = pd.read_csv(info_path)
+    df.loc[len(df)] = [data["email"], data["gender"], data["gan_permission"], f_path]
+    df.to_csv(info_path, mode = 'w', index=False)
+
     current_image_path = f_path[:]
     print(current_image_path)