Update api_server.py

api_server.py

@@ -13,7 +13,7 @@ from tensorflow import keras
 from flask import Flask, jsonify, request, render_template, send_file
 import torch
 from collections import Counter
-from clip import clip_result
+from clip_model import ClipModel
 
 # Disable tensorflow warnings
 os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
@@ -76,6 +76,8 @@ def get_jpg_files(path):
 
 # Initialize the Flask application
 app = Flask(__name__)
+# Initialize the ClipModel at the start
+clip_model = ClipModel()
 
 
 # API route for prediction(YOLO)
@@ -126,11 +128,14 @@ def predict():
             yolo_path = f"{YOLO_DIR}/{message_id}/{element}"
             yolo_file = get_jpg_files(yolo_path)
 
+            print(yolo_path)
+
             element_list.append(element)
             
             for yolo_img in yolo_file: # 每張切圖yolo_img
-                top_k_words.append(clip_result(yolo_img)) # CLIP預測3個結果(top_k_words)
+                top_k_words.append(clip_model.clip_result(yolo_img)) # CLIP預測3個結果(top_k_words)
                 encoded_images.append(image_to_base64(yolo_img))
+                print(top_k_words)
 
             # if element_counts[element] > 1: #某隻角色的數量>1
             #     yolo_path = f"{YOLO_DIR}/{message_id}/{element}"
@@ -162,7 +167,7 @@ def predict():
         # }
         
         return jsonify(response_data)
-        
+            
         # for label_name in label_names:
         #     yolo_file=f"{YOLO_DIR}/{message_id}/{label_name}/im.jpg.jpg"
         #     # 將圖片轉換為 base64 編碼