Update clip_model.py

clip_model.py

@@ -3,6 +3,20 @@ import torch
 from PIL import Image
 from transformers import ChineseCLIPProcessor, ChineseCLIPModel
 
+def check_memory_usage():
+    # Get memory details
+    memory_info = psutil.virtual_memory()
+    
+    total_memory = memory_info.total / (1024 * 1024)  # Convert bytes to MB
+    available_memory = memory_info.available / (1024 * 1024)
+    used_memory = memory_info.used / (1024 * 1024)
+    memory_usage_percent = memory_info.percent
+    
+    print(f"^^^^^^ Total Memory: {total_memory:.2f} MB ^^^^^^")
+    print(f"^^^^^^ Available Memory: {available_memory:.2f} MB ^^^^^^")
+    print(f"^^^^^^ Used Memory: {used_memory:.2f} MB ^^^^^^")
+    print(f"^^^^^^ Memory Usage (%): {memory_usage_percent}% ^^^^^^")
+
 class ClipModel:
     def __init__(self, model_name="OFA-Sys/chinese-clip-vit-base-patch16", model_path=None, vocab_path='./chiikawa/word_list.txt'):
         # Set device
@@ -26,21 +40,6 @@ class ClipModel:
         with open(vocab_path, 'r', encoding='utf-8') as f:
             self.vocab = [line.strip() for line in f.readlines()]
 
-    def check_memory_usage():
-        # Get memory details
-        memory_info = psutil.virtual_memory()
-    
-        total_memory = memory_info.total / (1024 * 1024)  # Convert bytes to MB
-        available_memory = memory_info.available / (1024 * 1024)
-        used_memory = memory_info.used / (1024 * 1024)
-        memory_usage_percent = memory_info.percent
-    
-        print(f"^^^^^^ Total Memory: {total_memory:.2f} MB ^^^^^^")
-        print(f"^^^^^^ Available Memory: {available_memory:.2f} MB ^^^^^^")
-        print(f"^^^^^^ Used Memory: {used_memory:.2f} MB ^^^^^^")
-        print(f"^^^^^^ Memory Usage (%): {memory_usage_percent}% ^^^^^^")
-
-
     def clip_result(self, image_path, top_k=3):
         """
         給定圖片路徑，返回最接近的 top_k 詞彙