修改可视化客户端ImageTk为ctk,消除警告。

classifier/embedding_food_classifier_app.py

@@ -4,7 +4,7 @@ import cv2
 import numpy as np
 import customtkinter as ctk
 from tkinter import filedialog, messagebox
-from PIL import Image, ImageTk
+from PIL import Image
 import torch
 import torch.nn.functional as F
 from typing import List, Optional, Tuple
@@ -387,11 +387,11 @@ class EmbeddingFoodClassifierApp:
             display_image = self.resize_image_for_display(img_info['image'], 100, 100)
             display_image = cv2.cvtColor(display_image, cv2.COLOR_BGR2RGB)
             pil_image = Image.fromarray(display_image)
-            tk_image = ImageTk.PhotoImage(pil_image)
+            ctk_image = ctk.CTkImage(light_image=pil_image, dark_image=pil_image, size=(100, 100))
             
             # 图片标签（可点击预览）
-            img_label = ctk.CTkLabel(img_frame, image=tk_image, text="")
+            img_label = ctk.CTkLabel(img_frame, image=ctk_image, text="")
-            img_label.image = tk_image  # 保持引用
+            img_label.image = ctk_image  # 保持引用
             img_label.pack(side="left", padx=10, pady=10)
             img_label.bind("<Button-1>", lambda e, idx=i: self.preview_image(idx))
             
@@ -483,10 +483,12 @@ class EmbeddingFoodClassifierApp:
         display_image = self.resize_image_for_display(img_info['image'], 750, 550)
         display_image = cv2.cvtColor(display_image, cv2.COLOR_BGR2RGB)
         pil_image = Image.fromarray(display_image)
-        tk_image = ImageTk.PhotoImage(pil_image)
+        # 获取实际图片尺寸
+        img_width, img_height = pil_image.size
+        ctk_image = ctk.CTkImage(light_image=pil_image, dark_image=pil_image, size=(img_width, img_height))
         
-        img_label = ctk.CTkLabel(preview_window, image=tk_image, text="")
+        img_label = ctk.CTkLabel(preview_window, image=ctk_image, text="")
-        img_label.image = tk_image
+        img_label.image = ctk_image
         img_label.pack(expand=True, padx=20, pady=20)
     
     def remove_image(self, index):
@@ -691,11 +693,11 @@ class EmbeddingFoodClassifierApp:
             display_image = self.resize_image_for_display(img_info['image'], 120, 120)
             display_image = cv2.cvtColor(display_image, cv2.COLOR_BGR2RGB)
             pil_image = Image.fromarray(display_image)
-            tk_image = ImageTk.PhotoImage(pil_image)
+            ctk_image = ctk.CTkImage(light_image=pil_image, dark_image=pil_image, size=(120, 120))
             
             # 图片标签
-            img_label = ctk.CTkLabel(result_frame, image=tk_image, text="")
+            img_label = ctk.CTkLabel(result_frame, image=ctk_image, text="")
-            img_label.image = tk_image
+            img_label.image = ctk_image
             img_label.pack(side="left", padx=10, pady=10)
             img_label.bind("<Button-1>", lambda e, idx=result['image_index']: self.preview_image(idx))
             

net/resnet_embedding.py

@@ -30,7 +30,8 @@ class ResNet50EmbeddingNet(nn.Module):
         
         # 加载预训练的ResNet50 (使用新的weights参数)
         if pretrained:
-            self.backbone = models.resnet50(weights=models.ResNet50_Weights.IMAGENET1K_V1)
+            # V2效果会好一点
+            self.backbone = models.resnet50(weights=models.ResNet50_Weights.IMAGENET1K_V2)
         else:
             self.backbone = models.resnet50(weights=None)