修改相似图片的路径，这样脚本就可以启动了

classifier/embedding_food_classifier_app.py

@@ -109,6 +109,34 @@ class EmbeddingFoodClassifierApp:
                 paths_path = os.path.join(index_dir, 'image_paths.pkl')
                 with open(paths_path, 'rb') as f:
                     self.image_paths = pickle.load(f)
+                # 兼容 python -m：将相对路径规范为绝对路径（基于项目根目录）
+                PROJECT_ROOT = os.path.abspath(os.path.join(BASE_DIR, ".."))
+                INDEX_DIR = index_dir
+                def _resolve_path(p):
+                    # 若已是绝对路径且存在
+                    if os.path.isabs(p) and os.path.exists(p):
+                        return p
+                    # 统一规范相对路径
+                    rp = os.path.normpath(p)
+                    candidates = [
+                        os.path.abspath(os.path.join(PROJECT_ROOT, rp)),
+                        os.path.abspath(os.path.join(BASE_DIR, rp)),
+                        os.path.abspath(os.path.join(INDEX_DIR, rp)),
+                    ]
+                    # 特殊修正：如果路径误指向 PythonProjects\\dataset，尝试插入 FoodClassifier
+                    try:
+                        proj_root_parent = os.path.dirname(PROJECT_ROOT)
+                        fixed = rp.replace(os.path.join("PythonProjects", "dataset"),
+                                          os.path.join("PythonProjects", "FoodClassifier", "dataset"))
+                        candidates.append(os.path.abspath(os.path.join(proj_root_parent, fixed)))
+                    except Exception:
+                        pass
+                    for c in candidates:
+                        if os.path.exists(c):
+                            return c
+                    # 找不到就退回 PROJECT_ROOT 拼接的绝对路径
+                    return os.path.abspath(os.path.join(PROJECT_ROOT, rp))
+                self.image_paths = [_resolve_path(p) for p in self.image_paths]
                 
                 # 加载标签映射，就是一个list,一张张图片的分类，不过是0，1，2，3，4这种
                 labels_path = os.path.join(index_dir, 'labels.pkl')
@@ -748,10 +776,18 @@ class EmbeddingFoodClassifierApp:
             faiss.write_index(self.faiss_index, index_path)
             
             # 保存图片路径
+            # 保存图片路径（统一存为绝对路径，避免工作目录变化带来的问题）
+            PROJECT_ROOT = os.path.abspath(os.path.join(BASE_DIR, ".."))
+            abs_image_paths = []
+            for p in self.image_paths:
+                if not os.path.isabs(p):
+                    abs_image_paths.append(os.path.abspath(os.path.join(PROJECT_ROOT, p)))
+                else:
+                    abs_image_paths.append(p)
             paths_path = os.path.join(index_dir, 'image_paths.pkl')
             with open(paths_path, 'wb') as f:
-                # 重新写入图片路径
+                # 重新写入图片路径（绝对路径）
-                pickle.dump(self.image_paths, f)
+                pickle.dump(abs_image_paths, f)
             
             # 保存标签
             labels_path = os.path.join(index_dir, 'labels.pkl')
@@ -1396,28 +1432,28 @@ class EmbeddingFoodClassifierApp:
             
             # 加载并显示图片
             try:
-                # 打开图片
+                # 加载图片（兼容中文路径）
-                pil_image = Image.open(image_path)
+                cv_img = self.load_image_with_chinese_path(image_path)
-                
+                if cv_img is None:
+                    raise FileNotFoundError(f"无法读取图片，路径可能不存在或不可访问: {image_path}")
+                # 转为 PIL 并缩放
+                image_rgb = cv2.cvtColor(cv_img, cv2.COLOR_BGR2RGB)
+                pil_image = Image.fromarray(image_rgb)
                 # 计算合适的显示尺寸
                 max_width, max_height = 500, 350
                 img_width, img_height = pil_image.size
-                
                 # 计算缩放比例
                 scale = min(max_width / img_width, max_height / img_height, 1.0)
                 new_width = int(img_width * scale)
                 new_height = int(img_height * scale)
-                
                 # 调整图片大小
                 pil_image = pil_image.resize((new_width, new_height), Image.Resampling.LANCZOS)
-                
                 # 转换为CTk图片
                 ctk_image = ctk.CTkImage(
                     light_image=pil_image,
                     dark_image=pil_image,
                     size=(new_width, new_height)
                 )
-                
                 # 显示图片
                 image_label = ctk.CTkLabel(
                     image_frame,
@@ -1425,9 +1461,8 @@ class EmbeddingFoodClassifierApp:
                     text=""
                 )
                 image_label.pack(expand=True, pady=20)
-                
                 # 图片信息
-                info_text = f"原始尺寸: {img_width} × {img_height}显示尺寸: {new_width} × {new_height}"
+                info_text = f"原始尺寸: {img_width} × {img_height}  显示尺寸: {new_width} × {new_height}"
                 info_label = ctk.CTkLabel(
                     main_frame,
                     text=info_text,