diff --git a/nodes/image.py b/nodes/image.py
index f9d88ad..8551788 100644
--- a/nodes/image.py
+++ b/nodes/image.py
@@ -1,36 +1,33 @@
-import os.path
+import os
 import uuid
-
-import torch
-import torchvision
-
-
+from PIL import Image
+import numpy as np
 class SaveImagePath:
     @classmethod
     def INPUT_TYPES(s):
         return {
             "required": {
-                "image_path":("IMAGE", {"forceInput": True}),
+                "image_path": ("IMAGE", {"forceInput": True}),
             }
         }
-
     RETURN_TYPES = ("STRING",)
-
     FUNCTION = "load"
-
     CATEGORY = "不忘科技-自定义节点🚩"
-
-    def load(self, image_path:torch.Tensor):
-        image_path = image_path.float()
-        # 假设数据范围在 [0, 255]，进行归一化
-        image_path = image_path / 255.0
-        # 检查并调整形状（这里只是示例，具体调整需根据实际情况）
-        if len(image_path.shape) == 3:
-            image_path = image_path.unsqueeze(0)  # 添加批次维度
-        u = uuid.uuid4()
-        p = os.path.join(os.path.dirname(os.path.abspath(__file__)), "output", "%s.jpg" % str(u))
-        torchvision.utils.save_image(image_path, p)
-        # u = uuid.uuid4()
-        # p = os.path.join(os.path.dirname(os.path.abspath(__file__)),"output","%s.jpg" % str(u))
-        # torchvision.utils.save_image(image_path, p)
-        return (p,)
+    def load(self, image_path):
+        # 确保数据类型为uint8且在0 - 255范围内
+        if image_path.dtype != np.uint8:
+            image_path = np.clip(image_path, 0, 255).astype(np.uint8)
+        # 如果是单通道图像，转换为3通道
+        if len(image_path.shape) == 2:
+            image_path = np.stack([image_path] * 3, axis=-1)
+        # 如果是通道优先格式 (C, H, W)，转换为通道最后格式 (H, W, C)
+        elif len(image_path.shape) == 3 and image_path.shape[0] <= 4:
+            image_path = np.transpose(image_path, (1, 2, 0))
+        pil_image = Image.fromarray(image_path)
+        output_dir = os.path.join(os.path.dirname(os.path.abspath(__file__)), "output")
+        if not os.path.exists(output_dir):
+            os.makedirs(output_dir)
+        file_name = "%s.jpg" % str(uuid.uuid4())
+        p = os.path.join(output_dir, file_name)
+        pil_image.save(p)
+        return (p,)
\ No newline at end of file