diff --git a/nodes/segformer_b2_clothes.py b/nodes/segformer_b2_clothes.py
new file mode 100644
index 0000000..f7e8843
--- /dev/null
+++ b/nodes/segformer_b2_clothes.py
@@ -0,0 +1,129 @@
+import os
+import numpy as np
+from urllib.request import urlopen
+import torchvision.transforms as transforms  
+import folder_paths
+from transformers import SegformerImageProcessor, AutoModelForSemanticSegmentation
+from PIL import Image,ImageOps, ImageFilter
+import torch.nn as nn
+import torch
+
+from .func import *
+
+# 指定本地分割模型文件夹的路径
+segformer_model_path=get_comfyui_config_model_path("segformer")
+
+model_folder_path = os.path.join(segformer_model_path,"segformer-b2-clothes")
+
+
+ 
+# 切割服装
+def get_segmentation(tensor_image):
+    cloth = tensor2pil(tensor_image)
+    # 预处理和预测
+    inputs = processor(images=cloth, return_tensors="pt")
+    outputs = model(**inputs)
+    logits = outputs.logits.cpu()
+    upsampled_logits = nn.functional.interpolate(logits, size=cloth.size[::-1], mode="bilinear", align_corners=False)
+    pred_seg = upsampled_logits.argmax(dim=1)[0].numpy()
+    return pred_seg,cloth
+
+
+class segformer_b2_clothes:
+   
+    def __init__(self):
+        pass
+    
+    # Labels: 0: "Background", 1: "Hat", 2: "Hair", 3: "Sunglasses", 4: "Upper-clothes", 5: "Skirt", 6: "Pants", 7: "Dress", 8: "Belt", 9: "Left-shoe", 10: "Right-shoe", 11: "Face", 12: "Left-leg", 13: "Right-leg", 14: "Left-arm", 15: "Right-arm", 16: "Bag", 17: "Scarf"
+    
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {"required":
+                {     
+                 "image":("IMAGE",),
+                "Face": ("BOOLEAN", {"default": True, "label_on": "✔ 脸部", "label_off": "× 脸部"}),
+                "Hat": ("BOOLEAN", {"default": True, "label_on": "✔ 帽子", "label_off": "× 帽子"}),
+                "Hair": ("BOOLEAN", {"default": True, "label_on": "✔ 头发", "label_off": "× 头发"}),
+                "Upper_clothes": ("BOOLEAN", {"default": True, "label_on": "✔ 上衣", "label_off": "× 上衣"}),
+                "Skirt": ("BOOLEAN", {"default": True, "label_on": "✔ 裙子", "label_off": "× 裙子"}),
+                "Pants": ("BOOLEAN", {"default": True, "label_on": "✔ 裤子", "label_off": "× 裤子"}),
+                "Dress": ("BOOLEAN", {"default": True, "label_on": "✔ 连衣裙", "label_off": "× 连衣裙"}),
+                "Belt": ("BOOLEAN", {"default": True, "label_on": "✔ 皮带", "label_off": "× 皮带"}),
+                "shoe": ("BOOLEAN", {"default": True, "label_on": "✔ 鞋子", "label_off": "× 鞋子"}),
+                "leg": ("BOOLEAN", {"default": True, "label_on": "✔ 腿", "label_off": "× 腿"}),
+                "arm": ("BOOLEAN", {"default": True, "label_on": "✔ 手臂", "label_off": "× 手臂"}),
+                "Bag": ("BOOLEAN", {"default": True, "label_on": "✔ 包", "label_off": "× 包"}),
+                "Scarf": ("BOOLEAN", {"default": True, "label_on": "✔ 围巾", "label_off": "× 围巾"})
+                }
+        }
+
+    RETURN_TYPES = ("MASK",)
+    RETURN_NAMES = ("mask",)
+    OUTPUT_NODE = True
+    FUNCTION = "sample"
+    CATEGORY = "♾️Mixlab/TryOn"
+
+    def sample(self,image,Face,Hat,Hair,Upper_clothes,Skirt,Pants,Dress,Belt,shoe,leg,arm,Bag,Scarf):
+        processor = SegformerImageProcessor.from_pretrained(model_folder_path)
+        model = AutoModelForSemanticSegmentation.from_pretrained(model_folder_path)
+
+        results = []
+        for item in image:
+        
+            # seg切割结果，衣服pil
+            pred_seg,cloth = get_segmentation(item)
+            labels_to_keep = [0]
+            # if background :
+            #     labels_to_keep.append(0)
+            if not Hat:
+                labels_to_keep.append(1)
+            if not Hair:
+                labels_to_keep.append(2)
+            if not Upper_clothes:
+                labels_to_keep.append(4)
+            if not Skirt:
+                labels_to_keep.append(5)
+            if not Pants:
+                labels_to_keep.append(6)
+            if not Dress:
+                labels_to_keep.append(7)
+            if not Belt:
+                labels_to_keep.append(8)
+            if not shoe:
+                labels_to_keep.append(9)
+                labels_to_keep.append(10)
+            if not Face:
+                labels_to_keep.append(11)
+            if not leg:
+                labels_to_keep.append(12)
+                labels_to_keep.append(13)
+            if not arm:
+                labels_to_keep.append(14) 
+                labels_to_keep.append(15) 
+            if not Bag:
+                labels_to_keep.append(16)
+            if not Scarf:
+                labels_to_keep.append(17)
+                
+            mask = np.isin(pred_seg, labels_to_keep).astype(np.uint8)
+            
+            # 创建agnostic-mask图像
+            mask_image = Image.fromarray(mask * 255)
+            mask_image = mask_image.convert("RGB")
+            mask_image = pil2tensor(mask_image)
+
+            temp = (torch.clamp(mask_image, 0, 1.0) * 255.0).round().to(torch.int)
+            temp = torch.bitwise_left_shift(temp[:,:,:,0], 16) + torch.bitwise_left_shift(temp[:,:,:,1], 8) + temp[:,:,:,2]
+            mask = torch.where(temp == 0, 255, 0).float()
+
+            results.append(mask)
+
+        return (torch.cat(results, dim=0),)
+
+NODE_CLASS_MAPPINGS = {
+    "FashionClothMask2": segformer_b2_clothes
+}
+
+NODE_DISPLAY_NAME_MAPPINGS = {
+    "FashionClothMask2": "Fashion Cloth Mask 2"
+}
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