diff --git a/ai.py b/ai.py
index f2821ad..5bcd6f2 100644
--- a/ai.py
+++ b/ai.py
@@ -12,6 +12,7 @@ import mediapipe as mp
 import torch
 import torch.nn as nn
 import numpy as np
+import tkinter as tk
 import shutil
 import math
 from scipy import stats
@@ -260,17 +261,16 @@ class AI:
                 optimizer.zero_grad()  # clear gradients for this training step
                 loss.backward()  # backpropagation, compute gradients
                 optimizer.step()  # apply gradients
-                if (step + 1) % 100 == 0:  # 输出结果
-                    if (step + 1) % 100 == 0:  # 输出结果
-                        print(
-                            "\r[Epoch: %d] [%d/%d (%0.f %%)][Loss: %f]"
-                            % (
-                                epoch,
-                                step * len(data),
-                                len(self.train_loader.dataset),
-                                100. * step / len(self.train_loader),
-                                loss.item()
-                            ), end="")
+                if (step + 1) % 50 == 0:  # 输出结果
+                    print(
+                        "\r[Epoch: %d] [%d/%d (%0.f %%)][Loss: %f]"
+                        % (
+                            epoch + 1,
+                            (step + 1) * len(data),
+                            len(self.train_loader.dataset),
+                            100. * (step + 1) / len(self.train_loader),
+                            loss.item()
+                        ), end="")
 
         cnn.out_label = self.out_label
         torch.save(cnn, 'CNN.pkl')
@@ -284,6 +284,20 @@ class Main:
         self.default_datasets = "Datasets"
         self.len_x = 22
         self.len_y = 4
+        self.label = ''
+        self.top1 = tk.Tk()
+        self.top1.geometry('300x50')
+        self.top1.title('请输入标签')
+        tk.Label(self.top1, text='Label:').place(x=27, y=10)
+        self.entry = tk.Entry(self.top1, width=15)
+        self.entry.place(x=80, y=10)
+        tk.Button(self.top1, text='确定', command=self.change_state).place(x=235, y=5)
+
+    def change_state(self):
+        self.label = self.entry.get()  # 调用get()方法，将Entry中的内容获取出来
+        self.top1.quit()
+        if self.label == "":
+            self.top1.destroy()
 
     def make_datasets(self, datasets_dir="default", n=100):
         if datasets_dir == "default":
@@ -295,8 +309,8 @@ class Main:
             self.camera = cv2.VideoCapture(0, cv2.CAP_DSHOW)
             self.camera.set(3, 1280)
             self.camera.set(4, 720)
-        label = input("label:")
-        while not label == "":
+        self.top1.mainloop()
+        while not self.label == "":
             data = np.zeros([n, self.len_x, self.len_y])
             shape_list = np.zeros([n, 2], dtype=np.int16)
             hand_type = np.zeros(n, dtype=np.int8)
@@ -332,10 +346,11 @@ class Main:
                     break
             cv2.destroyAllWindows()
 
-            open(datasets_dir + "/" + label + ".npz", "w")
-            np.savez(datasets_dir + "/" + label + ".npz", label=label, data=data,
+            open(datasets_dir + "/" + self.label + ".npz", "w")
+            np.savez(datasets_dir + "/" + self.label + ".npz", label=self.label, data=data,
                      handtype=hand_type, shape=shape_list)
-            label = input("label:")
+
+            self.top1.mainloop()
 
     def train(self, datasets_dir="default"):
         if datasets_dir == "default":