diff --git a/mnist_cnn_gui_main.py b/mnist_cnn_gui_main.py
new file mode 100644
index 0000000..b19673d
--- /dev/null
+++ b/mnist_cnn_gui_main.py
@@ -0,0 +1,159 @@
+
+import sys
+
+import numpy as np
+from PIL import Image, ImageQt
+from PyQt5.QtCore import QSize
+from PyQt5.QtGui import QPixmap, QColor
+from PyQt5.QtWidgets import QMainWindow, QDesktopWidget, QApplication
+from PyQt5.QtWidgets import QMessageBox
+
+from common.functions import softmax
+from dataset.mnist import load_mnist
+from qt.layout import Ui_MainWindow
+from qt.paintboard import PaintBoard
+from simple_convnet import SimpleConvNet
+
+MODE_WRITE = 2    # 手写输入
+
+Thresh = 0.5      # 识别结果置信度阈值
+
+
+
+# 读取MNIST数据集
+(_, _), (x_test, _) = load_mnist(normalize=True, flatten=False, one_hot_label=False)
+
+
+# 初始化网络
+
+# 简单CNN
+
+network = SimpleConvNet(input_dim=(1,28,28), 
+                        conv_param = {'filter_num': 30, 'filter_size': 5, 'pad': 0, 'stride': 1},
+                        hidden_size=100, output_size=10, weight_init_std=0.01)
+network.load_params("params.pkl")
+
+
+
+
+class MainWindow(QMainWindow,Ui_MainWindow):
+    def __init__(self):
+        super(MainWindow,self).__init__()
+    
+        # 初始化参数
+        self.result = [0, 0]
+
+        # 初始化UI
+        self.setupUi(self)
+        self.center()
+
+        # 初始化画板
+        self.paintBoard = PaintBoard(self, Size = QSize(224, 224), Fill = QColor(0,0,0,0))
+        self.paintBoard.setPenColor(QColor(0,0,0,0))
+        self.dArea_Layout.addWidget(self.paintBoard)
+
+        self.clearDataArea()
+
+    # 窗口居中
+    def center(self):
+        # 获得窗口
+        framePos = self.frameGeometry()
+        # 获得屏幕中心点
+        scPos = QDesktopWidget().availableGeometry().center()
+        # 显示到屏幕中心
+        framePos.moveCenter(scPos)
+        self.move(framePos.topLeft())
+    
+    
+    # 窗口关闭事件
+    def closeEvent(self, event):
+        reply = QMessageBox.question(self, '消息',
+            "确定退出吗?", QMessageBox.Yes |
+            QMessageBox.No, QMessageBox.Yes)
+
+        if reply == QMessageBox.Yes:
+            event.accept()
+        else:
+            event.ignore()   
+    
+    # 清除数据待输入区
+    def clearDataArea(self):
+        self.paintBoard.Clear()
+        self.lbDataArea.clear()
+        self.lbResult.clear()
+        self.lbCofidence.clear()
+        self.result = [0, 0]
+
+    """
+    回调函数
+    """
+    # 模式下拉列表回调
+    def cbBox_Mode_Callback(self, text):
+            self.mode = MODE_WRITE
+            self.clearDataArea()
+
+            # 更改背景
+            self.paintBoard.setBoardFill(QColor(0,0,0,255))
+            self.paintBoard.setPenColor(QColor(255,255,255,255))
+
+
+    # 数据清除
+    def pbtClear_Callback(self):
+        self.clearDataArea()
+ 
+
+    # 识别
+    def pbtPredict_Callback(self):
+
+        __img = self.paintBoard.getContentAsQImage()
+
+        # 转换成pil image类型处理
+        pil_img = ImageQt.fromqimage(__img)
+        pil_img = pil_img.resize((28, 28), Image.ANTIALIAS)
+
+
+        img_array = np.array(pil_img.convert('L')).reshape(1,1,28, 28) / 255.0
+        # img_array = np.where(img_array>0.5, 1, 0)
+    
+        # reshape成网络输入类型 
+        __result = network.predict(img_array)      # shape:[1, 10]
+
+        # print (__result)
+
+        # 将预测结果使用softmax输出
+        __result = softmax(__result)
+       
+        self.result[0] = np.argmax(__result)          # 预测的数字
+        self.result[1] = __result[0, self.result[0]]     # 置信度
+
+        self.lbResult.setText("%d" % (self.result[0]))
+        self.lbCofidence.setText("%.8f" % (self.result[1]))
+
+
+    # # 随机抽取
+    # def pbtGetMnist_Callback(self):
+    #     self.clearDataArea()
+    #
+    #     # 随机抽取一张测试集图片，放大后显示
+    #     img = x_test[np.random.randint(0, 9999)]    # shape:[1,28,28]
+    #     img = img.reshape(28, 28)                   # shape:[28,28]
+    #
+    #     img = img * 0xff      # 恢复灰度值大小
+    #     pil_img = Image.fromarray(np.uint8(img))
+    #     pil_img = pil_img.resize((224, 224))        # 图像放大显示
+    #
+    #     # 将pil图像转换成qimage类型
+    #     qimage = ImageQt.ImageQt(pil_img)
+    #
+    #     # 将qimage类型图像显示在label
+    #     pix = QPixmap.fromImage(qimage)
+    #     self.lbDataArea.setPixmap(pix)
+    #
+
+
+if __name__ == "__main__":
+    app = QApplication(sys.argv)
+    Gui = MainWindow()
+    Gui.show()
+
+    sys.exit(app.exec_())
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