def __initData(self):
self.__paintBoard = PaintBoard(self)
mint = tf.keras.datasets.mnist
(X, y), (X_test, y_test) = mint.load_data()
self.model = NaiveBayesScratch()
X = np.array(X).reshape(60000, 784)
self.__xtest = np.array(X_test).reshape(10000, 784)
self.__ytest = y_test
self.model.fit(X, y)
class MainWidget(QWidget):
def __init__(self, Parent=None):
super().__init__(Parent)
self.__result = -1
self.__xtest = []
self.__ytest = []
self.__initData()
self.__initView()
def __initData(self):
self.__paintBoard = PaintBoard(self)
mint = tf.keras.datasets.mnist
(X, y), (X_test, y_test) = mint.load_data()
self.model = NaiveBayesScratch()
X = np.array(X).reshape(60000, 784)
self.__xtest = np.array(X_test).reshape(10000, 784)
self.__ytest = y_test
self.model.fit(X, y)
def __initView(self):
self.setFixedSize(600, 400)
self.setWindowTitle('Application')
main_layout = QHBoxLayout(self)
main_layout.setSpacing(10)
main_layout.addWidget(self.__paintBoard)
sub_layout = QVBoxLayout()
sub_layout.setContentsMargins(10, 10, 10, 10)
sub_layout.setSpacing(30)
self.__btn_Clear = QPushButton('clear')
self.__btn_Clear.setParent(self)
self.__btn_Clear.clicked.connect(self.__paintBoard.clear)
sub_layout.addWidget(self.__btn_Clear)
self.__btn_Predict = QPushButton('predict')
self.__btn_Predict.setParent(self)
self.__btn_Predict.clicked.connect(self.predict)
sub_layout.addWidget(self.__btn_Predict)
self.__btn_Quit = QPushButton('quit')
self.__btn_Quit.setParent(self)
self.__btn_Quit.clicked.connect(self.quit)
sub_layout.addWidget(self.__btn_Quit)
self.__lb_Result_Tip = QLabel()
font = QFont()
font.setPointSize(24)
self.__lb_Result_Tip.setFont(font)
self.__lb_Result_Tip.setText('result')
self.__lb_Result_Tip.setParent(self)
sub_layout.addWidget(self.__lb_Result_Tip)
self.__lb_Result = QLabel()
font = QFont()
font.setPointSize(30)
self.__lb_Result.setFont(font)
self.__lb_Result.setParent(self)
self.__lb_Result.setAlignment(Qt.AlignHCenter)
sub_layout.addWidget(self.__lb_Result)
main_layout.addLayout(sub_layout)
def quit(self):
self.close()
def predict(self):
image = self.__paintBoard.getImage()
pil_img = ImageQt.fromqimage(image)
pil_img = pil_img.resize((28, 28), Image.ANTIALIAS)
# pil_img.save('./images/test66.png')
# pil_img.show()
img_array = np.array(pil_img.convert('L')).reshape(784)
# print(img_array.shape) # (784,)
# display image
# print(img_array)
plt.imshow(img_array.reshape(28, 28), cmap="binary")
plt.show()
# fig = plt.figure(figsize=(6, 6))
# fig.subplots_adjust(left=0, right=1, bottom=0, top=1, hspace=0.05, wspace=0.05)
# # 绘制数字：每张图像8*8像素点
# for i in range(64):
# ax = fig.add_subplot(8, 8, i + 1, xticks=[], yticks=[])
# ax.imshow(self.xtest[i].reshape(28, 28), cmap=plt.cm.binary, interpolation='nearest')
# # 用目标值标记图像
# ax.text(0, 7, str(self.ytest[i]))
# plt.show()
self.__result = self.model.predict(img_array)
print("result: %d" % self.__result)
self.__lb_Result.setText("%d" % self.__result)
def __initData(self):
self.__paintBoard = PaintBoard(self)
self.__model = DigitClassifier()
def __initData(self):
self.__paintBoard = PaintBoard(self)
self.__model = NeuralNetwork()
class MainWidget(QWidget):
def __init__(self, Parent=None):
super().__init__(Parent)
self.__result = -1
self.__initData()
self.__initView()
def __initData(self):
self.__paintBoard = PaintBoard(self)
self.__model = DigitClassifier()
def __initView(self):
self.setFixedSize(600, 400)
self.setWindowTitle('Application')
main_layout = QHBoxLayout(self)
main_layout.setSpacing(10)
main_layout.addWidget(self.__paintBoard)
sub_layout = QVBoxLayout()
sub_layout.setContentsMargins(10, 10, 10, 10)
sub_layout.setSpacing(30)
self.__btn_Clear = QPushButton('clear')
self.__btn_Clear.setParent(self)
self.__btn_Clear.clicked.connect(self.__paintBoard.clear)
sub_layout.addWidget(self.__btn_Clear)
self.__btn_Predict = QPushButton('predict')
self.__btn_Predict.setParent(self)
self.__btn_Predict.clicked.connect(self.predict)
sub_layout.addWidget(self.__btn_Predict)
self.__btn_Quit = QPushButton('quit')
self.__btn_Quit.setParent(self)
self.__btn_Quit.clicked.connect(self.quit)
sub_layout.addWidget(self.__btn_Quit)
self.__lb_Result_Tip = QLabel()
font = QFont()
font.setPointSize(24)
self.__lb_Result_Tip.setFont(font)
self.__lb_Result_Tip.setText('result')
self.__lb_Result_Tip.setParent(self)
sub_layout.addWidget(self.__lb_Result_Tip)
self.__lb_Result = QLabel()
font = QFont()
font.setPointSize(30)
self.__lb_Result.setFont(font)
self.__lb_Result.setParent(self)
self.__lb_Result.setAlignment(Qt.AlignHCenter)
sub_layout.addWidget(self.__lb_Result)
main_layout.addLayout(sub_layout)
def quit(self):
self.close()
def predict(self):
image = self.__paintBoard.getImage()
pil_img = ImageQt.fromqimage(image)
pil_img = pil_img.resize((28, 28), Image.ANTIALIAS)
# pil_img.save('./images/test66.png')
# pil_img.show()
img_array = np.array(pil_img.convert('L')).reshape(784)
# display image
plt.imshow(img_array.reshape(28, 28), cmap="binary")
# plt.imshow(pil_img, cmap="binary")
plt.show()
img_array = np.hstack([img_array, [1.0]]).reshape((1, 785))
# img_array = np.hstack([img_array, [1.0]])
# print(img_array.shape) # (785,)
# img_array = np.reshape(img_array, (img_array.shape[0], -1))
# print(img_array.shape) # (785, 1)
self.__result = self.__model.predict(img_array)
print("result: %d" % self.__result)
self.__lb_Result.setText("%d" % self.__result)
def __initData(self):
self.__paintBoard = PaintBoard(self)
self.model = NaiveBayes()