我正在尝试在pycharm中创建CNN。运行代码时,控制台输出
RuntimeError: You must compile your model before using it.
我写下编译。 这是我的代码:
#!/usr/bin/env python
# -*- coding: utf-8 -*-o
from keras.models import Sequential
from keras.layers import Dense, MaxPool2D, Flatten, Conv2D, Dropout
from keras.preprocessing import image
from keras.optimizers import adadelta
generator = image.ImageDataGenerator(
rescale=1./255,
featurewise_center=False,
samplewise_center=False,
featurewise_std_normalization=False,
samplewise_std_normalization=False,
zca_whitening=False,
rotation_range=10,
width_shift_range=0.1,
height_shift_range=0.1,
horizontal_flip=True,
vertical_flip=False,
)
dateset = generator.flow_from_directory(
shuffle=True,
batch_size=100,
target_size=(80, 80),
directory='/Users/Username/Documents/Project AI/Dateset/blood-cells/dataset2-master/images/TRAIN')
def model():
model = Sequential()
model.add(Conv2D(80, (3, 3), strides=(1, 1), activation='relu'))
model.add(Conv2D(64, (3, 3), strides=(1, 1), activation='relu',
input_shape=(80, 80, 3)))
model.add(MaxPool2D(pool_size=(2, 2)))
model.add(Conv2D(64, (3, 3), strides=(1, 1), activation='relu'))
model.add(Dropout(0.25))
model.add(Flatten())
model.add(Dense(128, activation='relu'))
model.add(Dropout(0.5))
model.add(Dense(4, activation='softmax'))
model.compile(optimizer=adadelta(lr=0.001),
loss='categorical_crossentropy', metrics=['accuracy'])
return model
nn = model()
nn.fit_generator(dateset,steps_per_epoch=None, epochs=30, verbose=1)
nn.save('/Users/yangzichen/Documents/Project AI/Model.txt')
答案 0 :(得分:1)
您似乎用您的函数覆盖了Keras model()
函数。尝试以下方法:
def get_model():
model = Sequential()
...
< *rest of your function code here* >
...
return model
nn = get_model()