用Python写一个cnn-lstm代码

好的，我可以给您提供一个Python实现的CNN-LSTM代码，您需要安装TensorFlow和Keras库才能运行该代码，代码如下：

import tensorflow as tf
from keras.models import Sequential
from keras.layers import Dense, Dropout, Conv2D, MaxPooling2D, LSTM, TimeDistributed, Flatten

# Define the model
model = Sequential()
model.add(Conv2D(filters=32, kernel_size=(3, 3), activation='relu',
                 input_shape=(img_width, img_height, 3)))
model.add(MaxPooling2D(pool_size=(2, 2)))
model.add(Conv2D(filters=32, kernel_size=(3, 3), activation='relu'))
model.add(MaxPooling2D(pool_size=(2, 2)))
model.add(Flatten())
model.add(Dropout(0.5))
model.add(Dense(128, activation='relu'))
model.add(Dense(1, activation='sigmoid'))
model.add(Reshape([1, 1]))

model.add(LSTM(64, return_sequences=False))
model.add(Dense(1))

model.compile(loss='mean_squared_error', optimizer='adam')

# Train the model
model.fit(x_train, y_train, batch_size=32, epochs=10, validation_data=(x_test, y_test))

请注意，此代码只是一个样例，在实际应用中，您需要根据您的具体需求进行修改和调整。