手写体文字识别双11促销活动

import tensorflow as tf
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Conv2D, MaxPooling2D, LSTM, Dense, Bidirectional

# 假设我们已经有预处理好的手写体图像数据和标签
# X_train, y_train 是训练数据和标签

model = Sequential()
model.add(Conv2D(32, (3, 3), activation='relu', input_shape=(28, 28, 1)))
model.add(MaxPooling2D((2, 2)))
model.add(Conv2D(64, (3, 3), activation='relu'))
model.add(MaxPooling2D((2, 2)))
model.add(Bidirectional(LSTM(128, return_sequences=True)))
model.add(Bidirectional(LSTM(128)))
model.add(Dense(64, activation='relu'))
model.add(Dense(10, activation='softmax'))

model.compile(optimizer='adam', loss='sparse_categorical_crossentropy', metrics=['accuracy'])
model.fit(X_train, y_train, epochs=10, batch_size=32)

# 预测
predictions = model.predict(X_test)