#码力全开·技术π对#怎样使用TensorFlow框架来构建一个能够实时识别手写数字的模型

import tensorflow as tf
from tensorflow.keras import layers, models

model = models.Sequential([
    layers.Rescaling(1./255, input_shape=(28, 28, 1)),
    layers.Conv2D(32, (3,3), activation='relu'),
    layers.MaxPooling2D((2, 2)),
    layers.Conv2D(64, (3,3), activation='relu'),
    layers.Flatten(),
    layers.Dense(64, 'relu'),
    layers.Dense(10, 'softmax')
])

model.compile(optimizer='adam', loss='sparse_categorical_crossentropy', metrics=['accuracy'])
model.fit(train_dataset, epochs=5)

converter = tf.lite.TFLiteConverter.from_keras_model(model)
tflite_model = converter.convert()
with open('digit_recognizer.tflite', 'wb') as f:
    f.write(tflite_model)