商品识别新春大促

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

# 构建一个简单的卷积神经网络模型
def create_model():
    model = models.Sequential([
        layers.Conv2D(32, (3, 3), activation='relu', input_shape=(64, 64, 3)),
        layers.MaxPooling2D((2, 2)),
        layers.Conv2D(64, (3, 3), activation='relu'),
        layers.MaxPooling2D((2, 2)),
        layers.Conv2D(64, (3, 3), activation='relu'),
        layers.Flatten(),
        layers.Dense(64, activation='relu'),
        layers.Dense(10, activation='softmax')  # 假设有10种商品类别
    ])
    return model

model = create_model()
model.compile(optimizer='adam',
              loss='sparse_categorical_crossentropy',
              metrics=['accuracy'])

# 假设X_train和y_train是预处理后的训练数据和标签
model.fit(X_train, y_train, epochs=10)