商品智能识别新年促销

import tensorflow as tf
from tensorflow.keras import layers, models
from tensorflow.keras.preprocessing.image import ImageDataGenerator

# 数据准备
train_datagen = ImageDataGenerator(rescale=1./255, validation_split=0.2)
train_generator = train_datagen.flow_from_directory(
    'path_to_train_data',
    target_size=(150, 150),
    batch_size=32,
    class_mode='categorical',
    subset='training'
)
validation_generator = train_datagen.flow_from_directory(
    'path_to_train_data',
    target_size=(150, 150),
    batch_size=32,
    class_mode='categorical',
    subset='validation'
)

# 模型构建
model = models.Sequential([
    layers.Conv2D(32, (3, 3), activation='relu', input_shape=(150, 150, 3)),
    layers.MaxPooling2D((2, 2)),
    layers.Conv2D(64, (3, 3), activation='relu'),
    layers.MaxPooling2D((2, 2)),
    layers.Conv2D(128, (3, 3), activation='relu'),
    layers.Flatten(),
    layers.Dense(512, activation='relu'),
    layers.Dense(num_classes, activation='softmax')
])

# 模型编译与训练
model.compile(optimizer='adam', loss='categorical_crossentropy', metrics=['accuracy'])
model.fit(train_generator, validation_data=validation_generator, epochs=10)

# 模型保存
model.save('product_recognition_model.h5')