神经网络过滤掉除了猫/狗以外的所有东西

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

# 构建一个简单的卷积神经网络
def create_model():
    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.MaxPooling2D((2, 2)),
        layers.Flatten(),
        layers.Dense(512, activation='relu'),
        layers.Dropout(0.5),
        layers.Dense(1, activation='sigmoid')  # 二分类问题
    ])
    return model

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

# 假设你已经有了训练和验证数据集 train_images, train_labels, val_images, val_labels
model.fit(train_images, train_labels, epochs=10, validation_data=(val_images, val_labels))