单脸融合如何创建

import tensorflow as tf
from tensorflow.keras.models import Model
from tensorflow.keras.layers import Input, Conv2D, UpSampling2D

# 定义一个简单的卷积神经网络模型
def create_model(input_shape):
    inputs = Input(shape=input_shape)
    x = Conv2D(64, (3, 3), activation='relu', padding='same')(inputs)
    x = UpSampling2D((2, 2))(x)
    x = Conv2D(32, (3, 3), activation='relu', padding='same')(x)
    x = UpSampling2D((2, 2))(x)
    outputs = Conv2D(3, (3, 3), activation='sigmoid', padding='same')(x)
    model = Model(inputs, outputs)
    return model

# 加载和预处理图像
def load_and_preprocess_image(image_path):
    img = tf.keras.preprocessing.image.load_img(image_path, target_size=(256, 256))
    img_array = tf.keras.preprocessing.image.img_to_array(img)
    img_array = img_array / 255.0
    return img_array

# 融合两张图像
def blend_images(image1, image2):
    model = create_model((256, 256, 3))
    model.compile(optimizer='adam', loss='mean_squared_error')
    blended_image = model.predict([image1, image2])
    return blended_image

# 示例使用
image1 = load_and_preprocess_image('path_to_image1.jpg')
image2 = load_and_preprocess_image('path_to_image2.jpg')
blended_image = blend_images(image1, image2)