如何在python中将图像及其对应的值(.csv)输入到回归模型？

import pandas as pd
import numpy as np
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LinearRegression
from PIL import Image

# 读取图像数据
image = Image.open("image.jpg")
image_array = np.array(image)

# 读取对应的值数据
data = pd.read_csv("data.csv")

# 将图像数据转换为一维数组
image_flattened = image_array.flatten()

# 合并图像数据和值数据
combined_data = np.column_stack((image_flattened, data))

# 划分训练集和测试集
X_train, X_test, y_train, y_test = train_test_split(combined_data[:, :-1], combined_data[:, -1], test_size=0.2, random_state=0)

# 创建线性回归模型
regressor = LinearRegression()

# 训练模型
regressor.fit(X_train, y_train)

# 预测测试集数据
y_pred = regressor.predict(X_test)