如何为我的图像分类模型FastAPI API解码base64图像并获取它的类

from fastapi import FastAPI
import base64
import io
from PIL import Image
import numpy as np
import tensorflow as tf

app = FastAPI()

# 加载图像分类模型
model = tf.keras.models.load_model('path_to_your_model')

# 图像分类API端点
@app.post('/classify_image')
async def classify_image(image_data: str):
    # 解码base64图像数据
    image_bytes = base64.b64decode(image_data)
    image = Image.open(io.BytesIO(image_bytes))
    
    # 调整图像大小和格式
    image = image.resize((224, 224))
    image = np.array(image) / 255.0
    image = np.expand_dims(image, axis=0)
    
    # 使用模型进行预测
    predictions = model.predict(image)
    
    # 获取预测结果的类别
    class_index = np.argmax(predictions[0])
    class_label = 'your_class_labels[class_index]'
    
    return {'class': class_label}