gradi

# -*- coding: utf-8 -*-
"""
Created on Wed Apr 17 21:57:52 2024

@author: admin
"""

import gradio as gr  
import tensorflow as tf
import numpy as np

# 加载 TensorFlow 模型
model_path = 'model/model_CNN'
loaded_model = tf.saved_model.load(model_path)
model_predict = loaded_model.signatures['serving_default']
# 假设我们有一个处理这些输入的函数  
def process_inputs(AMT, t, BSA, BW, age, height):  
    # 在这里执行您的逻辑，比如模型预测、计算等  
    input_features = np.array([[AMT, t, BSA, BW, age, height]], dtype=float).reshape(-1, 6, 1)
    predictions = model_predict(tf.constant(input_features, dtype=tf.float32))['dense_5'].numpy()
    return predictions 
  
# 创建Gradio界面  
description = "Enter values for AMT, t, BSA, BW, age, and height."  
interface = gr.Interface(  
    fn=process_inputs,  
    inputs=[  
        gr.Number(label="AMT"),  
        gr.Number(label="t"),  
        gr.Number(label="BSA"),  
        gr.Number(label="BW"),  
        gr.Number(label="Age"),  
        gr.Number(label="Height")  
    ],  
    outputs="text",  
    description=description,  
    title="Input Processing Interface"  
)  
  
interface.launch()