app.py

import streamlit as st
import wfdb
from datasets import load_dataset
from load_wave import load_wave
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense
import tensorflow as tf
import os
import numpy as np



dataset = load_dataset("lhoestq/demo1")

st.set_page_config("銘傳大學生物醫學工程學系ECG分析網站")
st.sidebar.markdown(""" **Developed by** [吳允翔](https://www.linkedin.com/in/yjc-86941b101/)
    """)
st.sidebar.markdown(""" # **Step 1: 修改load_wave中，取得PhysioNet分析資料**""")
st.sidebar.markdown(""" # **Step 2: 開始分析**""")

def callback():
    data = load_wave()
    st.line_chart(data)
    data = np.array(data.T[1].reshape(1,4000))

    path = "./"
    checkpoint_path = os.path.join(path,"model.ckpt")
    model = Sequential()
    model.add(Dense(64, input_shape=(4000,), activation='relu'))
    model.add(Dense(8, activation='relu'))
    model.add(Dense(1, activation='sigmoid'))
    model.load_weights(checkpoint_path)

    out = np.array(tf.round(model.predict(data)).cpu())[0][0]
    
    if out == 0:
        st.text("測試者狀態是 Relax")
    else:
        st.text("測試者狀態是 Activate")
    

bt1 = st.button(
    "分析",
    on_click=callback,
    disabled=False,
)