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

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.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])
model.load_weights(checkpoint_path)


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** [邱彥榕](https://www.linkedin.com/in/yjc-86941b101/)
    """)
st.sidebar.markdown(""" # **Step 1: 上傳檔案到data**""")
st.sidebar.markdown(""" # **Step 2: 開始分析**""")

def callback():
    data = load_wave()
    st.line_chart(data)
    out = tf.round(model.predict(np.array(data.T[1]))).cpu()
    if np.array(out)[0] == "0":
        st.text("Relax")
    else:
        st.text("Activate")
    
    

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