Update app.py

app.py

@@ -1,4 +1,46 @@
 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
 
-x = st.slider('Select a value')
-st.write(x, 'squared is', x * x)
+
+
+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: 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,
+)