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.gitattributes

@@ -32,3 +32,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+model.ckpt.data-00000-of-00001 filter=lfs diff=lfs merge=lfs -text

README.md

@@ -1,10 +1,10 @@
 ---
-title: NMSL
-emoji: 👁
-colorFrom: indigo
-colorTo: gray
+title: ECG MAC
+emoji: 🐨
+colorFrom: blue
+colorTo: green
 sdk: streamlit
-sdk_version: 1.21.0
+sdk_version: 1.19.0
 app_file: app.py
 pinned: false
 ---

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,
+)

gitattributes.txt

@@ -0,0 +1,35 @@
+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.wasm filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zst filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text
+model.ckpt.data-00000-of-00001 filter=lfs diff=lfs merge=lfs -text

load_wave.py

@@ -0,0 +1,5 @@
+import wfdb
+
+def load_wave():
+    signals, fields = wfdb.rdsamp("test01_00s", pn_dir="macecgdb/1.0.0/")
+    return signals

model.ckpt.data-00000-of-00001

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5444543b8631327173d72a19415e9d4715f01d2b95baf6f27bf5893ce6d221b8
+size 3081647

requirements.txt

@@ -0,0 +1,3 @@
+tensorflow == 2.12.0
+wfdb
+altair<5