Upload 3 files
Browse files- app.py +96 -0
- images/image.jpg +0 -0
- requirements.txt +1 -0
app.py
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import streamlit as st
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import requests
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from PIL import Image
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image_path = '\images\image.jpg'
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image = Image.open(image_path)
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# Set API Endpoint
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URL = 'https://radiant-lowlands-86946.herokuapp.com/predict'
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# Create a function to make prediction
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def make_prediction(pg: float, bwr1: float, bp : float, bwr2: float, bwr3: float, bmi: float, bwr4: float, age: int, insurance: bool):
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parameters={
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'plasma_glucose':pg,
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'blood_work_result_1':bwr1,
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'blood_pressure':bp,
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'blood_work_result_2':bwr2,
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'blood_work_result_3':bwr3,
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'body_mass_index':bmi,
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'blood_work_result_4':bwr4,
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'age':int(age),
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'insurance':bool(insurance)}
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response = requests.post(URL, params=parameters)
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response_text = response.json()
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sepsis_status = response_text['results'][0]['0']['output']['Predicted Label']
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return sepsis_status
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# set page configuration
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st.set_page_config(
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page_title='Sepsis Prediction',
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page_icon="🤖",
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initial_sidebar_state="expanded",
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menu_items={
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'About': "# This is a Health App. Call it the Covid Vaccine Sepsis Analyzer!"
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}
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)
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# create a sidebar and contents
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st.sidebar.markdown("""
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## Demo App
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This app return sepsis status base on the input parameters
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""")
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st.markdown('''
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<h1 style="color: green; text-align:center">The Sepsis Prediction App</h1>
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''', unsafe_allow_html=True)
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# insert an image
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st.image(image, caption=None, width=None, use_column_width=None, clamp=False, channels="RGB", output_format="auto")
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# Create app interface
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container = st.container()
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container.write("Inputs to predict Sepsis")
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with container:
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col1, col2, col3 = st.columns(3)
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age = col1.number_input(label='Age')
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pg = col2.number_input(label='Blood Glucose')
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bp = col3.number_input(label='Blood Pressure')
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with st.expander(label='Blood Parameter', expanded=True, ):
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bwr1 = col1.number_input(label='Blood Work Result-1')
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bwr2 = col2.number_input(label='Blood Work Result-2')
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bwr3 = col1.number_input(label='Blood Work Result-3')
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bwr4 = col2.number_input(label='Blood Work Result-4')
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ins = col3.selectbox(label='Insurance', options=[True, False])
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bmi = col3.number_input(label='Body Mass Index')
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button = st.button(label='Predict', type='primary', use_container_width=True)
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if button:
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response = make_prediction(pg, bwr1, bp, bwr2, bwr3, bmi, bwr4, age, ins)
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st.write(f'The {response}')
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images/image.jpg
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requirements.txt
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@@ -0,0 +1 @@
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streamlit==1.23.1
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