heart/app.py at master · feverxai/heart · GitHub

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# -*- coding: utf-8 -*-
"""
Created on Tue Mar 17 14:47:25 2020

@author: TRUE
"""

import numpy as np
import flask
import pickle
# app
app = flask.Flask(__name__)
# load model
heart = pickle.load(open("logregheart.pkl","rb"))
# routes
@app.route("/")
def home():
    return """
           <body>
           <h1>Heart Disease Prediction<h1>
           </body>"""
@app.route("/predict", methods=["GET"])
def predict():
    thal = flask.request.args["thal"]
    cp = flask.request.args["cp"]
    slope = flask.request.args["slope"]
    exang = flask.request.args["exang"]
    ca = flask.request.args["ca"]
    fmap = {"normal": [1, 0, 0],
            "fixed defect": [0, 1, 0],
            "reversable defect": [0, 0, 1],
            "typical angina": [1, 0, 0, 0],
            "atypical angina": [0, 1, 0, 0],
            "non anginal pain": [0, 0, 1, 0],
            "asymptomatic": [0, 0, 0, 1],
            "upsloping": [1, 0, 0],
            "flat": [0, 1, 0],
            "downsloping": [0, 0, 1]}
    # X_new = fmap[thal] + fmap[cp] + fmap[slope]
    X_new = np.array(fmap[thal] + fmap[cp] + fmap[slope] + [int(exang)] + [int(ca)]).reshape(1, -1)
    yhat = heart.predict(X_new)
    if yhat[0] == 1:
        outcome = "heart disease"
    else:
        outcome = "normal"
    prob = heart.predict_proba(X_new)
    return "This patient is diagnosed as " + outcome + " with probability " + str(round(prob[0][1], 2))
@app.route("/page")
def page():
   with open("page.html", 'r') as viz_file:
       return viz_file.read()
@app.route("/result", methods=["GET", "POST"])
def result():
    """Gets prediction using the HTML form"""
    if flask.request.method == "POST":
        inputs = flask.request.form
        thal = inputs["thal"]
        cp = inputs["cp"]
        slope = inputs["slope"]
        exang = inputs["exang"]
        ca = inputs["ca"]
    fmap = {"normal": [1, 0, 0],
            "fixed defect": [0, 1, 0],
            "reversable defect": [0, 0, 1],
            "typical angina": [1, 0, 0, 0],
            "atypical angina": [0, 1, 0, 0],
            "non anginal pain": [0, 0, 1, 0],
            "asymptomatic": [0, 0, 0, 1],
            "upsloping": [1, 0, 0],
            "flat": [0, 1, 0],
            "downsloping": [0, 0, 1]}
    X_new = np.array(fmap[thal] + fmap[cp] + fmap[slope] + [int(exang)] + [int(ca)]).reshape(1, -1)
    yhat = heart.predict(X_new)
    if yhat[0] == 1:
        outcome = "heart disease"
    else:
        outcome = "normal"
    prob = heart.predict_proba(X_new)
    # results = """
    #           <body>
    #           <h3> Heart Disease Diagnosis <h3>
    #           <p> Patient profile </p>
    #               <h5> Thalassemia: """ + thal + """</h5>
    #               <h5> Chest Pain: """ + cp + """</h5>
    #               <h5> Slope: """ + slope + """</h5>
    #               <h5> Exercise induced angina: """ + exang + """</h5>
    #               <h5> Number of major vessels (0-3) colored by flourosopy: """ + ca + """</h5>
    #           <p> This patient is diagnose as """ + outcome + """ with probability """ + str(round(prob[0][1], 2)) + """.
    #           </body>
    #           """
    results = """
              <body>
              <h3> Heart Disease Diagnosis <h3>
              <p><h4> Patient profile </h4></p>
              <table>
              <tr>
                  <td>Thalassemia: </td>
                  <td>""" + thal + """</td>
              </tr>
              <tr>
                  <td>Chest Pain: </td>
                  <td>""" + cp + """</td>
              </tr>
              <tr>
                  <td>Slope: </td>
                  <td>""" + slope + """</td>
              </tr>
              <tr>
                  <td>Exercise induced angina: </td>
                  <td>""" + exang + """</td>
              </tr>
              <tr>
                  <td>Number of major vessels</td>
                  <td>""" + ca + """</td>
              </tr>
              </table>
              <p> This patient is diagnose as """ + outcome + """ with probability """ + str(round(prob[0][1], 2)) + """.
              </body>"""
              # <h3> Heart Disease Diagnosis <h3>
              # <p> Patient profile </p>
              #     <h5> Thalassemia: """ + thal + """</h5>
              #     <h5> Chest Pain: """ + cp + """</h5>
              #     <h5> Slope: """ + slope + """</h5>
              #     <h5> Exercise induced angina: """ + exang + """</h5>
              #     <h5> Number of major vessels (0-3) colored by flourosopy: """ + ca + """</h5>
              # <p> This patient is diagnose as """ + outcome + """ with probability """ + str(round(prob[0][1], 2)) + """.
              # </body>
    return results
if __name__ == '__main__':
    """Connect to Server"""
    HOST = "127.0.0.1"
    PORT = "4000"
    app.run(HOST, PORT)