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app.py
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app.py
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import json
import pickle
from flask import Flask,request,app,jsonify,url_for,render_template
import numpy as np
import pandas as pd
app=Flask(__name__)
## Load the model
diabeticpred=pickle.load(open('diabetespred.pkl','rb'))
scalar=pickle.load(open('scaling.pkl','rb'))
@app.route('/')
def home():
return render_template('index.html')
@app.route('/predict_api',methods=['POST'])
def predict_api():
data=request.json['data']
print(data)
print(np.array(list(data.values())).reshape(1,-1))
new_data=scalar.transform(np.array(list(data.values())).reshape(1,-1))
output=diabeticpred.predict(new_data)
print(output[0])
return jsonify(output[0])
@app.route('/predict',methods=['POST'])
def predict():
data=[float(x) for x in request.form.values()]
final_input=scalar.transform(np.array(data).reshape(1,-1))
print(final_input)
output=diabeticpred.predict(final_input)[0]
res=""
if output==0:
res="You will not have Diabetes"
else:
res="You will have Diabetes"
return render_template("index.html",prediction_text=res)
if __name__=="__main__":
app.run(debug=True)