Spaces:
Sleeping
Sleeping
File size: 1,463 Bytes
d7e1d8f fac529d d7e1d8f 0be4ca4 d7e1d8f 0be4ca4 d7e1d8f 5835d49 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 |
from flask import Flask,request,render_template
import numpy as np
import sys
from sklearn.preprocessing import StandardScaler
from src.exception import CustomException
from src.pipeline.predict_pipeline import CustomData,PredictPipeline
application = Flask(__name__)
app = application
## route for home page
@app.route('/')
def index():
return render_template('index.html')
@app.route('/predictdata',methods=['GET','POST'])
def predict_datapoint():
try:
if request.method == 'GET':
return render_template('index.html')
else:
data=CustomData(
gender=request.form.get('gender'),
race_ethnicity=request.form.get('race_ethnicity'),
parental_level_of_education=request.form.get('parental_level_of_education'),
lunch=request.form.get('lunch'),
test_preparation_course=request.form.get('test_preparation_course'),
reading_score=request.form.get('reading_score'),
writing_score=request.form.get('writing_Score')
)
pred_df = data.get_data_as_data_frame()
predict_pipeline = PredictPipeline()
results = predict_pipeline.predict(pred_df)
return render_template('index.html',results=results[0])
except Exception as e:
raise CustomException(e,sys)
if __name__ == '__main__':
app.run(host='0.0.0.0',port=7860) |