Error in Machine Learning model into Flask Web Applications - machine-learning

Question

I have created my machine learning model for heart disease prediction and now I want to deploy in my web application using FLASK. The Dataset as been acquired from Kaggle. Whenever I run the application I have some issues with my code whenever I execute it, it says:
C:\Users\Surface\Desktop\Flask_app>python app.py File "app.py", line 42
x_data = request.form['x_data']
^
IndentationError: unindent does not match any outer indentation level
Can anyone guide me Thankyou :)
from flask import Flask,render_template,url_for,request
import numpy as np
import pandas as pd
import pickle
from sklearn.ensemble import RandomForestClassifier
from sklearn.model_selection import train_test_split
from sklearn.externals import joblib
app = Flask(__name__)
#app.route('/')
def home():
return render_template('home.html')
#app.route('/predict',method=['POST'])
def predict():
df = pd.read_csv("heart.csv")
df = df.drop(columns = ['cp', 'thal', 'slope'])
#features and labels
y = df.target.values
x_data = df.drop(['target'], axis = 1)
#EXTRACT Features
x = (x_data - np.min(x_data)) / (np.max(x_data) - np.min(x_data)).values
x_train, x_test, y_train, y_test = train_test_split(x,y,test_size = 0.2,random_state=0)
# Random Forest Classification
from sklearn.ensemble import RandomForestClassifier
rf = RandomForestClassifier(n_estimators = 1000, random_state = 1)
rf.fit(x_train.T, y_train.T)
print("Random Forest Algorithm Accuracy Score : {:.2f}%".format(rf.score(x_test.T,y_test.T)*100))
#persist model in a standard format
from sklearn.externals import joblib
joblib.dump(rf, 'HAP_model.pkl')
HAP_model = open('HAP_model.pkl','rb')
rf = joblib.load(HAP_model)
if request.method=='POST':
x_data = request.form['x_data']
data = [df.drop(['target'], axis = 1)]
vect = rf.transform(data).toarray()
my_prediction = rf.predict(vect)
return render_template('result.html',prediction = my_prediction)
if __name__ == '__main__':
app.run(debug=True)