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from flask import flask,render,template, request
import joblib
sklearn.linear_model import LogisticRegression
app=flask(__name__)
model.joblib.load('iris_model.pkl')
pred=model.predict([[5,5,0,4.1,3]])
result=pred[0]
@app.route('/')
def home():
return render_template('index.html')
@app.route('/predict', methods=['POST'])
def predict():
if request.method == 'POST':
# Example: expecting 4 inputs from form (Sepal length, Sepal width, Petal length, Petal width)
sl = float(request.form['sepal_length'])
sw = float(request.form['sepal_width'])
pl = float(request.form['petal_length'])
pw = float(request.form['petal_width'])
# Make prediction
pred = model.predict([[sl, sw, pl, pw]])
result = pred[0] # Predicted class (0,1,2)
return render_template('index.html', result=result)
if __name__ == '__main__':
app.run(debug=True, host='0.0.0.0') |