app.py

from flask import Flask, render_template, request, jsonify
import joblib
import numpy as np

app = Flask(__name__)


@app.route("/", methods=['GET', 'POST'])
def iris_prediction():
    if request.method == 'GET':
        return render_template("iris-prediction.html")
    elif request.method == 'POST':
        print(dict(request.form))
        iris_features = dict(request.form).values() #string
        iris_features = np.array([float(x) for x in iris_features]) #float
        model, std_scaler = joblib.load("model-development/iris-classification-using-logistic-regression.pkl")
        iris_features = std_scaler.transform([iris_features])
        print(iris_features)
        result = model.predict(iris_features)
        iris = {
            '0': 'Iris Setosa',
            '1': 'Iris Versicolor',
            '2': 'Iris Virginica'
        }
        result = iris[str(result[0])]
        return render_template('iris-prediction.html', result=result)
    else:
        return "Unsupported Request Method"


if __name__ == '__main__':
    app.run(port=5000, debug=True)