app.py

import pickle
import sklearn
import numpy as np
import pandas as pd
import streamlit as st

model_file = 'model-6.pkl'
try:
    with open(model_file,'rb') as file:
        model = pickle.load(file)
except FileNotFoundError:
    st.error("The file was not found or may be its corrupted")

st.title("IRIS FLOWER CLASSIFICATION")
st.header("Enter the features for your prediction")

sepal_length = st.number_input("Sepal length (cm):",min_value=0.0,max_value=10.0)
sepal_width = st.number_input("Sepal Width (cm):",min_value=0.0,max_value=10.0)
petal_length = st.number_input("Petal length (cm):",min_value=0.0,max_value=10.0)
petal_width = st.number_input("Petal Width (cm):",min_value=0.0,max_value=10.0)

if st.button("PREDICT") :
    features = np.array([[sepal_length,sepal_width,petal_length,petal_width]])
    prediction = model.predict(features)[0]

    st.subheader("Prediction has been made: ")
    st.write("The prediction for your given parameters is:",prediction)