SuryaR4421/Spam_Classification

1import streamlit as st
2import numpy as np
3import pickle
4from tensorflow.keras.models import load_model
5
6model = load_model("model.h5")
7with open("count_vec.pkl", "rb") as f:
8    vectorizer = pickle.load(f)
9
10def run():
11    st.title("Prediction - Spam Message Detection Model")
12    st.write("---")
13    st.image('ham_or_spam.jpg')
14    
15    user_input = st.text_area("Enter the message to check for spam")
16
17    if st.button("Predict"):
18        if user_input:
19            user_input_vectorized = vectorizer.transform([user_input])
20            
21            prediction = model.predict(user_input_vectorized)
22            prediction_class = np.argmax(prediction, axis=1)[0]
23
24            if prediction_class == 1:
25                st.error("This message is predicted to be SPAM!")
26            else:
27                st.success("This message is NOT spam.")
28        else:
29            st.warning("Please enter a message to classify.")
30
31if __name__ == '__main__':
32    run()
33