app_rock_mine.py

# -*- coding: utf-8 -*-
"""app_Rock_mine.ipynb

Automatically generated by Colab.

Original file is located at
    https://colab.research.google.com/drive/19cYlXu5oldZgmQpFmr4N9JapuvWklFN6
"""

import streamlit as st
import numpy as np
import pickle

# Load the trained model
with open('model1 (1).pkl', 'rb') as file:
    model = pickle.load(file)

# Title
st.title("Rock vs Mine Prediction App")

st.markdown("""
Please enter the 60 sonar signal values (range: 0.0 to 1.0) below to predict whether the object is a **Rock** or a **Mine**.
""")

# Input fields
input_data = []
for i in range(60):
    value = st.number_input(f"Feature {i+1}", min_value=0.0, max_value=1.0, step=0.01, value=0.5, key=i)
    input_data.append(value)

# Predict button
if st.button("Predict"):
    input_array = np.array(input_data).reshape(1, -1)
    prediction = model.predict(input_array)[0]

    if prediction == 1:
        st.write("Prediction: Mine")
    else:
        st.write("Prediction: Rock")