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Stellar_Detection_App
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import streamlit as st
import pandas as pd
import numpy as np
import pickle
import base64
import seaborn as sns
import matplotlib.pyplot as plt

st.write("""
# Stellar Detection App

Stellar detection App adalah aplikasi untuk mendeteksi bintang star dan galaxy.
 
Aplikasi ini mendeteksi bintang menggunakan data Stellar Classification.

""")

url_dataset = f'<a href="churn_data.csv">Download Dataset CSV File</a>'
st.markdown(url_dataset, unsafe_allow_html=True)

def user_input_features() :
    alpha = st.sidebar.slider('Alpha', 0.005528,359.99981)
    delta = st.sidebar.slider('Delta', -18.785328,83.000519)
    u = st.sidebar.slider('U', -9999.0,32.78139)
    g = st.sidebar.slider('G', -9999.0,31.60224)
    r = st.sidebar.slider('R', 9.82207,29.57186)
    i = st.sidebar.slider('I', 9.469903,32.14147)
    z = st.sidebar.slider('Z', -9999.0,29.38374)
    redshift = st.sidebar.slider('Redshift', -0.009971,7.011245)

    data = {'alpha':[alpha], 
            'delta':[delta],
            'u':[u],
            'g':[g],
            'r':[r],
            'i':[i],
            'z':[z],
            'redshift':[redshift]}

    features = pd.DataFrame(data)
    return features

input_df = user_input_features()


star_raw = pd.read_csv('star_classification.csv')
star_raw.fillna(0, inplace=True)
star = star_raw.drop(columns=['class'])
df = pd.concat([input_df,star],axis=0)


df = df[:1] # Selects only the first row (the user input data)
df.fillna(0, inplace=True)

features = ['alpha', 'delta', 'u', 'g', 'r', 'i', 'z', 'redshift']

df = df[features]


st.subheader('User Input features')
st.write(df)

load_clf = pickle.load(open('stellar_clf.pkl', 'rb'))
detect = load_clf.predict(df)
detect_proba = load_clf.predict_proba(df)
star_labels = np.array(['Not Star','Star'])
st.subheader('Detection')
st.write(star_labels[detect[0]])
st.subheader('Detection Probability')
df_prob = pd.DataFrame(data = detect_proba,
                    index = ['Probability'],
                    columns = star_labels)
st.write(df_prob)