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import joblib
import pandas as pd
import streamlit as st
model = joblib.load('model (2).joblib')
unique_values = joblib.load('unique_values (2).joblib')
unique_CL = unique_values["Color"]
unique_SC = unique_values["Spectral_Class"]
def main():
st.title("My star type")
st.image("https://img.freepik.com/free-vector/different-types-stars-dark-space_1308-37762.jpg")
with st.form("questionaire"):
K = st.slider('Temperature',min_value=1500,max_value=40000)
L = st.slider('Relative Luminosity',min_value=0,max_value=1000000)
R = st.slider('Relative Radius',min_value=0,max_value=2000)
AM = st.slider('Absolute Magnitude',min_value=0,max_value=25)
Color = st.selectbox("General Color of Spectrum",options=unique_CL)
Spectral_Class = st.selectbox("Spectral_Class",options=unique_SC)
clicked = st.form_submit_button("Predict type")
if clicked:
result = model.predict(pd.DataFrame({"Temperature(K)": [K],
"Relative Luminosity(Watts)": [L],
"Relative Radius(m)": [R],
"Absolute Magnitude": [AM],
"Color": [Color],
"Spectral_Class": [Spectral_Class]
})
)
if result[0] == 0:
result = "Red "
elif result[0] == 1:
result = "Brown"
elif result[0] == 2:
result = "White"
elif result[0] == 3:
result = "Main Sequence"
elif result[0] == 4:
result = "Main "
else:
result = "Iris-virginica"
st.write(f"Your predicted class is {result}")
if __name__=="__main__":
main() |