Delete app_star.py
Browse files- app_star.py +0 -65
app_star.py
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import joblib
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import pandas as pd
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import streamlit as st
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CL_DICT = {'Red': 1,
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'Blue': 2,
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'White': 3,
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'Yellow': 4,
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'Orange': 5
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}
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SC_DICT = {'M': 1,
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'B': 2,
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'O': 3,
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'A': 4,
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'F': 5,
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'K': 6,
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'G': 7
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}
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model = joblib.load('model_star.joblib')
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unique_values = joblib.load('unique_values_star.joblib')
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unique_CL = unique_values["Color"]
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unique_SC = unique_values["Temperature"]
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st.title("My star type")
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st.image("https://study.com/academy/lesson/star-formation-main-sequence-dwarf-giant-stars.html")
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def main():
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st.text('For comparing all models of ML It can be used for prediction')
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with st.form("questionaire"):
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K = st.slider('Temperature',min_value=1900,max_value=40000)
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L = st.slider('Relative Luminosity',min_value=1900,max_value=40000)
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R = st.slider('Relative Radius',min_value=1900,max_value=40000)
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AM = st.slider('Absolute Magnitude',min_value=1900,max_value=40000)
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CL = st.selectbox("General Color of Spectrum",options=unique_CL)
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SC = st.selectbox("Spectral_Class",options=unique_SC)
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clicked = st.form_submit_button("Predict type")
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if clicked:
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result=model.predict(pd.DataFrame({"Temperature": [K],
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"Relative Luminosity": [L],
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"Relative Radiusducation": [R],
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"Absolute Magnitude": [AM],
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"General Color of Spectrum": [CL_DICT[CL]],
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"Spectral_Class": [SC_DICT[SC]]
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}))
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# Show prediction
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if result[0] == 0:
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result = "Red Dwarf"
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elif result[0] == 1:
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result = "Brown Dwarf"
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elif result[0] == 2:
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result = "White Dwarf"
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elif result[0] == 3:
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result = "Main Sequence"
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elif result[0] == 4:
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result = "Super Giants"
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elif result[0] == 5:
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result = "Hyper Giants"
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st.success("Your finished income is "+result)
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if __name__=="__main__":
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main()
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