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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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model = joblib.load('model.joblib') |
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unique_values = joblib.load('unique_values.joblib') |
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unique_sex = unique_values["sex"] |
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unique_country = unique_values["country"] |
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unique_returning = unique_values["returning"] |
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unique_GImg1 = unique_values["GImg1"] |
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unique_GImg2 = unique_values["GImg2"] |
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unique_GImg3 = unique_values["GImg3"] |
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unique_PImg1 = unique_values["PImg1"] |
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unique_PImg2 = unique_values["PImg2"] |
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unique_PImg3 = unique_values["PImg3"] |
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unique_PImg4= unique_values["PImg4"] |
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unique_PImg5 = unique_values["PImg5"] |
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unique_TAudio1 = unique_values["TAudio1"] |
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unique_TAudio2 = unique_values["TAudio2"] |
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unique_TAudio3 = unique_values["TAudio3"] |
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unique_QAudio1 = unique_values["QAudio1"] |
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unique_QAudio2 = unique_values["QAudio2"] |
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unique_QAudio3 = unique_values["QAudio3"] |
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unique_Proxemics = unique_values["Proxemics"] |
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unique_Authoritative = unique_values["Authoritative .anarchic"] |
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def main(): |
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st.title("Adult Income") |
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with st.form("questionaire"): |
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sex = st.selectbox("Sex",options = unique_sex) |
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age = st.slider("Age",min_value=10,max_values=100) |
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country = st.selectbox("Country of the client United Nations admitted countries",options = unique_country) |
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GImg1 = st.selectbox("Handshake Indifferent",options = unique_GImg1) |
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GImg2 = st.selectbox("Hug Indifferent",options = unique_GImg2) |
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GImg3 = st.selectbox("Kiss Indifferent",options = unique_GImg3) |
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PImg1 = st.selectbox("Consent posture Indifferent",options = unique_PImg1) |
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PImg2 = st.selectbox("Interest posture Indifferent",options = unique_PImg2) |
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PImg3 = st.selectbox("Neutral posture Indifferent",options = unique_PImg3) |
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PImg4 = st.selectbox("Reflexive posture Indifferent",options = unique_PImg4) |
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PImg5 = st.selectbox("Negative posture Indifferent",options = unique_PImg5) |
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Tense= st.slider("Observed emotional clime",min_value=1,max_values=10) |
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Authoritativean = st.selectbox("anarchic Observed emotional clime",options = unique_Authoritativean) |
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Hostile = st.slider("friendly Observed emotional clime",min_value=1,max_values=10) |
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TAudio1 = st.selectbox("Authoritative Indifferent",options = unique_TAudio1) |
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TAudio2 = st.selectbox("Sarcastic Indifferent",options = unique_TAudio2) |
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TAudio3 = st.selectbox("Friendly Indifferent",options = unique_TAudio3) |
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QAudio1 = st.selectbox("Spitting Indifferent",options = unique_QAudio1) |
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QAudio2 = st.selectbox("Hum Indifferent",options = unique_QAudio1) |
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QAudio3 = st.selectbox("Sigh Indifferent",options = unique_QAudio1) |
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Proxemics = st.selectbox("Physical distance preferred for the client : A. intimate: 15cm-45cm; B. per-sonal: 46cm-122cm; C. social:123cm-360cm; D. public: > 360cm",options = unique_Proxemics) |
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clicked = st.form_submit_button("Predict Type of Client") |
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if clicked: |
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result=model.predict(pd.DataFrame({"sex":[sex], |
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"age": [age], |
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"country": [country], |
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"GImg1" : [GImg1], |
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"GImg2" : [GImg2], |
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"GImg3" : [GImg3], |
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"PImg1" : [PImg1], |
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"PImg2" : [PImg2], |
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"PImg3" : [PImg3], |
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"PImg4" : [PImg4], |
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"PImg5" : [PImg5], |
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"Tense-relaxed" :[Tense], |
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"Authoritative-anarchic" : [Authoritative], |
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"Hostile-friendly" : [Hostile], |
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"TAudio1" : [TAudio1], |
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"TAudio2" : [TAudio2], |
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"TAudio3" : [TAudio3], |
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"QAudio1" : [QAudio1], |
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"QAudio2" : [QAudio1], |
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"QAudio3" : [QAudio1], |
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"Proxemics" : [Proxemics]})) |
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result = 'low' if result[0] == 1 else 'high' |
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st.success("Predict Type of Client is "+result) |
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if __name__ == "__main__": |
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main() |
