client / app.py
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import joblib
import pandas as pd
import streamlit as st
model = joblib.load('model.joblib')
unique_values = joblib.load('unique_values.joblib')
unique_sex = unique_values["sex"]
unique_country = unique_values["country"]
unique_returning = unique_values["returning"]
unique_GImg1 = unique_values["GImg1"]
unique_GImg2 = unique_values["GImg2"]
unique_GImg3 = unique_values["GImg3"]
unique_PImg1 = unique_values["PImg1"]
unique_PImg2 = unique_values["PImg2"]
unique_PImg3 = unique_values["PImg3"]
unique_PImg4= unique_values["PImg4"]
unique_PImg5 = unique_values["PImg5"]
unique_TAudio1 = unique_values["TAudio1"]
unique_TAudio2 = unique_values["TAudio2"]
unique_TAudio3 = unique_values["TAudio3"]
unique_QAudio1 = unique_values["QAudio1"]
unique_QAudio2 = unique_values["QAudio2"]
unique_QAudio3 = unique_values["QAudio3"]
unique_Proxemics = unique_values["Proxemics"]
def main():
st.title("Non verbal tourists data")
with st.form("questionaire"):
sex = st.selectbox("Sex", options = unique_sex)
age = st.slider("Age", min_value = 20, max_value = 90)
country = st.selectbox("Country of the client United Nations admitted countries", options = unique_country)
returning = st.selectbox(" If the client is returning ", options = unique_returning)
GImg1 = st.selectbox("Handshake Indifferent", options = unique_GImg1)
GImg2 = st.selectbox("Hug Indifferent", options = unique_GImg2)
GImg3 = st.selectbox("Kiss Indifferent", options = unique_GImg3)
PImg1 = st.selectbox("Consent posture Indifferent", options = unique_PImg1)
PImg2 = st.selectbox("Interest posture Indifferent", options = unique_PImg2)
PImg3 = st.selectbox("Neutral posture Indifferent", options = unique_PImg3)
PImg4 = st.selectbox("Reflexive posture Indifferent", options = unique_PImg4)
PImg5 = st.selectbox("Negative posture Indifferent", options = unique_PImg5)
Tense= st.slider("Observed emotional clime", min_value = 1, max_value = 10)
Hostile = st.slider("friendly Observed emotional clime", min_value = 1, max_value = 10)
Authoritative = st.slider("anarchic Observed emotional clime", min_value = 1, max_value = 10)
TAudio1 = st.selectbox("Authoritative Indifferent", options = unique_TAudio1)
TAudio2 = st.selectbox("Sarcastic Indifferent", options = unique_TAudio2)
TAudio3 = st.selectbox("Friendly Indifferent", options = unique_TAudio3)
QAudio1 = st.selectbox("Spitting Indifferent", options = unique_QAudio1)
QAudio2 = st.selectbox("Hum Indifferent", options = unique_QAudio1)
QAudio3 = st.selectbox("Sigh Indifferent", options = unique_QAudio1)
Proxemics = st.selectbox("Physical distance preferred for the client", options = unique_Proxemics)
# clicked==True only when the button is clicked
clicked = st.form_submit_button("Predict Type of Client")
if clicked:
result=model.predict(pd.DataFrame({"sex":[sex],
"age":[age],
"country":[country],
"returning":[returning],
"GImg1":[GImg1],
"GImg2":[GImg2],
"GImg3":[GImg3],
"PImg1":[PImg1],
"PImg2":[PImg2],
"PImg3":[PImg3],
"PImg4":[PImg4],
"PImg5":[PImg5],
"Tense.relaxed":[Tense],
"Hostile.friendly":[Hostile],
"Authoritative.anarchic":[Authoritative],
"TAudio1":[TAudio1],
"TAudio2":[TAudio2],
"TAudio3":[TAudio3],
"QAudio1":[QAudio1],
"QAudio2":[QAudio1],
"QAudio3":[QAudio1],
"Proxemics":[Proxemics]}))
# Show prediction
result = 'low' if result[0] == 1 else 'high'
st.success("Predict Type of Client is "+result) #แสดงผล
# Run main()
if __name__ == "__main__":
main()