| 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 = 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]})) |
| |
| result = 'low' if result[0] == 1 else 'high' |
| st.success("Predict Type of Client is "+result) |
| |
| |
| if __name__ == "__main__": |
| main() |
