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| import joblib | |
| import pandas as pd | |
| 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 tourist data") | |
| with st.form("questionaire"): | |
| sex = st.selectbox("Sex",options = unique_sex) | |
| age = st.slider("Age",min_value=10,max_values=100) | |
| country = st.selectbox("Country of the client United Nations admitted countries",options = unique_country) | |
| 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) | |
| relaxed = st.slider("Observed emotional clime",min_value=1,max_values=10) | |
| Authoritative_anarchic = st.slider("anarchic Observed emotional clime",min_value=1,max_values=10) | |
| Hostile_friendly = st.slider("friendly Observed emotional clime",min_value=1,max_values=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 : A. intimate: 15cm-45cm; B. per-sonal: 46cm-122cm; C. social: 123cm-360cm; D. public: > 360cm",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], | |
| "GImg1" = [GImg1], | |
| "GImg2" = [GImg2], | |
| "GImg3" = [GImg3], | |
| "PImg1" = [PImg1], | |
| "PImg2" = [PImg2], | |
| "PImg3" = [PImg3], | |
| "PImg4" = [PImg4], | |
| "PImg5" = [PImg5], | |
| "Tense-relaxed" = [relaxed], | |
| "Authoritative-anarchic" = [Authoritative_anarchic], | |
| "Hostile-friendly" = [Hostile_friendly], | |
| "TAudio1" =[TAudio1], | |
| "TAudio2" = [TAudio2], | |
| "TAudio3" = [TAudio3], | |
| "QAudio1" = [QAudio1], | |
| "QAudio2" = [QAudio1], | |
| "QAudio3" = [QAudio1], | |
| "Proxemics" = [Proxemics])) | |
| st.success("Predict Type of Client" + result) | |
| if __name__ == "__main__" : | |
| main() |