| # import streamlit as st | |
| # import pickle | |
| # import sklearn | |
| # from sklearn.preprocessing import RobustScaler, OneHotEncoder, LabelEncoder | |
| # from sklearn.neighbors import KNeighborsClassifier | |
| # import pandas as pd | |
| # import numpy as np | |
| # import matplotlib.pyplot as plt | |
| # # st.markdown(""" | |
| # # <style> | |
| # # .stApp { | |
| # # background-image: url('https://huggingface.co/spaces/shubham680/DiabetesPrediction/resolve/main/bg.jpg'); | |
| # # background-size: cover; | |
| # # background-repeat: no-repeat; | |
| # # background-attachment: fixed; | |
| # # } | |
| # # .stTitle { | |
| # # color: #ffffff; | |
| # # font-size: 36px; | |
| # # font-weight: bold; | |
| # # text-align: center; | |
| # # } | |
| # # </style> | |
| # # """, unsafe_allow_html=True) | |
| # st.title("Introvert/Extrovert Prediction App") | |
| # #with st.sidebar: | |
| # #st.header("Patient Information") | |
| # time_spent = st.number_input("🕒 Time Spent Alone",min_value=0,max_value=11,step=1) | |
| # stage_fear = st.selectbox("🎤 Stage Fear",["Yes","No"]) | |
| # social_event = st.number_input("🎉 Social Event Attendance",min_value=0,max_value=10,step=1) | |
| # going_outside = st.number_input("🚶♂️ Going Outside Frequency",min_value=0,max_value=7,step=1) | |
| # drained = st.selectbox("😓 Drained After Socializing",["Yes","No"]) | |
| # friends = st.number_input("👥 Friend Circle Size",min_value=0,max_value=15,step=1) | |
| # post_frequency = st.number_input("📱 Post Frequency on Social Media",min_value=0,max_value=10,step=1) | |
| # with open("rs.pkl", "rb") as f: | |
| # rs = pickle.load(f) | |
| # with open("ohe_drain.pkl", "rb") as f: | |
| # ohe_drain = pickle.load(f) | |
| # with open("ohe_stage.pkl", "rb") as f: | |
| # ohe_stage = pickle.load(f) | |
| # with open("le.pkl", "rb") as f: | |
| # le = pickle.load(f) | |
| # with open("knn.pkl", "rb") as f: | |
| # knn = pickle.load(f) | |
| # stage_encoded = ohe_stage.transform([[stage_fear]])[0] # gender encoded using one hot encoding | |
| # drain_encoded = ohe_drain.transform([[drained]])[0] | |
| # numeric_features = np.array([[time_spent, social_event, going_outside, friends, post_frequency]]) | |
| # scaled_features = rs.transform(numeric_features)[0] | |
| # st.write("Scaled Features:", scaled_features) | |
| # final_input = np.concatenate(( | |
| # scaled_features[:1], | |
| # stage_encoded, | |
| # scaled_features[1:3], | |
| # drain_encoded, | |
| # scaled_features[3:] | |
| # )).reshape(1, -1) | |
| # prediction_labels = { | |
| # 0: "Extrovert", | |
| # 1: "Introvert" | |
| # } | |
| # if st.button("🔍 Predict"): | |
| # prediction = knn.predict(final_input)[0] | |
| # result_label = prediction_labels.get(prediction, "Unknown") | |
| # # Styled result box | |
| # st.markdown( | |
| # f"<div class='prediction-box'><strong>Predicted Personality:</strong> {result_label}</div>", | |
| # unsafe_allow_html=True | |
| # ) | |
| import streamlit as st | |
| import pickle | |
| import numpy as np | |
| # --------- CSS Styling --------- | |
| st.markdown(""" | |
| <style> | |
| .stApp { | |
| background: linear-gradient(to right, #c9d6ff, #e2e2e2); | |
| font-family: 'Segoe UI', sans-serif; | |
| } | |
| .glass-card { | |
| background: rgba(255, 255, 255, 0.6); | |
| padding: 2rem; | |
| border-radius: 20px; | |
| box-shadow: 0 8px 32px rgba(31, 38, 135, 0.37); | |
| backdrop-filter: blur(10px); | |
| -webkit-backdrop-filter: blur(10px); | |
| border: 1px solid rgba(255, 255, 255, 0.18); | |
| margin-top: 2rem; | |
| } | |
| .title { | |
| font-size: 48px; | |
| font-weight: bold; | |
| text-align: center; | |
| background: linear-gradient(to right, #141E30, #243B55); | |
| -webkit-background-clip: text; | |
| -webkit-text-fill-color: transparent; | |
| } | |
| .predict-button button { | |
| background-color: #6c63ff; | |
| color: white; | |
| font-size: 18px; | |
| font-weight: 600; | |
| border-radius: 12px; | |
| padding: 0.6em 1.5em; | |
| margin-top: 1rem; | |
| } | |
| .result-box { | |
| animation: fadeIn 1s ease-in-out; | |
| background: #141E30; | |
| color: white; | |
| padding: 1.5em; | |
| border-radius: 15px; | |
| text-align: center; | |
| margin-top: 2rem; | |
| font-size: 22px; | |
| } | |
| @keyframes fadeIn { | |
| from {opacity: 0;} | |
| to {opacity: 1;} | |
| } | |
| </style> | |
| """, unsafe_allow_html=True) | |
| # --------- Title --------- | |
| st.markdown("<div class='title'>🧠 Introvert vs Extrovert Personality Predictor</div>", unsafe_allow_html=True) | |
| # --------- Input Form --------- | |
| with st.container(): | |
| st.markdown("<div class='glass-card'>", unsafe_allow_html=True) | |
| st.markdown("#### 👤 Input Your Social Behavior Details") | |
| col1, col2 = st.columns(2) | |
| with col1: | |
| time_spent = st.slider("🕒 Time Spent Alone", 0, 11, 5) | |
| stage_fear = st.radio("🎤 Stage Fear", ["Yes", "No"]) | |
| going_outside = st.slider("🚶 Going Outside Frequency", 0, 7, 3) | |
| with col2: | |
| social_event = st.slider("🎉 Social Event Attendance", 0, 10, 5) | |
| drained = st.radio("😓 Drained After Socializing", ["Yes", "No"]) | |
| friends = st.slider("👥 Friend Circle Size", 0, 15, 7) | |
| post_frequency = st.slider("📱 Social Media Post Frequency", 0, 10, 3) | |
| # --------- Load Pickles --------- | |
| with open("rs.pkl", "rb") as f: | |
| rs = pickle.load(f) | |
| with open("ohe_drain.pkl", "rb") as f: | |
| ohe_drain = pickle.load(f) | |
| with open("ohe_stage.pkl", "rb") as f: | |
| ohe_stage = pickle.load(f) | |
| with open("le.pkl", "rb") as f: | |
| le = pickle.load(f) | |
| with open("knn.pkl", "rb") as f: | |
| knn = pickle.load(f) | |
| # --------- Encoding & Scaling --------- | |
| stage_encoded = ohe_stage.transform([[stage_fear]])[0] | |
| drain_encoded = ohe_drain.transform([[drained]])[0] | |
| numeric_features = np.array([[time_spent, social_event, going_outside, friends, post_frequency]]) | |
| scaled_features = rs.transform(numeric_features)[0] | |
| final_input = np.concatenate(( | |
| scaled_features[:1], | |
| stage_encoded, | |
| scaled_features[1:3], | |
| drain_encoded, | |
| scaled_features[3:] | |
| )).reshape(1, -1) | |
| prediction_labels = {0: "🌟 Extrovert", 1: "🌙 Introvert"} | |
| st.markdown("</div>", unsafe_allow_html=True) # Close glass card | |
| # --- Prediction Button & Result --- | |
| result_placeholder = st.empty() # 👈 Reserve space near the button | |
| if st.button("🔍 Predict", key="predict", help="Click to see your personality"): | |
| prediction = knn.predict(final_input)[0] # --> return 1d array further taking it as scalar value | |
| proba = knn.predict_proba(final_input)[0] # --> returns 2d array containing both probablity taking as 1d array. | |
| label = prediction_labels.get(prediction, "❓ Unknown") | |
| confidence = proba[prediction] * 100 | |
| result_html = f""" | |
| <div class='result-box'> | |
| 🔮 <strong>Predicted Personality:</strong> {label}<br> | |
| 📊 <strong>Confidence:</strong> {confidence:.2f}% | |
| </div> | |
| """ | |
| result_placeholder.markdown(result_html, unsafe_allow_html=True) | |
| # # --- Prediction Button & Result --- | |
| # result_placeholder = st.empty() # 👈 Reserve space near the button | |
| # if st.button("🔍 Predict", key="predict", help="Click to see your personality"): | |
| # prediction = knn.predict(final_input)[0] | |
| # proba = knn.predict_proba(final_input)[0] | |
| # label = prediction_labels.get(prediction, "❓ Unknown") | |
| # result_html = f""" | |
| # <div class='result-box'> | |
| # 🔮 <strong>Predicted Personality:</strong> {label}<br><br> | |
| # 📊 <strong>Probabilities:</strong><br> | |
| # 🌟 Extrovert: {proba[0]*100:.2f}%<br> | |
| # 🌙 Introvert: {proba[1]*100:.2f}% | |
| # </div> | |
| # """ | |
| # result_placeholder.markdown(result_html, unsafe_allow_html=True) | |
| # # --- Prediction Button & Result --- | |
| # result_placeholder = st.empty() # 👈 Reserve space near the button | |
| # if st.button("🔍 Predict", key="predict", help="Click to see your personality"): | |
| # prediction = knn.predict(final_input)[0] | |
| # label = prediction_labels.get(prediction, "❓ Unknown") | |
| # result_html = f""" | |
| # <div class='result-box'> | |
| # 🔮 <strong>Predicted Personality:</strong> {label} | |
| # </div> | |
| # """ | |
| # result_placeholder.markdown(result_html, unsafe_allow_html=True) # 👈 result shows instantly in place | |