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| import streamlit as st | |
| import joblib | |
| import numpy as np | |
| import warnings | |
| warnings.filterwarnings("ignore", message="X does not have valid feature names, but .* was fitted with feature names") | |
| # Load the model | |
| model = joblib.load("forest_model.pkl") | |
| # Define the predict_score function | |
| def predict_score(batting_team, bowling_team, runs, wickets, overs, runs_last_5, wickets_last_5): | |
| prediction_array = [] | |
| # Batting Team | |
| if batting_team == 'Chennai Super Kings': | |
| prediction_array = prediction_array + [1,0,0,0,0,0,0,0] | |
| elif batting_team == 'Delhi Daredevils': | |
| prediction_array = prediction_array + [0,1,0,0,0,0,0,0] | |
| elif batting_team == 'Kings XI Punjab': | |
| prediction_array = prediction_array + [0,0,1,0,0,0,0,0] | |
| elif batting_team == 'Kolkata Knight Riders': | |
| prediction_array = prediction_array + [0,0,0,1,0,0,0,0] | |
| elif batting_team == 'Mumbai Indians': | |
| prediction_array = prediction_array + [0,0,0,0,1,0,0,0] | |
| elif batting_team == 'Rajasthan Royals': | |
| prediction_array = prediction_array + [0,0,0,0,0,1,0,0] | |
| elif batting_team == 'Royal Challengers Bangalore': | |
| prediction_array = prediction_array + [0,0,0,0,0,0,1,0] | |
| elif batting_team == 'Sunrisers Hyderabad': | |
| prediction_array = prediction_array + [0,0,0,0,0,0,0,1] | |
| # Bowling Team | |
| if bowling_team == 'Chennai Super Kings': | |
| prediction_array = prediction_array + [1,0,0,0,0,0,0,0] | |
| elif bowling_team == 'Delhi Daredevils': | |
| prediction_array = prediction_array + [0,1,0,0,0,0,0,0] | |
| elif bowling_team == 'Kings XI Punjab': | |
| prediction_array = prediction_array + [0,0,1,0,0,0,0,0] | |
| elif bowling_team == 'Kolkata Knight Riders': | |
| prediction_array = prediction_array + [0,0,0,1,0,0,0,0] | |
| elif bowling_team == 'Mumbai Indians': | |
| prediction_array = prediction_array + [0,0,0,0,1,0,0,0] | |
| elif bowling_team == 'Rajasthan Royals': | |
| prediction_array = prediction_array + [0,0,0,0,0,1,0,0] | |
| elif bowling_team == 'Royal Challengers Bangalore': | |
| prediction_array = prediction_array + [0,0,0,0,0,0,1,0] | |
| elif bowling_team == 'Sunrisers Hyderabad': | |
| prediction_array = prediction_array + [0,0,0,0,0,0,0,1] | |
| prediction_array = prediction_array + [runs, wickets, overs, runs_last_5, wickets_last_5] | |
| prediction_array = np.array([prediction_array]) | |
| pred = model.predict(prediction_array) | |
| return int(round(pred[0])) | |
| # Create the Streamlit app | |
| def app(): | |
| st.title("IPL Score Predictor") | |
| # Get user input | |
| batting_team = st.selectbox("Select the batting team", ['Chennai Super Kings', 'Delhi Daredevils', 'Kings XI Punjab', 'Kolkata Knight Riders', 'Mumbai Indians', 'Rajasthan Royals', 'Royal Challengers Bangalore', 'Sunrisers Hyderabad']) | |
| bowling_team = st.selectbox("Select the bowling team", ['Chennai Super Kings', 'Delhi Daredevils', 'Kings XI Punjab', 'Kolkata Knight Riders', 'Mumbai Indians', 'Rajasthan Royals', 'Royal Challengers Bangalore', 'Sunrisers Hyderabad']) | |
| runs = st.number_input("Enter the runs scored", value=0) | |
| wickets = st.number_input("Enter the wickets lost", value=0) | |
| overs = st.number_input("Enter the number of overs played", value=0.0) | |
| runs_last_5 = st.number_input("Enter the runs scored in the last 5 overs", value=0) | |
| wickets_last_5 = st.number_input("Enter the wickets lost in the last 5 overs", value=0) | |
| # Predict the score | |
| if st.button("Predict"): | |
| score = predict_score(batting_team, bowling_team, runs, wickets, overs, runs_last_5, wickets_last_5) | |
| st.write(f"Predicted score for {batting_team} against {bowling_team}: {score}") | |
| # Run the app | |
| if __name__ == "__main__": | |
| app() | |
| # App creator information | |
| # Add app creator information | |
| st.markdown("<p style='text-align: center; font-size: 18px; margin-top: 50px;'>Created by</p>", unsafe_allow_html=True) | |
| st.markdown("<h3 style='text-align: center; font-size: 30px;'>Manish Choudhary</h3>", unsafe_allow_html=True) | |
| st.markdown("<p style='text-align: center; font-size: 18px;'>Follow me on <a href='https://www.instagram.com/expert.py' target='_blank'>Instagram</a></p>", unsafe_allow_html=True) | |