pages/2player_comparison.py

import streamlit as st
import pandas as pd
import pickle
import matplotlib.pyplot as plt
import seaborn as sns

# Load model and encoder
@st.cache_resource
def load_model_and_encoder():
    with open('best_rf_pipeline.pkl', 'rb') as f:
        model = pickle.load(f)
    with open('label_encoder.pkl', 'rb') as f:
        encoder = pickle.load(f)
    return model, encoder

# Load player dataset
@st.cache_data
def load_data():
    df = pd.read_csv('Reduced_final_teams.csv')
    return df

# Main App
def main():
    st.title("Cricket Player Comparison Tool 🏏")
    st.write("Upload two player images and compare their performance visually.")

    df = load_data()
    model, encoder = load_model_and_encoder()

    # Upload Images
    col1, col2 = st.columns(2)
    with col1:
        img1 = st.file_uploader("Upload Image for Player 1", type=['png', 'jpg', 'jpeg'], key='img1')
    with col2:
        img2 = st.file_uploader("Upload Image for Player 2", type=['png', 'jpg', 'jpeg'], key='img2')

    if img1 and img2:
        # Placeholder: Extract player name from uploaded file name
        player1_name = img1.name.split('.')[0]
        player2_name = img2.name.split('.')[0]

        if player1_name in df['Player'].values and player2_name in df['Player'].values:
            player1_data = df[df['Player'] == player1_name].squeeze()
            player2_data = df[df['Player'] == player2_name].squeeze()

            st.success(f"Comparing **{player1_name}** vs **{player2_name}**")

            # Combine both players into one DataFrame for visualization
            comparison_df = pd.DataFrame([player1_data, player2_data])
            comparison_df.set_index('Player', inplace=True)

            # Display Side-by-Side Metrics
            st.subheader("🔍 Key Metrics")
            st.dataframe(comparison_df.T)

            # Radar chart / Barplot for comparison
            st.subheader("📊 Visual Comparison")
            num_cols = comparison_df.select_dtypes(include='number').columns.tolist()

            # Plot
            plt.figure(figsize=(10, 5))
            comparison_df[num_cols].T.plot(kind='bar', figsize=(10, 6))
            plt.title(f"Stat Comparison: {player1_name} vs {player2_name}")
            plt.ylabel("Metric Value")
            plt.xticks(rotation=45)
            st.pyplot(plt.gcf())
        else:
            st.error("Player names extracted from images do not match any in the dataset. Ensure filenames match player names in the CSV.")

if __name__ == "__main__":
    main()