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

# 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():
    return pd.read_csv('Reduced_final_teams.csv')

# Fuzzy match player name
def get_matching_player(name_from_file, player_list):
    name_lower = name_from_file.lower()
    for player in player_list:
        if player.lower() == name_lower:
            return player
    return None

# Horizontal bar chart
def plot_horizontal_bar(df, player1, player2):
    st.subheader("📊 Stat Comparison - Horizontal Bar Chart")
    num_cols = df.select_dtypes(include='number').columns
    df_num = df[num_cols].T
    df_num.columns = [player1, player2]
    df_num = df_num.sort_values(by=player1, ascending=False).head(15)

    fig, ax = plt.subplots(figsize=(10, 7))
    df_num.plot(kind='barh', ax=ax)
    ax.set_title(f"{player1} vs {player2} - Key Stats")
    ax.set_xlabel("Value")
    ax.set_ylabel("Metric")
    ax.legend(loc="lower right")
    st.pyplot(fig)

# Pie chart comparison
def plot_pie_charts(player1_data, player2_data, player1, player2):
    st.subheader("🥧 Batting vs Bowling Contribution")
    col1, col2 = st.columns(2)

    for col, player_data, player_name in zip([col1, col2], [player1_data, player2_data], [player1, player2]):
        batting_total = player_data.get('Runs_ODI', 0) + player_data.get('Runs_T20', 0) + player_data.get('Runs_Test', 0)
        bowling_total = player_data.get('Wickets_ODI', 0) + player_data.get('Wickets_T20', 0) + player_data.get('Wickets_Test', 0)

        labels = ['Batting', 'Bowling']
        sizes = [batting_total, bowling_total]

        fig, ax = plt.subplots()
        ax.pie(sizes, labels=labels, autopct='%1.1f%%', startangle=90, colors=['#4CAF50', '#2196F3'])
        ax.axis('equal')
        col.pyplot(fig)
        col.caption(f"{player_name}'s Batting vs Bowling")

# Bowling metric bar chart
def plot_bowling_comparison(df, player1, player2):
    st.subheader("🎯 Bowling Metrics Comparison")

    bowling_cols = [col for col in df.columns if 'Wickets' in col or 'Economy' in col or 'Bowling_Average' in col]
    df_bowling = df[bowling_cols].T
    df_bowling.columns = [player1, player2]
    df_bowling = df_bowling.dropna().sort_values(by=player1, ascending=False)

    fig, ax = plt.subplots(figsize=(10, 6))
    df_bowling.plot(kind='bar', ax=ax)
    ax.set_title("Bowling Stats")
    ax.set_ylabel("Value")
    ax.set_xticklabels(df_bowling.index, rotation=45, ha='right')
    ax.legend(loc="upper right")
    st.pyplot(fig)

# Main app
def main():
    st.set_page_config(layout="wide")
    st.title("Cricket Player Comparison Tool 🏏")

    df = load_data()
    model, encoder = load_model_and_encoder()
    player_list = df['Player'].tolist()

    # 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:
        name1_raw = img1.name.rsplit('.', 1)[0]
        name2_raw = img2.name.rsplit('.', 1)[0]

        player1_name = get_matching_player(name1_raw, player_list)
        player2_name = get_matching_player(name2_raw, player_list)

        if player1_name and player2_name and player1_name != player2_name:
            player1_data = df[df['Player'].str.lower() == player1_name.lower()].squeeze()
            player2_data = df[df['Player'].str.lower() == player2_name.lower()].squeeze()

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

            col3, col4 = st.columns(2)
            with col3:
                st.image(img1, caption=player1_name, use_container_width=True)
            with col4:
                st.image(img2, caption=player2_name, use_container_width=True)

            # Display comparison table
            comparison_df = pd.DataFrame([player1_data, player2_data])
            comparison_df.set_index('Player', inplace=True)
            st.subheader("📋 Full Stats Table")
            st.dataframe(comparison_df.T)

            # Visualizations
            plot_horizontal_bar(comparison_df, player1_name, player2_name)
            plot_pie_charts(player1_data, player2_data, player1_name, player2_name)
            plot_bowling_comparison(comparison_df, player1_name, player2_name)

        else:
            st.error("❌ Player names from image files don't match or are the same. Please check file names.")
    else:
        st.info("📸 Please upload two player images to continue.")

if __name__ == "__main__":
    main()