"""
EcoPulse: Region Comparison Tool
Compares greenery percentages between two different satellite images and generates a visual report.
"""
import argparse
import os
import cv2
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
from src.pipeline import EcoPulsePipeline
from src.visualization import create_greenery_overlay

def compare_regions(config_path, image_a_path, image_b_path):
    # Validate file paths upfront (before the ~30s model load)
    for label, path in [("image_a", image_a_path), ("image_b", image_b_path)]:
        if not os.path.exists(path):
            raise FileNotFoundError(f"{label} not found: {path}")

    print("=" * 60)
    print("  EcoPulse: Region Comparison")
    print("=" * 60)

    pipeline = EcoPulsePipeline(config_path)
    
    print(f"\nProcessing Area A: {os.path.basename(image_a_path)}...")
    img_a, results_a = pipeline.process_image(image_a_path)
    
    print(f"Processing Area B: {os.path.basename(image_b_path)}...")
    img_b, results_b = pipeline.process_image(image_b_path)
    
    pct_a = results_a['greenery_percentage']
    pct_b = results_b['greenery_percentage']
    
    diff = pct_a - pct_b
    more_green = "Area A" if diff > 0 else "Area B"
    
    print(f"\n{'='*60}")
    print(f"  COMPARISON SUMMARY")
    print(f"{'='*60}")
    print(f"  Area A Greenery: {pct_a:.2f}%")
    print(f"  Area B Greenery: {pct_b:.2f}%")
    print(f"  Difference:      {abs(diff):.2f}%")
    print(f"  Result:          {more_green} is more vegetated.")
    print(f"{'='*60}\n")
    
    # --- Visualization Generation ---
    output_dir = pipeline.config['paths']['output_figures']
    os.makedirs(output_dir, exist_ok=True)
    
    comp_a, _ = create_greenery_overlay(img_a, results_a['mask_classifications'])
    comp_b, _ = create_greenery_overlay(img_b, results_b['mask_classifications'])
    
    fig, axes = plt.subplots(1, 2, figsize=(16, 8))
    
    axes[0].imshow(comp_a)
    axes[0].set_title(f"Area A: {pct_a:.1f}% Greenery", fontsize=16)
    axes[0].axis('off')
    
    axes[1].imshow(comp_b)
    axes[1].set_title(f"Area B: {pct_b:.1f}% Greenery", fontsize=16)
    axes[1].axis('off')
    
    fig.suptitle(f"EcoPulse Region Comparison\n{more_green} is more vegetated by {abs(diff):.1f}%", fontsize=20)
    plt.tight_layout()
    
    vis_path = os.path.join(output_dir, "region_comparison.png")
    plt.savefig(vis_path, bbox_inches='tight', dpi=150)
    plt.close()
    
    # Save a small report
    report_path = os.path.join(output_dir, "region_comparison_report.csv")
    df = pd.DataFrame({
        'Region': ['Area A', 'Area B'],
        'Image': [image_a_path, image_b_path],
        'Greenery_Percentage': [pct_a, pct_b]
    })
    df.to_csv(report_path, index=False)
    
    print(f"Visual Report saved to: {vis_path}")
    print(f"Data Report saved to: {report_path}")

if __name__ == "__main__":
    parser = argparse.ArgumentParser(description="Compare greenery between two images")
    parser.add_argument("--config", default="config/config.yaml", help="Path to config")
    parser.add_argument("--image_a", required=True, help="Path to first image")
    parser.add_argument("--image_b", required=True, help="Path to second image")
    args = parser.parse_args()
    
    compare_regions(args.config, args.image_a, args.image_b)