"""
Development configuration and utilities for Forest Fire Detection project
"""
import json
from pathlib import Path
from typing import Dict, Any
class Config:
    """Project configuration management"""
    
    def __init__(self):
        self.project_root = Path.cwd()
        self.data_dir = self.project_root / "data"
        self.models_dir = self.project_root / "models"
        self.assets_dir = self.project_root / "assets"
        self.notebooks_dir = self.project_root / "notebooks"
        self.src_dir = self.project_root / "src"
        
        # Load or create configuration
        self.config_path = self.project_root / "config.json"
        self.load_config()
    
    def load_config(self) -> Dict[str, Any]:
        """Load configuration from file or create default"""
        if self.config_path.exists():
            with open(self.config_path, 'r') as f:
                self.config = json.load(f)
        else:
            self.config = self._get_default_config()
            self.save_config()
        
        return self.config
    
    def _get_default_config(self) -> Dict[str, Any]:
        """Get default project configuration"""
        return {
            "project_name": "Forest Fire Detection using FirenetCNN and XAI Techniques",
            "version": "1.0.0",
            "description": "Detect and classify forest fires with explainable AI",
            "model": {
                "input_size": [224, 224],
                "num_classes": 3,
                "class_labels": ["fire", "no_fire", "smoke"],
                "reverse_class_map": {"fire": 0, "no_fire": 1, "smoke": 2}
            },
            "gradcam": {
                "target_layer": "out_relu",
                "alpha": 0.5,
                "colormap": "cv2.COLORMAP_JET"
            },
            "app": {
                "title": "Forest Fire Detection - FirenetCNN",
                "port": 7860,
                "share": True
            },
            "paths": {
                "data_dir": "data",
                "models_dir": "models",
                "assets_dir": "assets",
                "notebooks_dir": "notebooks",
                "src_dir": "src"
            }
        }
    
    def save_config(self) -> None:
        """Save configuration to file"""
        with open(self.config_path, 'w') as f:
            json.dump(self.config, f, indent=2)
    
    def get_model_paths(self) -> Dict[str, str]:
        """Get all model file paths"""
        return {
            "modern": str(self.models_dir / "FirenetCNN.keras"),
            "legacy": str(self.models_dir / "FirenetCNN1.h5"),
            "alternative": str(self.models_dir / "firenet_model.h5")
        }
    
    def setup_directories(self) -> None:
        """Create necessary directories"""
        directories = [
            self.models_dir,
            self.assets_dir,
            self.notebooks_dir,
            self.src_dir,
            self.data_dir
        ]
        
        for directory in directories:
            directory.mkdir(parents=True, exist_ok=True)
    
    def validate_environment(self) -> bool:
        """Validate that required files and directories exist"""
        required_items = [
            self.notebooks_dir / "Fire_PredCopy.ipynb"
        ]
        
        for item in required_items:
            if not item.exists():
                print(f"⚠️  Warning: Required item not found: {item}")
        
        return all(item.exists() for item in required_items)
    
    def print_summary(self) -> None:
        """Print project structure summary"""
        print("=" * 60)
        print(f"🚀 {self.config['project_name']}")
        print("=" * 60)
        print(f"📝 Version: {self.config['version']}")
        print(f"📝 Description: {self.config['description']}")
        print()
        print("📂 Project Structure:")
        print(f"   • Models: {self.models_dir}/")
        print(f"   • Assets: {self.assets_dir}/")
        print(f"   • Notebooks: {self.notebooks_dir}/")
        print(f"   • Source: {self.src_dir}/")
        print(f"   • Data: {self.data_dir}/")
        print()
        print("🔧 Key Features:")
        print("   • FirenetCNN (MobileNetV2 based)")
        print("   • Grad-CAM Explainable AI")
        print("   • Gradio Web Interface")
        print("   • Image & Video Analysis")
        print("   • Model Conversion Tools")
        print("   • Full Documentation")
        print("=" * 60)
if __name__ == "__main__":
    config = Config()
    config.print_summary()