"""
BackgroundFX Pro Configuration Module
Centralizes all application configuration and environment variable handling

Note: Named 'app_config.py' to avoid conflicts with existing 'Configs/' folder
"""

import os
from dataclasses import dataclass, asdict, field
from typing import Dict, Any, Optional, List
from pathlib import Path
import logging
import json
import yaml

logger = logging.getLogger(__name__)

@dataclass
class ProcessingConfig:
    """
    Main processing configuration with environment variable defaults
    """
    # Application info
    app_name: str = "BackgroundFX Pro"
    version: str = "2.0.0"
    
    # Frame processing settings
    keyframe_interval: int = int(os.getenv('KEYFRAME_INTERVAL', '5'))
    frame_skip: int = int(os.getenv('FRAME_SKIP', '1'))
    
    # Memory management
    memory_cleanup_interval: int = int(os.getenv('MEMORY_CLEANUP_INTERVAL', '30'))
    memory_threshold_mb: int = int(os.getenv('MEMORY_THRESHOLD_MB', '1024'))
    
    # Video constraints
    max_video_length: int = int(os.getenv('MAX_VIDEO_LENGTH', '300'))  # seconds
    max_video_resolution: str = os.getenv('MAX_VIDEO_RESOLUTION', '1920x1080')
    min_video_fps: int = int(os.getenv('MIN_VIDEO_FPS', '15'))
    max_video_fps: int = int(os.getenv('MAX_VIDEO_FPS', '60'))
    
    # Quality settings
    quality_preset: str = os.getenv('QUALITY_PRESET', 'balanced')
    
    # Model settings
    sam2_model_size: str = os.getenv('SAM2_MODEL_SIZE', 'large')  # tiny, small, base, large
    matanyone_precision: str = os.getenv('MATANYONE_PRECISION', 'fp32')  # fp16, fp32
    model_device: str = os.getenv('MODEL_DEVICE', 'auto')  # auto, cuda, cpu
    
    # MatAnyone specific settings
    matanyone_enabled: bool = os.getenv('MATANYONE_ENABLED', 'false').lower() == 'true'
    matanyone_model_path: str = os.getenv('MATANYONE_MODEL_PATH', 'models/matanyone/checkpoint.pth')
    matanyone_threshold: float = float(os.getenv('MATANYONE_THRESHOLD', '0.5'))
    matanyone_hair_refinement: bool = os.getenv('MATANYONE_HAIR_REFINEMENT', 'true').lower() == 'true'
    matanyone_edge_enhancement: bool = os.getenv('MATANYONE_EDGE_ENHANCEMENT', 'true').lower() == 'true'
    matanyone_detail_refinement: bool = os.getenv('MATANYONE_DETAIL_REFINEMENT', 'true').lower() == 'true'
    matanyone_morphology_ops: bool = os.getenv('MATANYONE_MORPHOLOGY_OPS', 'true').lower() == 'true'
    matanyone_morphology_kernel_size: int = int(os.getenv('MATANYONE_MORPHOLOGY_KERNEL_SIZE', '5'))
    
    # Component paths for separate mask files
    hair_masks_dir: str = os.getenv('HAIR_MASKS_DIR', 'assets/hair_masks')
    edge_masks_dir: str = os.getenv('EDGE_MASKS_DIR', 'assets/edge_masks')
    detail_masks_dir: str = os.getenv('DETAIL_MASKS_DIR', 'assets/detail_masks')
    use_component_masks: bool = os.getenv('USE_COMPONENT_MASKS', 'false').lower() == 'true'
    
    # MatAnyone component weights
    matanyone_weight_base: float = float(os.getenv('MATANYONE_WEIGHT_BASE', '1.0'))
    matanyone_weight_hair: float = float(os.getenv('MATANYONE_WEIGHT_HAIR', '1.2'))
    matanyone_weight_edge: float = float(os.getenv('MATANYONE_WEIGHT_EDGE', '1.5'))
    matanyone_weight_detail: float = float(os.getenv('MATANYONE_WEIGHT_DETAIL', '1.1'))
    
    # MatAnyone processing modes
    matanyone_processing_mode: str = os.getenv('MATANYONE_PROCESSING_MODE', 'refine')  # refine, replace, blend
    matanyone_blend_alpha: float = float(os.getenv('MATANYONE_BLEND_ALPHA', '0.7'))
    matanyone_trimap_enabled: bool = os.getenv('MATANYONE_TRIMAP_ENABLED', 'false').lower() == 'true'
    matanyone_trimap_dilation: int = int(os.getenv('MATANYONE_TRIMAP_DILATION', '10'))
    
    # Processing settings
    temporal_consistency: bool = os.getenv('TEMPORAL_CONSISTENCY', 'true').lower() == 'true'
    edge_refinement: bool = os.getenv('EDGE_REFINEMENT', 'true').lower() == 'true'
    mask_blur_radius: int = int(os.getenv('MASK_BLUR_RADIUS', '5'))
    confidence_threshold: float = float(os.getenv('CONFIDENCE_THRESHOLD', '0.85'))
    background_preset: str = os.getenv('BACKGROUND_PRESET', 'minimalist')
    
    # Mask processing attributes (ADDED)
    mask_gamma: float = float(os.getenv('MASK_GAMMA', '1.0'))
    mask_blur: int = int(os.getenv('MASK_BLUR', '0'))
    mask_threshold: float = float(os.getenv('MASK_THRESHOLD', '0.5'))
    mask_edge_softness: int = int(os.getenv('MASK_EDGE_SOFTNESS', '2'))
    mask_spill_suppression: float = float(os.getenv('MASK_SPILL_SUPPRESSION', '0.35'))
    
    # Hard cutoff thresholds for mask processing (ADDED)
    hard_low: float = float(os.getenv('HARD_LOW', '0.2'))
    hard_medium: float = float(os.getenv('HARD_MEDIUM', '0.5'))
    hard_high: float = float(os.getenv('HARD_HIGH', '0.8'))
    hard_threshold: float = float(os.getenv('HARD_THRESHOLD', '0.5'))
    
    # Morphological operations for mask processing (ADDED)
    dilate_px: int = int(os.getenv('DILATE_PX', '0'))
    erode_px: int = int(os.getenv('ERODE_PX', '0'))
    open_px: int = int(os.getenv('OPEN_PX', '0'))
    close_px: int = int(os.getenv('CLOSE_PX', '0'))
    morph_iterations: int = int(os.getenv('MORPH_ITERATIONS', '1'))
    
    # Edge processing attributes (ADDED)
    edge_blur_px: int = int(os.getenv('EDGE_BLUR_PX', '0'))
    edge_feather_px: int = int(os.getenv('EDGE_FEATHER_PX', '2'))
    edge_threshold: float = float(os.getenv('EDGE_THRESHOLD', '0.5'))
    edge_detect_method: str = os.getenv('EDGE_DETECT_METHOD', 'canny')
    
    # Tracking and temporal consistency attributes (ADDED)
    min_iou_to_accept: float = float(os.getenv('MIN_IOU_TO_ACCEPT', '0.3'))
    max_iou_distance: float = float(os.getenv('MAX_IOU_DISTANCE', '0.7'))
    min_track_length: int = int(os.getenv('MIN_TRACK_LENGTH', '3'))
    track_buffer_size: int = int(os.getenv('TRACK_BUFFER_SIZE', '30'))
    temporal_smoothing: float = float(os.getenv('TEMPORAL_SMOOTHING', '0.7'))
    motion_threshold: float = float(os.getenv('MOTION_THRESHOLD', '0.1'))
    
    # Segmentation refinement attributes (ADDED)
    refine_iterations: int = int(os.getenv('REFINE_ITERATIONS', '1'))
    refine_threshold: float = float(os.getenv('REFINE_THRESHOLD', '0.5'))
    use_crf: bool = os.getenv('USE_CRF', 'false').lower() == 'true'
    crf_iterations: int = int(os.getenv('CRF_ITERATIONS', '5'))
    bilateral_sigma_color: float = float(os.getenv('BILATERAL_SIGMA_COLOR', '80.0'))
    bilateral_sigma_space: float = float(os.getenv('BILATERAL_SIGMA_SPACE', '10.0'))
    
    # Feathering and blending attributes (ADDED)
    feather_amount: int = int(os.getenv('FEATHER_AMOUNT', '5'))
    blend_mode: str = os.getenv('BLEND_MODE', 'normal')
    alpha_matting: bool = os.getenv('ALPHA_MATTING', 'false').lower() == 'true'
    alpha_threshold: float = float(os.getenv('ALPHA_THRESHOLD', '0.5'))
    composite_mode: str = os.getenv('COMPOSITE_MODE', 'over')
    
    # Color correction attributes (ADDED)
    color_correct: bool = os.getenv('COLOR_CORRECT', 'false').lower() == 'true'
    brightness_adjust: float = float(os.getenv('BRIGHTNESS_ADJUST', '1.0'))
    contrast_adjust: float = float(os.getenv('CONTRAST_ADJUST', '1.0'))
    saturation_adjust: float = float(os.getenv('SATURATION_ADJUST', '1.0'))
    hue_shift: float = float(os.getenv('HUE_SHIFT', '0.0'))
    
    # Noise reduction attributes (ADDED)
    denoise: bool = os.getenv('DENOISE', 'false').lower() == 'true'
    denoise_strength: float = float(os.getenv('DENOISE_STRENGTH', '10.0'))
    median_filter_size: int = int(os.getenv('MEDIAN_FILTER_SIZE', '0'))
    gaussian_sigma: float = float(os.getenv('GAUSSIAN_SIGMA', '1.0'))
    
    # Performance optimization attributes (ADDED)
    use_gpu: bool = os.getenv('USE_GPU', 'true').lower() == 'true'
    gpu_device_id: int = int(os.getenv('GPU_DEVICE_ID', '0'))
    use_fp16: bool = os.getenv('USE_FP16', 'false').lower() == 'true'
    use_tensorrt: bool = os.getenv('USE_TENSORRT', 'false').lower() == 'true'
    use_quantization: bool = os.getenv('USE_QUANTIZATION', 'false').lower() == 'true'
    
    # Video codec attributes (ADDED)
    use_nvenc: bool = os.getenv('USE_NVENC', 'false').lower() == 'true'
    prefer_mp4: bool = os.getenv('PREFER_MP4', 'true').lower() == 'true'
    video_codec: str = os.getenv('VIDEO_CODEC', 'mp4v')
    audio_copy: bool = os.getenv('AUDIO_COPY', 'true').lower() == 'true'
    ffmpeg_path: str = os.getenv('FFMPEG_PATH', 'ffmpeg')
    
    # Model size constraints (ADDED)
    max_model_size: int = int(os.getenv('MAX_MODEL_SIZE', '0'))
    max_model_size_bytes: int = int(os.getenv('MAX_MODEL_SIZE_BYTES', '0'))
    
    # Temporal consistency and smoothing (COMPREHENSIVE)
    temporal_ema_alpha: float = float(os.getenv('TEMPORAL_EMA_ALPHA', '0.7'))
    temporal_window_size: int = int(os.getenv('TEMPORAL_WINDOW_SIZE', '5'))
    temporal_blend_factor: float = float(os.getenv('TEMPORAL_BLEND_FACTOR', '0.5'))
    temporal_consistency_threshold: float = float(os.getenv('TEMPORAL_CONSISTENCY_THRESHOLD', '0.8'))
    use_temporal_smoothing: bool = os.getenv('USE_TEMPORAL_SMOOTHING', 'true').lower() == 'true'
    temporal_buffer_frames: int = int(os.getenv('TEMPORAL_BUFFER_FRAMES', '10'))
    
    # Mask post-processing (COMPREHENSIVE)
    mask_min_area: int = int(os.getenv('MASK_MIN_AREA', '100'))
    mask_max_area: int = int(os.getenv('MASK_MAX_AREA', '0'))
    mask_fill_holes: bool = os.getenv('MASK_FILL_HOLES', 'true').lower() == 'true'
    mask_convex_hull: bool = os.getenv('MASK_CONVEX_HULL', 'false').lower() == 'true'
    mask_largest_component: bool = os.getenv('MASK_LARGEST_COMPONENT', 'true').lower() == 'true'
    mask_smooth_radius: int = int(os.getenv('MASK_SMOOTH_RADIUS', '0'))
    mask_binary_threshold: float = float(os.getenv('MASK_BINARY_THRESHOLD', '0.5'))
    mask_confidence_threshold: float = float(os.getenv('MASK_CONFIDENCE_THRESHOLD', '0.7'))
    
    # Contour processing (COMPREHENSIVE)
    contour_approx_epsilon: float = float(os.getenv('CONTOUR_APPROX_EPSILON', '0.01'))
    contour_min_points: int = int(os.getenv('CONTOUR_MIN_POINTS', '4'))
    contour_max_points: int = int(os.getenv('CONTOUR_MAX_POINTS', '0'))
    contour_smoothing: bool = os.getenv('CONTOUR_SMOOTHING', 'false').lower() == 'true'
    contour_simplification: bool = os.getenv('CONTOUR_SIMPLIFICATION', 'false').lower() == 'true'
    
    # Trimap generation (COMPREHENSIVE)
    trimap_dilation_size: int = int(os.getenv('TRIMAP_DILATION_SIZE', '10'))
    trimap_erosion_size: int = int(os.getenv('TRIMAP_EROSION_SIZE', '5'))
    trimap_unknown_width: int = int(os.getenv('TRIMAP_UNKNOWN_WIDTH', '20'))
    trimap_confidence_threshold: float = float(os.getenv('TRIMAP_CONFIDENCE_THRESHOLD', '0.5'))
    use_trimap: bool = os.getenv('USE_TRIMAP', 'false').lower() == 'true'
    
    # SAM2 specific parameters (COMPREHENSIVE)
    sam2_points_per_side: int = int(os.getenv('SAM2_POINTS_PER_SIDE', '32'))
    sam2_pred_iou_thresh: float = float(os.getenv('SAM2_PRED_IOU_THRESH', '0.88'))
    sam2_stability_score_thresh: float = float(os.getenv('SAM2_STABILITY_SCORE_THRESH', '0.95'))
    sam2_crop_n_layers: int = int(os.getenv('SAM2_CROP_N_LAYERS', '0'))
    sam2_crop_n_points_downscale_factor: int = int(os.getenv('SAM2_CROP_N_POINTS_DOWNSCALE_FACTOR', '1'))
    sam2_min_mask_region_area: int = int(os.getenv('SAM2_MIN_MASK_REGION_AREA', '0'))
    sam2_use_m2m: bool = os.getenv('SAM2_USE_M2M', 'false').lower() == 'true'
    sam2_multimask_output: bool = os.getenv('SAM2_MULTIMASK_OUTPUT', 'true').lower() == 'true'
    
    # Background processing (COMPREHENSIVE)
    bg_blur_radius: int = int(os.getenv('BG_BLUR_RADIUS', '0'))
    bg_blur_type: str = os.getenv('BG_BLUR_TYPE', 'gaussian')
    bg_fill_mode: str = os.getenv('BG_FILL_MODE', 'stretch')
    bg_color: str = os.getenv('BG_COLOR', '#000000')
    bg_opacity: float = float(os.getenv('BG_OPACITY', '1.0'))
    
    # Green screen / chroma key (COMPREHENSIVE)
    chroma_tolerance: float = float(os.getenv('CHROMA_TOLERANCE', '0.3'))
    chroma_softness: float = float(os.getenv('CHROMA_SOFTNESS', '0.1'))
    chroma_defringe: bool = os.getenv('CHROMA_DEFRINGE', 'true').lower() == 'true'
    chroma_despill: bool = os.getenv('CHROMA_DESPILL', 'true').lower() == 'true'
    chroma_key_color: str = os.getenv('CHROMA_KEY_COLOR', '#00FF00')
    
    # Motion detection (COMPREHENSIVE)
    motion_detect: bool = os.getenv('MOTION_DETECT', 'false').lower() == 'true'
    motion_threshold_percent: float = float(os.getenv('MOTION_THRESHOLD_PERCENT', '5.0'))
    motion_blur_kernel: int = int(os.getenv('MOTION_BLUR_KERNEL', '21'))
    motion_min_area: int = int(os.getenv('MOTION_MIN_AREA', '500'))
    
    # Stabilization (COMPREHENSIVE)
    stabilize: bool = os.getenv('STABILIZE', 'false').lower() == 'true'
    stabilize_smoothing: float = float(os.getenv('STABILIZE_SMOOTHING', '30.0'))
    stabilize_crop_percent: float = float(os.getenv('STABILIZE_CROP_PERCENT', '0.05'))
    
    # Advanced processing flags (COMPREHENSIVE)
    use_guided_filter: bool = os.getenv('USE_GUIDED_FILTER', 'false').lower() == 'true'
    guided_filter_radius: int = int(os.getenv('GUIDED_FILTER_RADIUS', '8'))
    guided_filter_eps: float = float(os.getenv('GUIDED_FILTER_EPS', '0.2'))
    use_grabcut: bool = os.getenv('USE_GRABCUT', 'false').lower() == 'true'
    grabcut_iterations: int = int(os.getenv('GRABCUT_ITERATIONS', '5'))
    use_watershed: bool = os.getenv('USE_WATERSHED', 'false').lower() == 'true'
    watershed_markers: int = int(os.getenv('WATERSHED_MARKERS', '10'))
    
    # Frame sampling (COMPREHENSIVE)
    sample_rate: int = int(os.getenv('SAMPLE_RATE', '1'))
    start_frame: int = int(os.getenv('START_FRAME', '0'))
    end_frame: int = int(os.getenv('END_FRAME', '-1'))
    process_every_nth_frame: int = int(os.getenv('PROCESS_EVERY_NTH_FRAME', '1'))
    interpolate_frames: bool = os.getenv('INTERPOLATE_FRAMES', 'false').lower() == 'true'
    
    # Preview and debug (COMPREHENSIVE)
    preview_enabled: bool = os.getenv('PREVIEW_ENABLED', 'false').lower() == 'true'
    preview_scale: float = float(os.getenv('PREVIEW_SCALE', '0.5'))
    debug_masks: bool = os.getenv('DEBUG_MASKS', 'false').lower() == 'true'
    debug_contours: bool = os.getenv('DEBUG_CONTOURS', 'false').lower() == 'true'
    save_debug_frames: bool = os.getenv('SAVE_DEBUG_FRAMES', 'false').lower() == 'true'
    
    # Threading and parallelization (COMPREHENSIVE)
    num_threads: int = int(os.getenv('NUM_THREADS', '4'))
    use_multiprocessing: bool = os.getenv('USE_MULTIPROCESSING', 'false').lower() == 'true'
    chunk_size: int = int(os.getenv('CHUNK_SIZE', '10'))
    prefetch_frames: int = int(os.getenv('PREFETCH_FRAMES', '5'))
    
    # Memory optimization (COMPREHENSIVE)
    low_memory_mode: bool = os.getenv('LOW_MEMORY_MODE', 'false').lower() == 'true'
    cache_frames: bool = os.getenv('CACHE_FRAMES', 'true').lower() == 'true'
    max_cache_size_mb: int = int(os.getenv('MAX_CACHE_SIZE_MB', '1024'))
    clear_cache_interval: int = int(os.getenv('CLEAR_CACHE_INTERVAL', '100'))
    
    # Output settings
    output_dir: str = os.getenv('OUTPUT_DIR', 'outputs')
    output_format: str = os.getenv('OUTPUT_FORMAT', 'mp4')
    output_quality: str = os.getenv('OUTPUT_QUALITY', 'high')  # low, medium, high
    output_codec: str = os.getenv('OUTPUT_CODEC', 'h264')
    write_fps: Optional[float] = None
    preserve_audio: bool = os.getenv('PRESERVE_AUDIO', 'true').lower() == 'true'
    
    # Cache settings
    model_cache_dir: str = os.getenv('MODEL_CACHE_DIR', 'models/cache')
    temp_dir: str = os.getenv('TEMP_DIR', 'temp')
    cleanup_temp_files: bool = os.getenv('CLEANUP_TEMP_FILES', 'true').lower() == 'true'
    cache_size_limit_gb: float = float(os.getenv('CACHE_SIZE_LIMIT_GB', '10.0'))
    
    # Performance settings
    max_concurrent_processes: int = int(os.getenv('MAX_CONCURRENT_PROCESSES', '1'))
    gpu_memory_fraction: float = float(os.getenv('GPU_MEMORY_FRACTION', '0.8'))
    batch_size: int = int(os.getenv('BATCH_SIZE', '4'))
    num_workers: int = int(os.getenv('NUM_WORKERS', '4'))
    
    # API settings
    api_enabled: bool = os.getenv('API_ENABLED', 'false').lower() == 'true'
    api_host: str = os.getenv('API_HOST', '0.0.0.0')
    api_port: int = int(os.getenv('API_PORT', '8000'))
    api_key: Optional[str] = os.getenv('API_KEY', None)
    
    # Web UI settings
    gradio_server_name: str = os.getenv('GRADIO_SERVER_NAME', '0.0.0.0')
    gradio_server_port: int = int(os.getenv('GRADIO_SERVER_PORT', '7860'))
    gradio_share: bool = os.getenv('GRADIO_SHARE', 'false').lower() == 'true'
    gradio_auth: Optional[str] = os.getenv('GRADIO_AUTH', None)  # username:password
    
    # Debug settings
    debug_mode: bool = os.getenv('DEBUG_MODE', 'false').lower() == 'true'
    save_intermediate_results: bool = os.getenv('SAVE_INTERMEDIATE_RESULTS', 'false').lower() == 'true'
    log_level: str = os.getenv('LOG_LEVEL', 'INFO')
    profile_performance: bool = os.getenv('PROFILE_PERFORMANCE', 'false').lower() == 'true'
    
    # Feature flags
    enable_two_stage: bool = os.getenv('ENABLE_TWO_STAGE', 'true').lower() == 'true'
    enable_preview_modes: bool = os.getenv('ENABLE_PREVIEW_MODES', 'true').lower() == 'true'
    enable_batch_processing: bool = os.getenv('ENABLE_BATCH_PROCESSING', 'false').lower() == 'true'
    
    # Legacy compatibility
    legacy_mode: bool = os.getenv('LEGACY_MODE', 'true').lower() == 'true'
    legacy_configs_dir: str = os.getenv('LEGACY_CONFIGS_DIR', 'Configs')
    
    def __post_init__(self):
        """Validate configuration after initialization"""
        self._validate_config()
        self._create_directories()
        self._setup_logging()
        if self.debug_mode:
            self._log_config()
    
    def _validate_config(self):
        """Validate configuration values"""
        # Validate frame settings
        self.keyframe_interval = max(1, self.keyframe_interval)
        self.frame_skip = max(1, self.frame_skip)
        
        # Validate memory settings
        self.memory_cleanup_interval = max(1, self.memory_cleanup_interval)
        self.memory_threshold_mb = max(256, self.memory_threshold_mb)
        
        # Validate video constraints
        self.max_video_length = max(1, self.max_video_length)
        self.min_video_fps = max(1, min(self.min_video_fps, 60))
        self.max_video_fps = max(self.min_video_fps, min(self.max_video_fps, 120))
        
        # Validate resolution format
        if 'x' not in self.max_video_resolution:
            logger.warning(f"Invalid resolution format: {self.max_video_resolution}. Setting to 1920x1080.")
            self.max_video_resolution = '1920x1080'
        
        # Validate quality preset
        valid_presets = ['fast', 'balanced', 'high', 'ultra']
        if self.quality_preset not in valid_presets:
            logger.warning(f"Invalid quality preset: {self.quality_preset}. Setting to 'balanced'.")
            self.quality_preset = 'balanced'
        
        # Validate model settings
        valid_sam2_sizes = ['tiny', 'small', 'base', 'large']
        if self.sam2_model_size not in valid_sam2_sizes:
            logger.warning(f"Invalid SAM2 model size: {self.sam2_model_size}. Setting to 'large'.")
            self.sam2_model_size = 'large'
        
        valid_precisions = ['fp16', 'fp32']
        if self.matanyone_precision not in valid_precisions:
            logger.warning(f"Invalid precision: {self.matanyone_precision}. Setting to 'fp32'.")
            self.matanyone_precision = 'fp32'
        
        # Validate MatAnyone settings
        self.matanyone_threshold = max(0.0, min(1.0, self.matanyone_threshold))
        self.matanyone_weight_base = max(0.1, min(2.0, self.matanyone_weight_base))
        self.matanyone_weight_hair = max(0.1, min(2.0, self.matanyone_weight_hair))
        self.matanyone_weight_edge = max(0.1, min(2.0, self.matanyone_weight_edge))
        self.matanyone_weight_detail = max(0.1, min(2.0, self.matanyone_weight_detail))
        self.matanyone_blend_alpha = max(0.0, min(1.0, self.matanyone_blend_alpha))
        self.matanyone_morphology_kernel_size = max(3, min(15, self.matanyone_morphology_kernel_size))
        self.matanyone_trimap_dilation = max(1, min(50, self.matanyone_trimap_dilation))
        
        # Validate MatAnyone processing mode
        valid_modes = ['refine', 'replace', 'blend']
        if self.matanyone_processing_mode not in valid_modes:
            logger.warning(f"Invalid MatAnyone processing mode: {self.matanyone_processing_mode}. Setting to 'refine'.")
            self.matanyone_processing_mode = 'refine'
        
        # Validate mask settings (ADDED)
        self.mask_gamma = max(0.1, min(5.0, self.mask_gamma))
        self.mask_blur = max(0, min(20, self.mask_blur))
        self.mask_threshold = max(0.0, min(1.0, self.mask_threshold))
        self.mask_edge_softness = max(0, min(10, self.mask_edge_softness))
        self.mask_spill_suppression = max(0.0, min(1.0, self.mask_spill_suppression))
        
        # Validate hard threshold settings (ADDED)
        self.hard_low = max(0.0, min(1.0, self.hard_low))
        self.hard_medium = max(0.0, min(1.0, self.hard_medium))
        self.hard_high = max(0.0, min(1.0, self.hard_high))
        self.hard_threshold = max(0.0, min(1.0, self.hard_threshold))
        
        # Validate morphological operations (ADDED)
        self.dilate_px = max(0, min(20, self.dilate_px))
        self.erode_px = max(0, min(20, self.erode_px))
        self.open_px = max(0, min(20, self.open_px))
        self.close_px = max(0, min(20, self.close_px))
        self.morph_iterations = max(1, min(10, self.morph_iterations))
        
        # Validate edge processing (ADDED)
        self.edge_blur_px = max(0, min(30, self.edge_blur_px))
        self.edge_feather_px = max(0, min(20, self.edge_feather_px))
        self.edge_threshold = max(0.0, min(1.0, self.edge_threshold))
        valid_edge_methods = ['canny', 'sobel', 'laplacian', 'scharr']
        if self.edge_detect_method not in valid_edge_methods:
            self.edge_detect_method = 'canny'
        
        # Validate tracking and temporal consistency (ADDED)
        self.min_iou_to_accept = max(0.0, min(1.0, self.min_iou_to_accept))
        self.max_iou_distance = max(0.0, min(1.0, self.max_iou_distance))
        self.min_track_length = max(1, min(100, self.min_track_length))
        self.track_buffer_size = max(1, min(300, self.track_buffer_size))
        self.temporal_smoothing = max(0.0, min(1.0, self.temporal_smoothing))
        self.motion_threshold = max(0.0, min(1.0, self.motion_threshold))
        
        # Validate segmentation refinement (ADDED)
        self.refine_iterations = max(0, min(10, self.refine_iterations))
        self.refine_threshold = max(0.0, min(1.0, self.refine_threshold))
        self.crf_iterations = max(1, min(20, self.crf_iterations))
        self.bilateral_sigma_color = max(1.0, min(200.0, self.bilateral_sigma_color))
        self.bilateral_sigma_space = max(1.0, min(50.0, self.bilateral_sigma_space))
        
        # Validate feathering and blending (ADDED)
        self.feather_amount = max(0, min(50, self.feather_amount))
        valid_blend_modes = ['normal', 'multiply', 'screen', 'overlay', 'soft_light', 'hard_light']
        if self.blend_mode not in valid_blend_modes:
            self.blend_mode = 'normal'
        self.alpha_threshold = max(0.0, min(1.0, self.alpha_threshold))
        valid_composite_modes = ['over', 'under', 'atop', 'xor', 'plus']
        if self.composite_mode not in valid_composite_modes:
            self.composite_mode = 'over'
        
        # Validate color correction (ADDED)
        self.brightness_adjust = max(0.0, min(2.0, self.brightness_adjust))
        self.contrast_adjust = max(0.0, min(2.0, self.contrast_adjust))
        self.saturation_adjust = max(0.0, min(2.0, self.saturation_adjust))
        self.hue_shift = max(-180.0, min(180.0, self.hue_shift))
        
        # Validate noise reduction (ADDED)
        self.denoise_strength = max(0.0, min(100.0, self.denoise_strength))
        self.median_filter_size = max(0, min(15, self.median_filter_size))
        if self.median_filter_size % 2 == 0 and self.median_filter_size > 0:
            self.median_filter_size += 1  # Must be odd
        self.gaussian_sigma = max(0.0, min(10.0, self.gaussian_sigma))
        
        # Validate performance optimization (ADDED)
        self.gpu_device_id = max(0, self.gpu_device_id)
        
        # Validate video codec (ADDED)
        valid_codecs = ['mp4v', 'h264', 'h265', 'xvid', 'mjpeg']
        if self.video_codec not in valid_codecs:
            self.video_codec = 'mp4v'
        
        # Validate temporal consistency (COMPREHENSIVE)
        self.temporal_ema_alpha = max(0.0, min(1.0, self.temporal_ema_alpha))
        self.temporal_window_size = max(1, min(100, self.temporal_window_size))
        self.temporal_blend_factor = max(0.0, min(1.0, self.temporal_blend_factor))
        self.temporal_consistency_threshold = max(0.0, min(1.0, self.temporal_consistency_threshold))
        self.temporal_buffer_frames = max(1, min(300, self.temporal_buffer_frames))
        
        # Validate mask post-processing
        self.mask_min_area = max(0, self.mask_min_area)
        self.mask_binary_threshold = max(0.0, min(1.0, self.mask_binary_threshold))
        self.mask_confidence_threshold = max(0.0, min(1.0, self.mask_confidence_threshold))
        self.mask_smooth_radius = max(0, min(50, self.mask_smooth_radius))
        
        # Validate contour processing
        self.contour_approx_epsilon = max(0.0, min(1.0, self.contour_approx_epsilon))
        self.contour_min_points = max(3, self.contour_min_points)
        
        # Validate trimap
        self.trimap_dilation_size = max(0, min(50, self.trimap_dilation_size))
        self.trimap_erosion_size = max(0, min(50, self.trimap_erosion_size))
        self.trimap_unknown_width = max(1, min(100, self.trimap_unknown_width))
        self.trimap_confidence_threshold = max(0.0, min(1.0, self.trimap_confidence_threshold))
        
        # Validate SAM2 parameters
        self.sam2_points_per_side = max(1, min(100, self.sam2_points_per_side))
        self.sam2_pred_iou_thresh = max(0.0, min(1.0, self.sam2_pred_iou_thresh))
        self.sam2_stability_score_thresh = max(0.0, min(1.0, self.sam2_stability_score_thresh))
        self.sam2_crop_n_layers = max(0, min(10, self.sam2_crop_n_layers))
        self.sam2_crop_n_points_downscale_factor = max(1, min(16, self.sam2_crop_n_points_downscale_factor))
        self.sam2_min_mask_region_area = max(0, self.sam2_min_mask_region_area)
        
        # Validate background processing
        self.bg_blur_radius = max(0, min(100, self.bg_blur_radius))
        valid_blur_types = ['gaussian', 'box', 'median', 'bilateral']
        if self.bg_blur_type not in valid_blur_types:
            self.bg_blur_type = 'gaussian'
        valid_fill_modes = ['stretch', 'fit', 'fill', 'tile']
        if self.bg_fill_mode not in valid_fill_modes:
            self.bg_fill_mode = 'stretch'
        self.bg_opacity = max(0.0, min(1.0, self.bg_opacity))
        
        # Validate chroma key
        self.chroma_tolerance = max(0.0, min(1.0, self.chroma_tolerance))
        self.chroma_softness = max(0.0, min(1.0, self.chroma_softness))
        
        # Validate motion detection
        self.motion_threshold_percent = max(0.0, min(100.0, self.motion_threshold_percent))
        self.motion_blur_kernel = max(1, min(99, self.motion_blur_kernel))
        if self.motion_blur_kernel % 2 == 0:
            self.motion_blur_kernel += 1
        self.motion_min_area = max(0, self.motion_min_area)
        
        # Validate stabilization
        self.stabilize_smoothing = max(1.0, min(100.0, self.stabilize_smoothing))
        self.stabilize_crop_percent = max(0.0, min(0.5, self.stabilize_crop_percent))
        
        # Validate guided filter
        self.guided_filter_radius = max(1, min(50, self.guided_filter_radius))
        self.guided_filter_eps = max(0.0, min(1.0, self.guided_filter_eps))
        self.grabcut_iterations = max(1, min(20, self.grabcut_iterations))
        self.watershed_markers = max(2, min(100, self.watershed_markers))
        
        # Validate frame sampling
        self.sample_rate = max(1, self.sample_rate)
        self.start_frame = max(0, self.start_frame)
        self.process_every_nth_frame = max(1, self.process_every_nth_frame)
        
        # Validate preview
        self.preview_scale = max(0.1, min(2.0, self.preview_scale))
        
        # Validate threading
        self.num_threads = max(1, min(32, self.num_threads))
        self.chunk_size = max(1, min(1000, self.chunk_size))
        self.prefetch_frames = max(0, min(100, self.prefetch_frames))
        
        # Validate memory
        self.max_cache_size_mb = max(0, self.max_cache_size_mb)
        self.clear_cache_interval = max(1, self.clear_cache_interval)
        
        # Validate output settings
        valid_formats = ['mp4', 'avi', 'mov', 'webm', 'mkv']
        if self.output_format not in valid_formats:
            logger.warning(f"Invalid output format: {self.output_format}. Setting to 'mp4'.")
            self.output_format = 'mp4'
        
        valid_qualities = ['low', 'medium', 'high', 'ultra']
        if self.output_quality not in valid_qualities:
            logger.warning(f"Invalid output quality: {self.output_quality}. Setting to 'high'.")
            self.output_quality = 'high'
        
        # Validate performance settings
        self.max_concurrent_processes = max(1, self.max_concurrent_processes)
        self.gpu_memory_fraction = max(0.1, min(1.0, self.gpu_memory_fraction))
        self.batch_size = max(1, self.batch_size)
        self.num_workers = max(0, self.num_workers)
        
        # Validate API settings
        self.api_port = max(1024, min(65535, self.api_port))
        
        # Validate confidence threshold
        self.confidence_threshold = max(0.0, min(1.0, self.confidence_threshold))
        
        # Validate cache size
        self.cache_size_limit_gb = max(0.1, self.cache_size_limit_gb)
    
    def _create_directories(self):
        """Create necessary directories if they don't exist"""
        directories = [
            self.model_cache_dir,
            self.temp_dir,
            self.output_dir,
            Path(self.output_dir) / 'masks',
            Path(self.output_dir) / 'greenscreen',
            Path(self.output_dir) / 'final',
            Path(self.output_dir) / 'two_stage'
        ]
        
        # Add MatAnyone component directories if enabled
        if self.use_component_masks:
            directories.extend([
                self.hair_masks_dir,
                self.edge_masks_dir,
                self.detail_masks_dir
            ])
        
        for directory in directories:
            try:
                Path(directory).mkdir(parents=True, exist_ok=True)
                logger.debug(f"Ensured directory exists: {directory}")
            except Exception as e:
                logger.error(f"Failed to create directory {directory}: {e}")
    
    def _setup_logging(self):
        """Setup logging based on configuration"""
        log_levels = {
            'DEBUG': logging.DEBUG,
            'INFO': logging.INFO,
            'WARNING': logging.WARNING,
            'ERROR': logging.ERROR,
            'CRITICAL': logging.CRITICAL
        }
        
        level = log_levels.get(self.log_level.upper(), logging.INFO)
        logging.getLogger().setLevel(level)
    
    def _log_config(self):
        """Log current configuration in debug mode"""
        logger.info("=" * 60)
        logger.info(f"{self.app_name} v{self.version} Configuration")
        logger.info("=" * 60)
        config_dict = self.to_dict()
        # Hide sensitive information
        if config_dict.get('api_key'):
            config_dict['api_key'] = '***hidden***'
        if config_dict.get('gradio_auth'):
            config_dict['gradio_auth'] = '***hidden***'
        
        for key, value in config_dict.items():
            logger.info(f"{key}: {value}")
        logger.info("=" * 60)
    
    def to_dict(self) -> Dict[str, Any]:
        """Convert configuration to dictionary"""
        return asdict(self)
    
    def to_json(self, filepath: Optional[str] = None) -> str:
        """Export configuration to JSON"""
        config_dict = self.to_dict()
        if filepath:
            with open(filepath, 'w') as f:
                json.dump(config_dict, f, indent=2)
            logger.info(f"Configuration saved to {filepath}")
        return json.dumps(config_dict, indent=2)
    
    def to_yaml(self, filepath: Optional[str] = None) -> str:
        """Export configuration to YAML"""
        config_dict = self.to_dict()
        if filepath:
            with open(filepath, 'w') as f:
                yaml.dump(config_dict, f, default_flow_style=False)
            logger.info(f"Configuration saved to {filepath}")
        return yaml.dump(config_dict, default_flow_style=False)
    
    @classmethod
    def from_json(cls, filepath: str) -> 'ProcessingConfig':
        """Load configuration from JSON file"""
        with open(filepath, 'r') as f:
            config_dict = json.load(f)
        return cls(**config_dict)
    
    @classmethod
    def from_yaml(cls, filepath: str) -> 'ProcessingConfig':
        """Load configuration from YAML file"""
        with open(filepath, 'r') as f:
            config_dict = yaml.safe_load(f)
        return cls(**config_dict)
    
    def get_matanyone_config(self) -> Dict[str, Any]:
        """Get MatAnyone-specific configuration as a dictionary"""
        return {
            'enabled': self.matanyone_enabled,
            'model_path': self.matanyone_model_path,
            'threshold': self.matanyone_threshold,
            'edge_refinement': self.matanyone_edge_enhancement,
            'hair_refinement': self.matanyone_hair_refinement,
            'detail_refinement': self.matanyone_detail_refinement,
            'morphology_ops': self.matanyone_morphology_ops,
            'morphology_kernel_size': self.matanyone_morphology_kernel_size,
            'processing_mode': self.matanyone_processing_mode,
            'blend_alpha': self.matanyone_blend_alpha,
            'trimap_enabled': self.matanyone_trimap_enabled,
            'trimap_dilation': self.matanyone_trimap_dilation,
            'component_weights': {
                'base': self.matanyone_weight_base,
                'hair': self.matanyone_weight_hair,
                'edge': self.matanyone_weight_edge,
                'detail': self.matanyone_weight_detail
            },
            'component_paths': {
                'hair': self.hair_masks_dir if self.use_component_masks else None,
                'edge': self.edge_masks_dir if self.use_component_masks else None,
                'detail': self.detail_masks_dir if self.use_component_masks else None
            },
            'precision': self.matanyone_precision
        }
    
    def get_quality_settings(self) -> Dict[str, Any]:
        """Get quality-specific settings based on preset"""
        quality_maps = {
            'fast': {
                'keyframe_interval': max(self.keyframe_interval, 10),
                'frame_skip': max(self.frame_skip, 2),
                'edge_refinement': False,
                'temporal_consistency': False,
                'model_precision': 'fp16',
                'batch_size': min(self.batch_size * 2, 16),
                'output_quality_params': '-preset ultrafast -crf 28',
                'matanyone_enabled': False  # Disable MatAnyone for fast mode
            },
            'balanced': {
                'keyframe_interval': self.keyframe_interval,
                'frame_skip': self.frame_skip,
                'edge_refinement': True,
                'temporal_consistency': True,
                'model_precision': 'fp32',
                'batch_size': self.batch_size,
                'output_quality_params': '-preset medium -crf 23',
                'matanyone_enabled': self.matanyone_enabled
            },
            'high': {
                'keyframe_interval': max(self.keyframe_interval // 2, 1),
                'frame_skip': 1,
                'edge_refinement': True,
                'temporal_consistency': True,
                'model_precision': 'fp32',
                'batch_size': max(self.batch_size // 2, 1),
                'output_quality_params': '-preset slow -crf 18',
                'matanyone_enabled': True  # Enable MatAnyone for high quality
            },
            'ultra': {
                'keyframe_interval': 1,
                'frame_skip': 1,
                'edge_refinement': True,
                'temporal_consistency': True,
                'model_precision': 'fp32',
                'batch_size': 1,
                'output_quality_params': '-preset veryslow -crf 15',
                'matanyone_enabled': True,  # Always enable MatAnyone for ultra
                'matanyone_morphology_ops': True,
                'matanyone_trimap_enabled': True
            }
        }
        
        return quality_maps.get(self.quality_preset, quality_maps['balanced'])
    
    def get_resolution_limits(self) -> tuple[int, int]:
        """Get max width and height from resolution setting"""
        try:
            width, height = map(int, self.max_video_resolution.split('x'))
            return width, height
        except ValueError:
            logger.error(f"Invalid resolution format: {self.max_video_resolution}")
            return 1920, 1080
    
    def get_output_params(self) -> Dict[str, str]:
        """Get FFmpeg output parameters based on settings"""
        quality_settings = self.get_quality_settings()
        codec_map = {
            'h264': 'libx264',
            'h265': 'libx265',
            'vp9': 'libvpx-vp9',
            'av1': 'libaom-av1'
        }
        
        return {
            'codec': codec_map.get(self.output_codec, 'libx264'),
            'quality': quality_settings['output_quality_params'],
            'format': self.output_format,
            'audio': '-c:a copy' if self.preserve_audio else '-an'
        }
    
    def is_high_performance_mode(self) -> bool:
        """Check if configuration is set for high performance"""
        return (
            self.quality_preset in ['high', 'ultra'] and
            self.edge_refinement and
            self.temporal_consistency and
            self.keyframe_interval <= 3 and
            self.matanyone_enabled  # Include MatAnyone in high performance check
        )
    
    def get_memory_limits(self) -> Dict[str, Any]:
        """Get memory-related limits"""
        return {
            'gpu_memory_fraction': self.gpu_memory_fraction,
            'cleanup_interval': self.memory_cleanup_interval,
            'max_concurrent': self.max_concurrent_processes,
            'threshold_mb': self.memory_threshold_mb,
            'cache_size_gb': self.cache_size_limit_gb
        }
    
    def validate_for_production(self) -> List[str]:
        """Validate configuration for production deployment"""
        warnings = []
        
        if self.debug_mode:
            warnings.append("Debug mode is enabled in production")
        
        if self.save_intermediate_results:
            warnings.append("Intermediate results saving is enabled (disk usage)")
        
        if not self.cleanup_temp_files:
            warnings.append("Temp file cleanup is disabled (disk usage)")
        
        if self.gradio_share:
            warnings.append("Gradio share is enabled (security risk)")
        
        if not self.api_key and self.api_enabled:
            warnings.append("API is enabled without authentication")
        
        if self.gpu_memory_fraction > 0.9:
            warnings.append("GPU memory fraction is very high (>90%)")
        
        if self.max_concurrent_processes > 4:
            warnings.append("High concurrent processes may cause instability")
        
        # MatAnyone-specific warnings
        if self.matanyone_enabled and self.quality_preset == 'fast':
            warnings.append("MatAnyone is enabled with 'fast' quality preset (may impact performance)")
        
        if self.use_component_masks and not Path(self.hair_masks_dir).exists():
            warnings.append(f"Component masks enabled but directory not found: {self.hair_masks_dir}")
        
        return warnings

# Singleton instance for application-wide use
_config_instance: Optional[ProcessingConfig] = None

def get_config() -> ProcessingConfig:
    """Get global configuration instance"""
    global _config_instance
    if _config_instance is None:
        _config_instance = ProcessingConfig()
    return _config_instance

def reload_config() -> ProcessingConfig:
    """Reload configuration from environment variables"""
    global _config_instance
    _config_instance = ProcessingConfig()
    logger.info("Configuration reloaded from environment variables")
    return _config_instance

def update_config(**kwargs) -> ProcessingConfig:
    """Update configuration with new values"""
    global _config_instance
    if _config_instance is None:
        _config_instance = ProcessingConfig()
    
    for key, value in kwargs.items():
        if hasattr(_config_instance, key):
            setattr(_config_instance, key, value)
            logger.debug(f"Updated config: {key} = {value}")
        else:
            logger.warning(f"Unknown configuration key: {key}")
    
    # Re-validate after updates
    _config_instance._validate_config()
    return _config_instance

def load_config_from_file(filepath: str) -> ProcessingConfig:
    """Load configuration from file (JSON or YAML)"""
    global _config_instance
    
    file_path = Path(filepath)
    if not file_path.exists():
        raise FileNotFoundError(f"Configuration file not found: {filepath}")
    
    if file_path.suffix.lower() in ['.json']:
        _config_instance = ProcessingConfig.from_json(filepath)
    elif file_path.suffix.lower() in ['.yaml', '.yml']:
        _config_instance = ProcessingConfig.from_yaml(filepath)
    else:
        raise ValueError(f"Unsupported configuration file format: {file_path.suffix}")
    
    logger.info(f"Configuration loaded from {filepath}")
    return _config_instance