"""Central configuration for all models and pipeline settings."""

from dataclasses import dataclass, field
from enum import Enum
from pathlib import Path


class Quality(str, Enum):
    FAST = "fast"
    BALANCED = "balanced"
    HIGH = "high"
    ULTRA = "ultra"


class LineArtStyle(str, Enum):
    INFORMATIVE = "informative"
    ANYLINE = "anyline"
    MANGA = "manga"
    FUSED = "fused"          # Merge multiple models
    AUTO = "auto"            # Pick based on content


class ContentType(str, Enum):
    PHOTO = "photo"
    ILLUSTRATION = "illustration"
    ANIME = "anime"
    PORTRAIT = "portrait"
    LANDSCAPE = "landscape"
    AUTO = "auto"


class Difficulty(str, Enum):
    EASY = "easy"       # 6-8 colors, large regions
    MEDIUM = "medium"   # 10-14 colors
    HARD = "hard"       # 16-22 colors, small regions
    EXPERT = "expert"   # 24-30 colors, tiny regions
    AUTO = "auto"


@dataclass
class ModelPaths:
    informative_drawings: str = "models/informative_drawings.onnx"
    anyline: str = "models/anyline.onnx"
    manga_line: str = "models/manga_line.onnx"
    sam2_encoder: str = "models/sam2_encoder.onnx"
    sam2_decoder: str = "models/sam2_decoder.onnx"
    depth_anything: str = "models/depth_anything_v2.onnx"
    real_esrgan: str = "models/real_esrgan_x4.onnx"
    rmbg: str = "models/rmbg2.onnx"
    face_parsing: str = "models/face_parsing.onnx"

    def available(self, name: str) -> bool:
        path = getattr(self, name, None)
        return path is not None and Path(path).exists()


@dataclass
class PipelineConfig:
    # Content
    content_type: ContentType = ContentType.AUTO
    difficulty: Difficulty = Difficulty.AUTO
    quality: Quality = Quality.BALANCED

    # Colors
    k_colors: int | None = None   # None = auto
    use_lab: bool = True
    spatial_weight: float = 0.0

    # Line art
    line_style: LineArtStyle = LineArtStyle.FUSED
    line_threshold: int = 128

    # Regions
    min_region_area: int = 200
    use_sam: bool = True          # Use SAM2 for segmentation

    # Enhancement
    upscale_if_small: bool = True
    remove_background: bool = False
    detect_faces: bool = True

    # Depth
    use_depth: bool = True
    depth_layers: int = 3         # Number of difficulty layers

    # Closing
    density: str = "auto"
    close_kernel: int = 3
    close_iterations: int = 2
    bridge_gaps: bool = True

    # System
    max_dimension: int = 1024
    save_debug: bool = False
    debug_dir: str = "outputs/debug"

    def apply_difficulty(self):
        """Set parameters based on difficulty level."""
        presets = {
            Difficulty.EASY:   {"k": 8,  "min_area": 500, "spatial": 0.4},
            Difficulty.MEDIUM: {"k": 14, "min_area": 300, "spatial": 0.2},
            Difficulty.HARD:   {"k": 22, "min_area": 150, "spatial": 0.1},
            Difficulty.EXPERT: {"k": 30, "min_area": 20,  "spatial": 0.05},
        }
        if self.difficulty in presets:
            p = presets[self.difficulty]
            if self.k_colors is None:
                self.k_colors = p["k"]
            self.min_region_area = p["min_area"]
            self.spatial_weight = p["spatial"]

    def apply_quality(self):
        """Set processing params based on quality level."""
        if self.quality == Quality.FAST:
            self.use_sam = False
            self.use_depth = False
            self.bridge_gaps = False
            self.line_style = LineArtStyle.INFORMATIVE
            self.upscale_if_small = False
        elif self.quality == Quality.ULTRA:
            self.use_sam = True
            self.use_depth = True
            self.bridge_gaps = True
            self.line_style = LineArtStyle.FUSED
            self.density = "dense"
            self.close_iterations = 2