from __future__ import annotations

from dataclasses import dataclass

import numpy as np


# --- 1. 物品节点：极其扁平，只存"当前最新/平均"状态 ---
@dataclass
class ObjectNode:
    obj_id: str  # 唯一ID (例如: "obj_001")
    room_id: str  # 所属房间的直接外键，不搞复杂的层级关系

    # 位置：在 debug 阶段，一切认准全局坐标，不要搞局部坐标系
    position: np.ndarray  # [x, y, z] 世界坐标系下的中心点或锚点

    # 特征：直接存你压缩后的 512bit 结果，不搞历史缓存
    visual_hash: bytes  # 512bit 视觉特征 (用于外观检索)
    semantic_hash: bytes  # 512bit 语义特征 (用于类别对齐)

    # Debug 必备：极简的生命周期管理，防止满屏"幽灵节点"
    hit_count: int = 1  # 被观测到的次数。太低的可以直接过滤掉
    last_seen_frame: int = 0  # 最后一次看到的帧号或时间戳

    # Optional detection metadata (from M0 integration)
    label: str | None = None
    confidence: float | None = None
    bbox_xyxy: tuple[float, float, float, float] | None = None
    source_view_id: str | None = None
    position_confidence: float | None = None

    def __post_init__(self):
        self.position = np.asarray(self.position, dtype=np.float32)
        if len(self.visual_hash) != 64:
            raise ValueError("visual_hash must be exactly 64 bytes (512 bits)")
        if len(self.semantic_hash) != 64:
            raise ValueError("semantic_hash must be exactly 64 bytes (512 bits)")
        if self.position.shape != (3,):
            raise ValueError("position must have shape (3,)")
        if self.bbox_xyxy is not None and len(self.bbox_xyxy) != 4:
            raise ValueError("bbox_xyxy must have exactly 4 elements")