from __future__ import annotations

from dataclasses import dataclass
from typing import Any, Protocol


@dataclass(frozen=True)
class SegmentationAdapterResult:
    class_name: str
    confidence: float | None
    geometry: dict[str, Any]
    bbox_json: dict[str, Any] | None = None
    mask_path: str | None = None
    source_tile_path: str | None = None
    tile_index: int | None = None
    properties_json: dict[str, Any] | None = None
    provenance_json: dict[str, Any] | None = None
    area_m2: float | None = None


class SegmentationAdapter(Protocol):
    def segment(self, *args: Any, **kwargs: Any) -> list[SegmentationAdapterResult]:
        """Future segmentation adapters must local-import model dependencies inside execution paths."""


class FixtureSegmentationAdapter:
    def segment(self, raw_segmentations: Any) -> list[SegmentationAdapterResult]:
        if not isinstance(raw_segmentations, list):
            return []
        results: list[SegmentationAdapterResult] = []
        for raw in raw_segmentations:
            if not isinstance(raw, dict):
                continue
            results.append(
                SegmentationAdapterResult(
                    class_name=str(raw.get("class_name") or ""),
                    confidence=float(raw["confidence"]) if raw.get("confidence") is not None else None,
                    geometry=raw.get("geometry"),
                    bbox_json=raw.get("bbox_json"),
                    mask_path=raw.get("mask_path"),
                    source_tile_path=raw.get("source_tile_path"),
                    tile_index=raw.get("tile_index"),
                    properties_json=raw.get("properties_json"),
                    provenance_json=raw.get("provenance_json"),
                    area_m2=raw.get("area_m2"),
                )
            )
        return results