"""
Simple hand gesture detection — open palm, closed fist, pinch.

Operates on raw (21, 3) landmark arrays; calls normalize_hand() internally.
"""

from __future__ import annotations

from enum import Enum
from typing import Optional

import numpy as np

from circuitforge_core.input.gestures.normalizer import normalize_hand

_FINGERTIP_IDX = [4, 8, 12, 16, 20]
_THUMB_TIP = 4
_INDEX_TIP = 8

OPEN_PALM_THRESHOLD = 1.5
PINCH_THRESHOLD = 0.15


class HandGesture(str, Enum):
    OPEN_PALM = "open_palm"
    PINCH = "pinch"
    FIST = "fist"


class HandGestureDetector:
    """Classify a hand pose from MediaPipe landmarks."""

    def detect(self, raw_points: np.ndarray) -> Optional[HandGesture]:
        """
        Args:
            raw_points: (21, 3) float32 — raw MediaPipe hand landmarks.

        Returns:
            HandGesture or None if pose is ambiguous.
        """
        vec = normalize_hand(raw_points).reshape(21, 3)
        tip_distances = [float(np.linalg.norm(vec[i])) for i in _FINGERTIP_IDX]
        tip_sum = sum(tip_distances)

        pinch_dist = float(np.linalg.norm(vec[_THUMB_TIP] - vec[_INDEX_TIP]))
        if pinch_dist < PINCH_THRESHOLD:
            return HandGesture.PINCH
        if tip_sum > OPEN_PALM_THRESHOLD:
            return HandGesture.OPEN_PALM
        if tip_sum < 0.6:
            return HandGesture.FIST
        return None