"""Various utilities for preprocess or postprocess computations."""
from typing import List, Tuple

import numpy as np
import numpy.typing as npt

def bbox_to_center_and_scale(
    bbox: List[int]) -> Tuple[npt.NDArray[np.float32], npt.NDArray[np.float32]]:
    """Returns the center and dimensions of a given box.

    Args:
        bbox: List of integers representing a box. Length 4 and is in [x, y, w, h] format.

    Returns:
        A tuple (center, scale) where center is a NumPy array of size 2 representing the
        coordinates of the center of the box and scale is a NumPy array of size 2 representing
        the dimensions of the box.
    """
    x, y, w, h = bbox

    center = np.zeros(2, dtype=np.float32)
    center[0] = x + w / 2.0
    center[1] = y + h / 2.0

    scale = np.array([w, h], dtype=np.float32)

    return center, scale

def softmax(values: npt.ArrayLike) -> np.ndarray:
    """Returns softmax of a dataset with dimensions (N, k)."""
    exponential = np.exp(values)
    return exponential / np.sum(exponential, axis=1, keepdims=True)