from typing import Optional, Iterable

import cv2
import numpy as np

import util as abu
from data.xhdfs import MIN_PIXEL_VALUE, MAX_PIXEL_VALUE

_WHITE = 255


def to_8_bit_image(src_image: np.ndarray,
                   display_min: Optional[int] = None,
                   display_max: Optional[int] = None) -> np.ndarray:
    """Copies the image and normalizes pixel values to [0; 255].

    See https://stackoverflow.com/questions/14464449/using-numpy-to-efficiently-convert-16-bit-image-data-to-8-bit-for-display-with"""

    if src_image.dtype == np.uint8:  # Do nothing with images that are already 8-bit
        return src_image

    copy = np.array(src_image, copy=True)

    # Clip pixel values if necessary
    need_to_clip = display_min is not None or display_max is not None

    if display_min is None:
        display_min = MIN_PIXEL_VALUE
    if display_max is None:
        display_max = MAX_PIXEL_VALUE

    if need_to_clip:
        copy.clip(display_min, display_max, out=copy)

    copy -= display_min
    np.floor_divide(copy, (display_max - display_min + 1) / 256, out=copy, casting='unsafe')

    return copy.astype(np.uint8)


def imshow_xhdfs_frame(frame: np.ndarray,
                       window_name: Optional[str] = None,
                       color_map: Optional[int] = None,
                       display_min: Optional[int] = None,
                       display_max: Optional[int] = None) -> None:
    frame_as_8_bit = to_8_bit_image(frame, display_min=display_min, display_max=display_max)
    if color_map:
        frame_as_8_bit = cv2.applyColorMap(frame_as_8_bit, color_map)

    if not window_name:
        window_name = __name__

    cv2.imshow(window_name, frame_as_8_bit)
    del frame_as_8_bit


def box_mask(box_points: Iterable[abu.FloatPoint],
             image_width: Optional[int] = None,
             image_height: Optional[int] = None) -> np.ndarray:
    image_width = image_width or abu.FRAME_WIDTH  # FIXME: hard-coded dimensions
    image_height = image_height or abu.FRAME_HEIGHT

    mask = np.zeros(shape=(image_height, image_width), dtype=np.uint8)
    box_corners = np.asarray(box_points, dtype=np.int32)
    cv2.fillConvexPoly(mask, box_corners, _WHITE)

    return mask