import cv2
import numpy as np

from cv_analysis.utils.common import find_contours_and_hierarchies


def detect_large_coherent_structures(image: np.array):
    """Detects large coherent structures in an image.
    Expects an image with binary color space (e.g. threshold applied).

    Args:
        image (np.array): Image to look for large coherent structures in.

    Returns:
        list: List of contours.

    References:
         https://stackoverflow.com/questions/60259169/how-to-group-nearby-contours-in-opencv-python-zebra-crossing-detection
    """
    assert len(image.shape) == 2

    # FIXME: Parameterize via factory
    dilate_kernel = cv2.getStructuringElement(cv2.MORPH_OPEN, (5, 5))
    # FIXME: Parameterize via factory
    dilate = cv2.dilate(image, dilate_kernel, iterations=4)
    # FIXME: Parameterize via factory
    close_kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (20, 20))
    # FIXME: Parameterize via factory
    close = cv2.morphologyEx(dilate, cv2.MORPH_CLOSE, close_kernel, iterations=1)  # TODO: Tweak iterations

    contours, _ = find_contours_and_hierarchies(close)

    return contours