from functools import reduce
from typing import Iterable

import cv2
import numpy as np
from funcy import first

from cv_analysis.utils.rectangle import Rectangle


def find_contours_and_hierarchies(image):
    contours, hierarchies = cv2.findContours(image, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
    return contours, first(hierarchies) if hierarchies is not None else None


def dilate_page_components(image: np.ndarray) -> np.ndarray:
    # FIXME: Parameterize via factory
    image = cv2.GaussianBlur(image, (7, 7), 0)
    # FIXME: Parameterize via factory
    thresh = cv2.threshold(image, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)[1]
    # FIXME: Parameterize via factory
    kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (5, 5))
    # FIXME: Parameterize via factory
    dilate = cv2.dilate(thresh, kernel, iterations=4)
    return dilate


def normalize_to_gray_scale(image: np.ndarray) -> np.ndarray:
    image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) if len(image.shape) > 2 else image
    return image


def threshold_image(image: np.ndarray) -> np.ndarray:
    # FIXME: Parameterize via factory
    _, image = cv2.threshold(image, 254, 255, cv2.THRESH_BINARY)
    return image


def invert_image(image: np.ndarray):
    return ~image


def fill_rectangles(image: np.ndarray, rectangles: Iterable[Rectangle]) -> np.ndarray:
    image = reduce(fill_in_component_area, rectangles, image)
    return image


def fill_in_component_area(image: np.ndarray, rectangle: Rectangle) -> np.ndarray:
    cv2.rectangle(image, (rectangle.x1, rectangle.y1), (rectangle.x2, rectangle.y2), (0, 0, 0), -1)
    cv2.rectangle(image, (rectangle.x1, rectangle.y1), (rectangle.x2, rectangle.y2), (255, 255, 255), 7)
    return image