from functools import partial

import numpy as np
from funcy import lmap

from cv_analysis.figure_detection.figures import detect_large_coherent_structures
from cv_analysis.figure_detection.text import remove_primary_text_regions
from cv_analysis.utils.conversion import contour_to_rectangle
from cv_analysis.utils.filters import (
    is_large_enough,
    has_acceptable_format,
    is_small_enough,
)
from cv_analysis.utils.postprocessing import remove_included


def detect_figures(image: np.array):
    max_area = image.shape[0] * image.shape[1] * 0.99
    min_area = 5000
    max_width_to_height_ratio = 6
    figure_filter = partial(is_likely_figure, min_area, max_area, max_width_to_height_ratio)

    image = remove_primary_text_regions(image)
    contours = detect_large_coherent_structures(image)
    contours = filter(figure_filter, contours)

    rectangles = lmap(contour_to_rectangle, contours)
    rectangles = remove_included(rectangles)

    return rectangles


def is_likely_figure(min_area, max_area, max_width_to_height_ratio, contours):
    return (
        is_small_enough(contours, max_area)
        and is_large_enough(contours, min_area)
        and has_acceptable_format(contours, max_width_to_height_ratio)
    )