import numpy as np
from shapely import geometry
import cv2

def filter_contours_area_of_image(image, contours, hirarchy, max_area, min_area):
    found_polygons_early = list()

    jv = 0
    for c in contours:
        if len(c) < 3:  # A polygon cannot have less than 3 points
            continue

        polygon = geometry.Polygon([point[0] for point in c])
        area = polygon.area
        if area >= min_area * np.prod(image.shape[:2]) and area <= max_area * np.prod(image.shape[:2]) and hirarchy[0][jv][3] == -1:  # and hirarchy[0][jv][3]==-1 :
            found_polygons_early.append(np.array([[point] for point in polygon.exterior.coords], dtype=np.uint))
        jv += 1
    return found_polygons_early

def filter_contours_area_of_image_interiors(image, contours, hirarchy, max_area, min_area):
    found_polygons_early = list()

    jv = 0
    for c in contours:
        if len(c) < 3:  # A polygon cannot have less than 3 points
            continue

        polygon = geometry.Polygon([point[0] for point in c])
        area = polygon.area
        if area >= min_area * np.prod(image.shape[:2]) and area <= max_area * np.prod(image.shape[:2]) and hirarchy[0][jv][3] != -1:
            # print(c[0][0][1])
            found_polygons_early.append(np.array([point for point in polygon.exterior.coords], dtype=np.uint))
        jv += 1
    return found_polygons_early


def filter_contours_area_of_image_tables(image, contours, hirarchy, max_area, min_area):
    found_polygons_early = list()

    jv = 0
    for c in contours:
        if len(c) < 3:  # A polygon cannot have less than 3 points
            continue

        polygon = geometry.Polygon([point[0] for point in c])
        # area = cv2.contourArea(c)
        area = polygon.area
        ##print(np.prod(thresh.shape[:2]))
        # Check that polygon has area greater than minimal area
        # print(hirarchy[0][jv][3],hirarchy )
        if area >= min_area * np.prod(image.shape[:2]) and area <= max_area * np.prod(image.shape[:2]):  # and hirarchy[0][jv][3]==-1 :
            # print(c[0][0][1])
            found_polygons_early.append(np.array([[point] for point in polygon.exterior.coords], dtype=np.int32))
        jv += 1
    return found_polygons_early

def resize_image(img_in, input_height, input_width):
    return cv2.resize(img_in, (input_width, input_height), interpolation=cv2.INTER_NEAREST)

def rotatedRectWithMaxArea(w, h, angle):
    if w <= 0 or h <= 0:
        return 0, 0

    width_is_longer = w >= h
    side_long, side_short = (w, h) if width_is_longer else (h, w)

    # since the solutions for angle, -angle and 180-angle are all the same,
    # if suffices to look at the first quadrant and the absolute values of sin,cos:
    sin_a, cos_a = abs(math.sin(angle)), abs(math.cos(angle))
    if side_short <= 2.0 * sin_a * cos_a * side_long or abs(sin_a - cos_a) < 1e-10:
        # half constrained case: two crop corners touch the longer side,
        #   the other two corners are on the mid-line parallel to the longer line
        x = 0.5 * side_short
        wr, hr = (x / sin_a, x / cos_a) if width_is_longer else (x / cos_a, x / sin_a)
    else:
        # fully constrained case: crop touches all 4 sides
        cos_2a = cos_a * cos_a - sin_a * sin_a
        wr, hr = (w * cos_a - h * sin_a) / cos_2a, (h * cos_a - w * sin_a) / cos_2a

    return wr, hr

def rotate_max_area_new(image, rotated, angle):
    wr, hr = rotatedRectWithMaxArea(image.shape[1], image.shape[0], math.radians(angle))
    h, w, _ = rotated.shape
    y1 = h // 2 - int(hr / 2)
    y2 = y1 + int(hr)
    x1 = w // 2 - int(wr / 2)
    x2 = x1 + int(wr)
    return rotated[y1:y2, x1:x2]

def rotation_image_new(img, thetha):
    rotated = imutils.rotate(img, thetha)
    return rotate_max_area_new(img, rotated, thetha)