import cv2
import numpy as np


MASK_VALUE = 255
ADAPTIVE_BLOCK_SIZE = 35
ADAPTIVE_OFFSET = 8
BACKGROUND_RING_WIDTH = 3
MIN_COMPONENT_AREA = 2
DEFAULT_MARGIN = 2
MAX_MARGIN = 10
POLARITY_AUTO = "Auto"
POLARITY_DARK = "Dark text"
POLARITY_LIGHT = "Light text"
POLARITY_CHOICES = [POLARITY_AUTO, POLARITY_DARK, POLARITY_LIGHT]


def character_mask(rgb_image, polygons, margin=DEFAULT_MARGIN, polarity=POLARITY_AUTO):
    margin = int(margin)
    if not 0 <= margin <= MAX_MARGIN:
        raise ValueError(f"Margin must be between 0 and {MAX_MARGIN}")
    if polarity not in POLARITY_CHOICES:
        raise ValueError("Invalid text polarity")

    gray = cv2.cvtColor(rgb_image, cv2.COLOR_RGB2GRAY)
    height, width = gray.shape
    mask = np.zeros_like(gray)
    padding = max(ADAPTIVE_BLOCK_SIZE // 2, BACKGROUND_RING_WIDTH)
    ring_size = BACKGROUND_RING_WIDTH * 2 + 1
    ring_kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (ring_size, ring_size))

    for polygon in polygons:
        points = np.asarray(polygon, dtype=np.float32).reshape(-1, 2)
        if len(points) < 3 or not np.isfinite(points).all():
            continue
        points = np.rint(points).astype(np.int32)
        x, y, box_width, box_height = cv2.boundingRect(points)
        left, top = max(0, x - padding), max(0, y - padding)
        right = min(width, x + box_width + padding)
        bottom = min(height, y + box_height + padding)
        if left >= right or top >= bottom:
            continue

        crop = gray[top:bottom, left:right]
        region = np.zeros_like(crop)
        cv2.fillPoly(region, [points - (left, top)], MASK_VALUE)
        inside = region != 0
        if not np.any(inside):
            continue

        selected_polarity = polarity
        if selected_polarity == POLARITY_AUTO:
            ring = (cv2.dilate(region, ring_kernel) != 0) & ~inside
            background = np.median(crop[ring] if np.any(ring) else crop[inside])
            split, _ = cv2.threshold(
                crop[inside], 0, MASK_VALUE, cv2.THRESH_BINARY | cv2.THRESH_OTSU
            )
            selected_polarity = POLARITY_DARK if background > split else POLARITY_LIGHT

        dark_text = selected_polarity == POLARITY_DARK
        threshold_type = cv2.THRESH_BINARY_INV if dark_text else cv2.THRESH_BINARY
        offset = ADAPTIVE_OFFSET if dark_text else -ADAPTIVE_OFFSET
        foreground = cv2.adaptiveThreshold(
            crop,
            MASK_VALUE,
            cv2.ADAPTIVE_THRESH_GAUSSIAN_C,
            threshold_type,
            ADAPTIVE_BLOCK_SIZE,
            offset,
        )
        foreground = cv2.bitwise_and(foreground, region)
        count, labels, stats, _ = cv2.connectedComponentsWithStats(foreground, connectivity=8)
        keep = np.zeros(count, dtype=np.uint8)
        keep[1:] = (stats[1:, cv2.CC_STAT_AREA] >= MIN_COMPONENT_AREA) * MASK_VALUE
        cleaned = keep[labels]
        target = mask[top:bottom, left:right]
        np.maximum(target, cleaned, out=target)

    if margin:
        kernel_size = margin * 2 + 1
        kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (kernel_size, kernel_size))
        mask = cv2.dilate(mask, kernel)

    return mask