import cv2
import numpy as np
from typing import Tuple, Any

from numpy import ndarray

class BoardManager:

    def process_frame(self, prediction: object, image : np.ndarray, scale_size: tuple[int, int]) -> tuple[ndarray, ndarray] | None:
        try :
            mask = self.__get_mask(prediction)
            contour = self.__get_largest_contour(mask)
            corners = self.__approx_corners(contour)
            scaled_corners = self.__scale_corners(corners, mask.shape, image.shape)
            ordered_corners = self.__order_corners(scaled_corners)
            transformation_matrix = self.__calculte_transformation_matrix(ordered_corners, scale_size)
            warped_corners = cv2.perspectiveTransform(
                np.array(ordered_corners, np.float32).reshape(-1, 1, 2),
                transformation_matrix
            ).reshape(-1, 2)
            return warped_corners, transformation_matrix
        except Exception as e:
            print(e)
            return None

    def __calculte_transformation_matrix(self, corners: np.ndarray, output_size : tuple[int, int]) -> np.ndarray:
        width = output_size[0]
        height = output_size[1]

        dst = np.array([
            [0, 0],  # top-left
            [width - 1, 0],  # top-right
            [width - 1, height - 1],  # bottom-right
            [0, height - 1]  # bottom-left
        ], dtype=np.float32)
        return cv2.getPerspectiveTransform(corners, dst)

    def __get_mask(self, pred: object) -> Any:
        if pred.masks is None:
            raise ValueError("Board contour is not 4 corners")
        mask = pred.masks.data[0].cpu().numpy()
        mask = (mask * 255).astype(np.uint8)
        return mask

    def __get_largest_contour(self, mask: np.ndarray) -> np.ndarray:
        contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
        if not contours:
            raise ValueError("No contours found")
        return max(contours, key=cv2.contourArea)

    def __approx_corners(self, contour: np.ndarray) -> np.ndarray:
        epsilon = 0.02 * cv2.arcLength(contour, True)
        approx = cv2.approxPolyDP(contour, epsilon, True)
        if len(approx) != 4:
            raise ValueError("Board contour is not 4 corners")
        return approx.reshape(4, 2)

    def __scale_corners(self, pts: np.ndarray, mask_shape: Tuple[int, int], image_shape: Tuple[int, int, int]) -> np.ndarray:
        mask_h, mask_w = mask_shape
        img_h, img_w = image_shape[:2]
        scale_x = img_w / mask_w
        scale_y = img_h / mask_h
        scaled_pts = [(int(p[0] * scale_x), int(p[1] * scale_y)) for p in pts]
        return np.array(scaled_pts, dtype=np.float32)

    def __order_corners(self, pts: np.ndarray) -> np.ndarray:
        rect = np.zeros((4, 2), dtype="float32")
        s = pts.sum(axis=1)
        rect[0] = pts[np.argmin(s)]  # top-left
        rect[2] = pts[np.argmax(s)]  # bottom-right
        diff = np.diff(pts, axis=1)
        rect[1] = pts[np.argmin(diff)]  # top-right
        rect[3] = pts[np.argmax(diff)]  # bottom-left
        return rect