from typing import Tuple

import numpy as np
import cv2

from config import BlurrinessConfig


class BlurrinessEstimator:
    def __init__(self, cfg: BlurrinessConfig):
        """
        Checks if an image is blurry or not, in respect to a user-defined threshold.
        The metric used here is the variance of the laplacian.
        Args:
            cfg: config for blurriness
        """
        self.threshold = cfg.threshold

    def __call__(self, img: np.ndarray) -> Tuple[bool, float]:
        """
        Compute the Laplacian of the image and then return the variance of the Laplacian,
        which is a decent indicator of image blur
        Args:
            img (np.ndarray): input image
        """

        laplacian = cv2.Laplacian(img, cv2.CV_64F)
        variance_of_laplacian = laplacian.var()
        is_blurry = variance_of_laplacian < self.threshold
        return is_blurry, variance_of_laplacian


if __name__ == "__main__":
    blur = BlurrinessEstimator(BlurrinessConfig())
    img = cv2.imread('data/104_IPHONE-SE_F.jpg')
    print(blur(img))