Classes

class WhiteBalanceAdjuster

WhiteBalanceAdjuster

This class is responsible for adjusting the white balance of an image.

Methods

• adjust(image: np.ndarray, reference_region: tuple[int, int, int, int] = (62, 80, 20, 20)) -> np.ndarray
  • This method adjusts the white balance of the image.

Example

import cv2 as cv
import numpy as np
from src.objs.image.utils.image_white_balancer import WhiteBalanceAdjuster

scanned_image = cv.imread('path/to/image.jpg')
adjusted_image = WhiteBalanceAdjuster.adjust(scanned_image)

Expand source code

class WhiteBalanceAdjuster:
    """
    # WhiteBalanceAdjuster
    This class is responsible for adjusting the white balance of an image.

    ## Methods
    - `adjust(image: np.ndarray, reference_region: tuple[int, int, int, int] = (62, 80, 20, 20)) -> np.ndarray`
        - This method adjusts the white balance of the image.
    
    ### Example
    ```python
    import cv2 as cv
    import numpy as np
    from src.objs.image.utils.image_white_balancer import WhiteBalanceAdjuster

    scanned_image = cv.imread('path/to/image.jpg')
    adjusted_image = WhiteBalanceAdjuster.adjust(scanned_image)
    ```
    """

    @staticmethod
    def adjust( image: np.ndarray, 
                reference_region: tuple[int, int, int, int] = (62, 80, 20, 20)
            ) -> np.ndarray:
        """
        Adjust the white balance of the image.
        Args:
            image: The image to adjust.
            reference_region: The top-left coordinates and size of the reference region.
        Returns:
            The white-balanced image.
        """

        # Get the top-left coordinates and size of the reference region
        reference_top_left, reference_size = reference_region[:2], reference_region[2:]

        # Create the reference 10x10 square for the reference region for white balancing
        reference_region = image[reference_top_left[1]:reference_top_left[1] + reference_size[1],
                                reference_top_left[0]:reference_top_left[0] + reference_size[0]]

        # Calculate the mean RGB values of the reference region - image white baseline value
        mean_reference = np.mean(reference_region, axis=(0, 1))

        # Scaling factors for each channel
        scale_factors = 255.0 / mean_reference

        # Apply white balancing to the entire image by multiplying the image to the scale factor
        balanced_image = cv.merge([cv.multiply(image[:, :, i], scale_factors[i]) for i in range(3)])

        # Clip the values to the valid range [0, 255]
        balanced_image = np.clip(balanced_image, 0, 255).astype(np.uint8)
        
        return balanced_image

Static methods

def adjust(image: numpy.ndarray, reference_region: tuple[int, int, int, int] = (62, 80, 20, 20)) ‑> numpy.ndarray

Adjust the white balance of the image.

Args

image

The image to adjust.

reference_region

The top-left coordinates and size of the reference region.

Returns

The white-balanced image.