fix alpha inpainting

    '''

    result_alpha = original_alpha.copy()

    return result_alpha

    # Analyze the alpha values around the original mask to determine appropriate transparency

    mask_dilated = cv2.dilate((mask > 0).astype(np.uint8), np.ones((15, 15), np.uint8), iterations=1)

    surrounding_mask = mask_dilated - (mask > 0).astype(np.uint8)

    mask_dilated = cv2.dilate((mask > 127).astype(np.uint8), np.ones((15, 15), np.uint8), iterations=1)

    surrounding_mask = mask_dilated - (mask > 127).astype(np.uint8)

    if np.any(surrounding_mask > 0):

        surrounding_alpha = original_alpha[surrounding_mask > 0]

        if len(surrounding_alpha) > 0:

            median_surrounding_alpha = np.median(surrounding_alpha)

            result_alpha[surrounding_mask] = median_surrounding_alpha

            # If surrounding area is mostly transparent (median alpha < 128),

            # make inpainted areas transparent too

            if median_surrounding_alpha < 128:

                inpainted_mask = (mask > 127)

                result_alpha[inpainted_mask] = median_surrounding_alpha

    return result_alpha

class InpainterBase(BaseModule):

    inpaint_by_block = True

            # Recombine with alpha if original was RGBA

            if original_alpha is not None:

                result_alpha = inpaint_handle_alpha_channel(original_alpha, mask)

                result_alpha = inpaint_handle_alpha_channel(original_alpha, original_mask)

                return np.concatenate([inpainted, result_alpha], axis=2)

            return inpainted

            balloon_areas = np.where(ballon_mask > 0)

            if len(img.shape) == 3 and img.shape[2] == 4:

                avg_alpha = np.mean(img[balloon_areas][..., 3])

                avg_alpha = 0 if avg_alpha < 127 else avg_alpha

                bg_pixel_value.append(avg_alpha)

            bg_pixel_value = np.array(np.round(bg_pixel_value), dtype=np.uint8)

            img[balloon_areas] = bg_pixel_value