# SPDX-License-Identifier: BSD-2-Clause # # Copyright (C) 2019, Raspberry Pi Ltd # Copyright (C) 2022, Paul Elder <paul.elder@ideasonboard.com> from ..module import Module import libtuning as lt import libtuning.utils as utils import numpy as np class LSC(Module): type = 'lsc' hr_name = 'LSC (Base)' out_name = 'GenericLSC' def __init__(self, *, debug: list, sector_shape: tuple, sector_x_gradient: lt.Gradient, sector_y_gradient: lt.Gradient, sector_average_function: lt.Average, smoothing_function: lt.Smoothing): super().__init__() self.debug = debug self.sector_shape = sector_shape self.sector_x_gradient = sector_x_gradient self.sector_y_gradient = sector_y_gradient self.sector_average_function = sector_average_function self.smoothing_function = smoothing_function def _enumerate_lsc_images(self, images): for image in images: if image.lsc_only: yield image def _get_grid(self, channel, img_w, img_h): # List of number of pixels in each sector sectors_x = self.sector_x_gradient.distribute(img_w / 2, self.sector_shape[0]) sectors_y = self.sector_y_gradient.distribute(img_h / 2, self.sector_shape[1]) grid = [] r = 0 for y in sectors_y: c = 0 for x in sectors_x: grid.append(self.sector_average_function.average(channel[r:r + y, c:c + x])) c += x r += y return np.array(grid) def _lsc_single_channel(self, channel: np.array, image: lt.Image, green_grid: np.array = None): grid = self._get_grid(channel, image.w, image.h) grid -= image.blacklevel_16 if green_grid is None: table = np.reshape(1 / grid, self.sector_shape[::-1]) else: table = np.reshape(green_grid / grid, self.sector_shape[::-1]) table = self.smoothing_function.smoothing(table) if green_grid is None: table = table / np.min(table) return table, grid