e91f6c384f
The current LSC algorithm for the rkisp1 just forwards the LSC tables to the hardware, so absolute factors are needed and not ratios compared to green. Therefore every channel needs to be calculated independently. Signed-off-by: Stefan Klug <stefan.klug@ideasonboard.com> Reviewed-by: Laurent Pinchart <laurent.pinchart@ideasonboard.com> Reviewed-by: Paul Elder <paul.elder@ideasonboard.com>
116 lines
4 KiB
Python
116 lines
4 KiB
Python
# SPDX-License-Identifier: BSD-2-Clause
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#
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# Copyright (C) 2019, Raspberry Pi Ltd
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# Copyright (C) 2022, Paul Elder <paul.elder@ideasonboard.com>
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#
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# LSC module for tuning rkisp1
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from .lsc import LSC
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import libtuning as lt
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import libtuning.utils as utils
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from numbers import Number
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import numpy as np
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class LSCRkISP1(LSC):
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hr_name = 'LSC (RkISP1)'
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out_name = 'LensShadingCorrection'
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# \todo Not sure if this is useful. Probably will remove later.
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compatible = ['rkisp1']
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def __init__(self, *args, **kwargs):
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super().__init__(**kwargs)
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# We don't actually need anything from the config file
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def validate_config(self, config: dict) -> bool:
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return True
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# @return Image color temperature, flattened array of red calibration table
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# (containing {sector size} elements), flattened array of blue
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# calibration table, flattened array of (red's) green calibration
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# table, flattened array of (blue's) green calibration table
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def _do_single_lsc(self, image: lt.Image):
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# Perform LSC on each colour channel independently. A future enhancement
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# worth investigating would be splitting the luminance and chrominance
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# LSC as done by Raspberry Pi.
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cgr, _ = self._lsc_single_channel(image.channels[lt.Color.GR], image)
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cgb, _ = self._lsc_single_channel(image.channels[lt.Color.GB], image)
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cr, _ = self._lsc_single_channel(image.channels[lt.Color.R], image)
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cb, _ = self._lsc_single_channel(image.channels[lt.Color.B], image)
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return image.color, cr.flatten(), cb.flatten(), cgr.flatten(), cgb.flatten()
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# @return List of dictionaries of color temperature, red table, red's green
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# table, blue's green table, and blue table
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def _do_all_lsc(self, images: list) -> list:
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output_list = []
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output_map_func = lt.gradient.Linear().map
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# List of colour temperatures
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list_col = []
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# Associated calibration tables
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list_cr = []
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list_cb = []
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list_cgr = []
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list_cgb = []
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for image in self._enumerate_lsc_images(images):
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col, cr, cb, cgr, cgb = self._do_single_lsc(image)
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list_col.append(col)
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list_cr.append(cr)
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list_cb.append(cb)
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list_cgr.append(cgr)
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list_cgb.append(cgb)
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# Convert to numpy array for data manipulation
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list_col = np.array(list_col)
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list_cr = np.array(list_cr)
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list_cb = np.array(list_cb)
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list_cgr = np.array(list_cgr)
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list_cgb = np.array(list_cgb)
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for color_temperature in sorted(set(list_col)):
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# Average tables for the same colour temperature
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indices = np.where(list_col == color_temperature)
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color_temperature = int(color_temperature)
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tables = []
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for lis in [list_cr, list_cgr, list_cgb, list_cb]:
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table = np.mean(lis[indices], axis=0)
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table = output_map_func((1, 4), (1024, 4096), table)
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table = np.clip(table, 1024, 4095)
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table = np.round(table).astype('int32').tolist()
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tables.append(table)
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entry = {
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'ct': color_temperature,
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'r': tables[0],
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'gr': tables[1],
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'gb': tables[2],
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'b': tables[3],
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}
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output_list.append(entry)
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return output_list
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def process(self, config: dict, images: list, outputs: dict) -> dict:
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output = {}
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# \todo This should actually come from self.sector_{x,y}_gradient
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size_gradient = lt.gradient.Linear(lt.Remainder.Float)
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output['x-size'] = size_gradient.distribute(0.5, 8)
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output['y-size'] = size_gradient.distribute(0.5, 8)
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output['sets'] = self._do_all_lsc(images)
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if len(output['sets']) == 0:
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return None
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# \todo Validate images from greyscale camera and force grescale mode
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# \todo Debug functionality
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return output
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