Stefan Klug
14f6a87917
Based on the input images, the lsc values could exceed the range allowed by the rkisp1. As we are now clipping the values, we can simplify the value mapping. 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>
114 lines
3.9 KiB
Python
114 lines
3.9 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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cgr, gr = self._lsc_single_channel(image.channels[lt.Color.GR], image)
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cgb, gb = self._lsc_single_channel(image.channels[lt.Color.GB], image)
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# \todo Should these ratio against the average of both greens or just
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# each green like we've done here?
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cr, _ = self._lsc_single_channel(image.channels[lt.Color.R], image, gr)
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cb, _ = self._lsc_single_channel(image.channels[lt.Color.B], image, gb)
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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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# \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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