src/ipa/rkisp1/algorithms/lsc.h


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/* SPDX-License-Identifier: LGPL-2.1-or-later */
/*
 * Copyright (C) 2021-2022, Ideas On Board
 *
 * lsc.h - RkISP1 Lens Shading Correction control
 */

#pragma once

#include "algorithm.h"

namespace libcamera {

namespace ipa::rkisp1::algorithms {

class LensShadingCorrection : public Algorithm
{
public:
	LensShadingCorrection();
	~LensShadingCorrection() = default;

	int init(IPAContext &context, const YamlObject &tuningData) override;
	int configure(IPAContext &context, const IPACameraSensorInfo &configInfo) override;
	void prepare(IPAContext &context, rkisp1_params_cfg *params) override;

private:
	bool initialized_;

	std::vector<uint16_t> rData_;
	std::vector<uint16_t> grData_;
	std::vector<uint16_t> gbData_;
	std::vector<uint16_t> bData_;

	std::vector<double> xSize_;
	std::vector<double> ySize_;
};

} /* namespace ipa::rkisp1::algorithms */
} /* namespace libcamera */
# SPDX-License-Identifier: BSD-2-Clause
#
# Copyright (C) 2019, Raspberry Pi (Trading) Limited
#
# ctt_ccm.py - camera tuning tool for CCM (colour correction matrix)

from ctt_image_load import *
from ctt_awb import get_alsc_patches


"""
takes 8-bit macbeth chart values, degammas and returns 16 bit
"""
def degamma(x):
    x = x / ((2**8)-1)
    x = np.where(x < 0.04045, x/12.92, ((x+0.055)/1.055)**2.4)
    x = x * ((2**16)-1)
    return x


"""
FInds colour correction matrices for list of images
"""
def ccm(Cam, cal_cr_list, cal_cb_list):
    imgs = Cam.imgs
    """
    standard macbeth chart colour values
    """
    m_rgb = np.array([  # these are in sRGB
        [116, 81, 67],    # dark skin
        [199, 147, 129],  # light skin
        [91, 122, 156],   # blue sky
        [90, 108, 64],    # foliage
        [130, 128, 176],  # blue flower
        [92, 190, 172],   # bluish green
        [224, 124, 47],   # orange
        [68, 91, 170],     # purplish blue
        [198, 82, 97],    # moderate red
        [94, 58, 106],    # purple
        [159, 189, 63],   # yellow green
        [230, 162, 39],   # orange yellow
        [35, 63, 147],    # blue
        [67, 149, 74],    # green
        [180, 49, 57],    # red
        [238, 198, 20],   # yellow
        [193, 84, 151],   # magenta
        [0, 136, 170],    # cyan (goes out of gamut)
        [245, 245, 243],  # white 9.5
        [200, 202, 202],  # neutral 8
        [161, 163, 163],  # neutral 6.5
        [121, 121, 122],  # neutral 5
        [82, 84, 86],     # neutral 3.5
        [49, 49, 51]      # black 2
    ])

    """
    convert reference colours from srgb to rgb
    """
    m_srgb = degamma(m_rgb)
    """
    reorder reference values to match how patches are ordered
    """
    m_srgb = np.array([m_srgb[i::6] for i in range(6)]).reshape((24, 3))

    """
    reformat alsc correction tables or set colour_cals to None if alsc is
    deactivated
    """
    if cal_cr_list is None:
        colour_cals = None
    else:
        colour_cals = {}
        for cr, cb in zip(cal_cr_list, cal_cb_list):
            cr_tab = cr['table']
            cb_tab = cb['table']
            """
            normalise tables so min value is 1
            """
            cr_tab = cr_tab/np.min(cr_tab)
            cb_tab = cb_tab/np.min(cb_tab)
            colour_cals[cr['ct']] = [cr_tab, cb_tab]

    """
    for each image, perform awb and alsc corrections.
    Then calculate the colour correction matrix for that image, recording the
    ccm and the colour tempertaure.