The colour gains are initialized with a default value of 1. Improve that by querying the auto white balance algorithm for the gains for a default colour temperature. This is still not based on measurements, but it is still better than the current implementation. If the algorithm doesn't implement mapping from colour temperature to gains, it will internally fallback to 1.0. Signed-off-by: Stefan Klug <stefan.klug@ideasonboard.com> Reviewed-by: Paul Elder <paul.elder@ideasonboard.com> Reviewed-by: Daniel Scally <dan.scally@ideasonboard.com>
406 lines
11 KiB
C++
406 lines
11 KiB
C++
/* SPDX-License-Identifier: LGPL-2.1-or-later */
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/*
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* Copyright (C) 2021-2022, Ideas On Board
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*
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* AWB control algorithm
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*/
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#include "awb.h"
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#include <algorithm>
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#include <ios>
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#include <libcamera/base/log.h>
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#include <libcamera/control_ids.h>
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#include <libcamera/ipa/core_ipa_interface.h>
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#include "libipa/awb_bayes.h"
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#include "libipa/awb_grey.h"
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#include "libipa/colours.h"
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/**
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* \file awb.h
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*/
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namespace libcamera {
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namespace ipa::rkisp1::algorithms {
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/**
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* \class Awb
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* \brief A Grey world white balance correction algorithm
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*/
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LOG_DEFINE_CATEGORY(RkISP1Awb)
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constexpr int32_t kMinColourTemperature = 2500;
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constexpr int32_t kMaxColourTemperature = 10000;
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constexpr int32_t kDefaultColourTemperature = 5000;
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/* Minimum mean value below which AWB can't operate. */
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constexpr double kMeanMinThreshold = 2.0;
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class RkISP1AwbStats : public AwbStats
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{
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public:
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RkISP1AwbStats(const RGB<double> &rgbMeans)
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: rgbMeans_(rgbMeans)
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{
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rg_ = rgbMeans_.r() / rgbMeans_.g();
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bg_ = rgbMeans_.b() / rgbMeans_.g();
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}
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double computeColourError(const RGB<double> &gains) const override
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{
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/*
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* Compute the sum of the squared colour error (non-greyness) as it
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* appears in the log likelihood equation.
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*/
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double deltaR = gains.r() * rg_ - 1.0;
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double deltaB = gains.b() * bg_ - 1.0;
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double delta2 = deltaR * deltaR + deltaB * deltaB;
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return delta2;
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}
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RGB<double> getRGBMeans() const override
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{
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return rgbMeans_;
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}
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private:
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RGB<double> rgbMeans_;
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double rg_;
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double bg_;
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};
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Awb::Awb()
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: rgbMode_(false)
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{
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}
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/**
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* \copydoc libcamera::ipa::Algorithm::init
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*/
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int Awb::init(IPAContext &context, const YamlObject &tuningData)
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{
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auto &cmap = context.ctrlMap;
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cmap[&controls::ColourTemperature] = ControlInfo(kMinColourTemperature,
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kMaxColourTemperature,
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kDefaultColourTemperature);
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if (!tuningData.contains("algorithm"))
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LOG(RkISP1Awb, Info) << "No awb algorithm specified."
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<< " Default to grey world";
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auto mode = tuningData["algorithm"].get<std::string>("grey");
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if (mode == "grey") {
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awbAlgo_ = std::make_unique<AwbGrey>();
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} else if (mode == "bayes") {
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awbAlgo_ = std::make_unique<AwbBayes>();
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} else {
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LOG(RkISP1Awb, Error) << "Unknown awb algorithm: " << mode;
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return -EINVAL;
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}
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LOG(RkISP1Awb, Debug) << "Using awb algorithm: " << mode;
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int ret = awbAlgo_->init(tuningData);
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if (ret) {
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LOG(RkISP1Awb, Error) << "Failed to init awb algorithm";
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return ret;
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}
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const auto &src = awbAlgo_->controls();
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cmap.insert(src.begin(), src.end());
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return 0;
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}
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/**
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* \copydoc libcamera::ipa::Algorithm::configure
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*/
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int Awb::configure(IPAContext &context,
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const IPACameraSensorInfo &configInfo)
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{
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context.activeState.awb.gains.manual = RGB<double>{ 1.0 };
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context.activeState.awb.gains.automatic =
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awbAlgo_->gainsFromColourTemperature(kDefaultColourTemperature);
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context.activeState.awb.autoEnabled = true;
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context.activeState.awb.temperatureK = kDefaultColourTemperature;
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/*
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* Define the measurement window for AWB as a centered rectangle
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* covering 3/4 of the image width and height.
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*/
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context.configuration.awb.measureWindow.h_offs = configInfo.outputSize.width / 8;
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context.configuration.awb.measureWindow.v_offs = configInfo.outputSize.height / 8;
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context.configuration.awb.measureWindow.h_size = 3 * configInfo.outputSize.width / 4;
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context.configuration.awb.measureWindow.v_size = 3 * configInfo.outputSize.height / 4;
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context.configuration.awb.enabled = true;
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return 0;
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}
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/**
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* \copydoc libcamera::ipa::Algorithm::queueRequest
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*/
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void Awb::queueRequest(IPAContext &context,
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[[maybe_unused]] const uint32_t frame,
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IPAFrameContext &frameContext,
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const ControlList &controls)
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{
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auto &awb = context.activeState.awb;
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const auto &awbEnable = controls.get(controls::AwbEnable);
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if (awbEnable && *awbEnable != awb.autoEnabled) {
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awb.autoEnabled = *awbEnable;
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LOG(RkISP1Awb, Debug)
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<< (*awbEnable ? "Enabling" : "Disabling") << " AWB";
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}
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awbAlgo_->handleControls(controls);
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frameContext.awb.autoEnabled = awb.autoEnabled;
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if (awb.autoEnabled)
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return;
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const auto &colourGains = controls.get(controls::ColourGains);
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const auto &colourTemperature = controls.get(controls::ColourTemperature);
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bool update = false;
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if (colourGains) {
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awb.gains.manual.r() = (*colourGains)[0];
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awb.gains.manual.b() = (*colourGains)[1];
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/*
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* \todo: Colour temperature reported in metadata is now
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* incorrect, as we can't deduce the temperature from the gains.
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* This will be fixed with the bayes AWB algorithm.
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*/
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update = true;
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} else if (colourTemperature) {
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const auto &gains = awbAlgo_->gainsFromColourTemperature(*colourTemperature);
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awb.gains.manual.r() = gains.r();
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awb.gains.manual.b() = gains.b();
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awb.temperatureK = *colourTemperature;
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update = true;
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}
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if (update)
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LOG(RkISP1Awb, Debug)
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<< "Set colour gains to " << awb.gains.manual;
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frameContext.awb.gains = awb.gains.manual;
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frameContext.awb.temperatureK = awb.temperatureK;
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}
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/**
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* \copydoc libcamera::ipa::Algorithm::prepare
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*/
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void Awb::prepare(IPAContext &context, const uint32_t frame,
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IPAFrameContext &frameContext, RkISP1Params *params)
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{
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/*
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* This is the latest time we can read the active state. This is the
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* most up-to-date automatic values we can read.
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*/
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if (frameContext.awb.autoEnabled) {
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frameContext.awb.gains = context.activeState.awb.gains.automatic;
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frameContext.awb.temperatureK = context.activeState.awb.temperatureK;
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}
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auto gainConfig = params->block<BlockType::AwbGain>();
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gainConfig.setEnabled(true);
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gainConfig->gain_green_b = std::clamp<int>(256 * frameContext.awb.gains.g(), 0, 0x3ff);
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gainConfig->gain_blue = std::clamp<int>(256 * frameContext.awb.gains.b(), 0, 0x3ff);
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gainConfig->gain_red = std::clamp<int>(256 * frameContext.awb.gains.r(), 0, 0x3ff);
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gainConfig->gain_green_r = std::clamp<int>(256 * frameContext.awb.gains.g(), 0, 0x3ff);
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/* If we have already set the AWB measurement parameters, return. */
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if (frame > 0)
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return;
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auto awbConfig = params->block<BlockType::Awb>();
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awbConfig.setEnabled(true);
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/* Configure the measure window for AWB. */
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awbConfig->awb_wnd = context.configuration.awb.measureWindow;
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/* Number of frames to use to estimate the means (0 means 1 frame). */
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awbConfig->frames = 0;
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/* Select RGB or YCbCr means measurement. */
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if (rgbMode_) {
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awbConfig->awb_mode = RKISP1_CIF_ISP_AWB_MODE_RGB;
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/*
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* For RGB-based measurements, pixels are selected with maximum
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* red, green and blue thresholds that are set in the
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* awb_ref_cr, awb_min_y and awb_ref_cb respectively. The other
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* values are not used, set them to 0.
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*/
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awbConfig->awb_ref_cr = 250;
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awbConfig->min_y = 250;
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awbConfig->awb_ref_cb = 250;
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awbConfig->max_y = 0;
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awbConfig->min_c = 0;
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awbConfig->max_csum = 0;
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} else {
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awbConfig->awb_mode = RKISP1_CIF_ISP_AWB_MODE_YCBCR;
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/* Set the reference Cr and Cb (AWB target) to white. */
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awbConfig->awb_ref_cb = 128;
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awbConfig->awb_ref_cr = 128;
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/*
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* Filter out pixels based on luminance and chrominance values.
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* The acceptable luma values are specified as a [16, 250]
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* range, while the acceptable chroma values are specified with
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* a minimum of 16 and a maximum Cb+Cr sum of 250.
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*/
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awbConfig->min_y = 16;
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awbConfig->max_y = 250;
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awbConfig->min_c = 16;
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awbConfig->max_csum = 250;
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}
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}
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/**
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* \copydoc libcamera::ipa::Algorithm::process
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*/
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void Awb::process(IPAContext &context,
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[[maybe_unused]] const uint32_t frame,
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IPAFrameContext &frameContext,
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const rkisp1_stat_buffer *stats,
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ControlList &metadata)
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{
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const rkisp1_cif_isp_stat *params = &stats->params;
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const rkisp1_cif_isp_awb_stat *awb = ¶ms->awb;
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IPAActiveState &activeState = context.activeState;
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RGB<double> rgbMeans = calculateRgbMeans(frameContext, awb);
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metadata.set(controls::AwbEnable, frameContext.awb.autoEnabled);
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metadata.set(controls::ColourGains, {
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static_cast<float>(frameContext.awb.gains.r()),
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static_cast<float>(frameContext.awb.gains.b())
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});
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metadata.set(controls::ColourTemperature, frameContext.awb.temperatureK);
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if (!stats || !(stats->meas_type & RKISP1_CIF_ISP_STAT_AWB)) {
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LOG(RkISP1Awb, Error) << "AWB data is missing in statistics";
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return;
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}
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/*
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* If the means are too small we don't have enough information to
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* meaningfully calculate gains. Freeze the algorithm in that case.
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*/
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if (rgbMeans.r() < kMeanMinThreshold && rgbMeans.g() < kMeanMinThreshold &&
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rgbMeans.b() < kMeanMinThreshold)
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return;
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RkISP1AwbStats awbStats{ rgbMeans };
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AwbResult awbResult = awbAlgo_->calculateAwb(awbStats, frameContext.lux.lux);
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activeState.awb.temperatureK = awbResult.colourTemperature;
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/* Metadata shall contain the up to date measurement */
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metadata.set(controls::ColourTemperature, activeState.awb.temperatureK);
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/*
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* Clamp the gain values to the hardware, which expresses gains as Q2.8
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* unsigned integer values. Set the minimum just above zero to avoid
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* divisions by zero when computing the raw means in subsequent
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* iterations.
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*/
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awbResult.gains = awbResult.gains.max(1.0 / 256).min(1023.0 / 256);
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/* Filter the values to avoid oscillations. */
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double speed = 0.2;
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awbResult.gains = awbResult.gains * speed +
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activeState.awb.gains.automatic * (1 - speed);
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activeState.awb.gains.automatic = awbResult.gains;
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LOG(RkISP1Awb, Debug)
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<< std::showpoint
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<< "Means " << rgbMeans << ", gains "
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<< activeState.awb.gains.automatic << ", temp "
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<< activeState.awb.temperatureK << "K";
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}
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RGB<double> Awb::calculateRgbMeans(const IPAFrameContext &frameContext, const rkisp1_cif_isp_awb_stat *awb) const
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{
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Vector<double, 3> rgbMeans;
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if (rgbMode_) {
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rgbMeans = {{
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static_cast<double>(awb->awb_mean[0].mean_y_or_g),
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static_cast<double>(awb->awb_mean[0].mean_cr_or_r),
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static_cast<double>(awb->awb_mean[0].mean_cb_or_b)
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}};
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} else {
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/* Get the YCbCr mean values */
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Vector<double, 3> yuvMeans({
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static_cast<double>(awb->awb_mean[0].mean_y_or_g),
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static_cast<double>(awb->awb_mean[0].mean_cb_or_b),
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static_cast<double>(awb->awb_mean[0].mean_cr_or_r)
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});
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/*
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* Convert from YCbCr to RGB. The hardware uses the following
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* formulas:
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*
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* Y = 16 + 0.2500 R + 0.5000 G + 0.1094 B
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* Cb = 128 - 0.1406 R - 0.2969 G + 0.4375 B
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* Cr = 128 + 0.4375 R - 0.3750 G - 0.0625 B
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*
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* This seems to be based on limited range BT.601 with Q1.6
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* precision.
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*
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* The inverse matrix is:
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*
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* [[1,1636, -0,0623, 1,6008]
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* [1,1636, -0,4045, -0,7949]
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* [1,1636, 1,9912, -0,0250]]
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*/
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static const Matrix<double, 3, 3> yuv2rgbMatrix({
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1.1636, -0.0623, 1.6008,
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1.1636, -0.4045, -0.7949,
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1.1636, 1.9912, -0.0250
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});
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static const Vector<double, 3> yuv2rgbOffset({
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16, 128, 128
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});
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rgbMeans = yuv2rgbMatrix * (yuvMeans - yuv2rgbOffset);
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/*
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* Due to hardware rounding errors in the YCbCr means, the
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* calculated RGB means may be negative. This would lead to
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* negative gains, messing up calculation. Prevent this by
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* clamping the means to positive values.
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*/
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rgbMeans = rgbMeans.max(0.0);
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}
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/*
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* The ISP computes the AWB means after applying the colour gains,
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* divide by the gains that were used to get the raw means from the
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* sensor.
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*/
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rgbMeans /= frameContext.awb.gains;
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return rgbMeans;
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}
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REGISTER_IPA_ALGORITHM(Awb, "Awb")
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} /* namespace ipa::rkisp1::algorithms */
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} /* namespace libcamera */
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