diff options
Diffstat (limited to 'src/ipa/libipa')
34 files changed, 2369 insertions, 1247 deletions
diff --git a/src/ipa/libipa/agc_mean_luminance.cpp b/src/ipa/libipa/agc_mean_luminance.cpp index f97ef117..02555a44 100644 --- a/src/ipa/libipa/agc_mean_luminance.cpp +++ b/src/ipa/libipa/agc_mean_luminance.cpp @@ -89,10 +89,10 @@ static constexpr double kDefaultRelativeLuminanceTarget = 0.16; * \class AgcMeanLuminance * \brief A mean-based auto-exposure algorithm * - * This algorithm calculates a shutter time, analogue and digital gain such that - * the normalised mean luminance value of an image is driven towards a target, - * which itself is discovered from tuning data. The algorithm is a two-stage - * process. + * This algorithm calculates an exposure time, analogue and digital gain such + * that the normalised mean luminance value of an image is driven towards a + * target, which itself is discovered from tuning data. The algorithm is a + * two-stage process. * * In the first stage, an initial gain value is derived by iteratively comparing * the gain-adjusted mean luminance across the entire image against a target, @@ -109,7 +109,7 @@ static constexpr double kDefaultRelativeLuminanceTarget = 0.16; * stage is then clamped to the gain from this stage. * * The final gain is used to adjust the effective exposure value of the image, - * and that new exposure value is divided into shutter time, analogue gain and + * and that new exposure value is divided into exposure time, analogue gain and * digital gain according to the selected AeExposureMode. This class uses the * \ref ExposureModeHelper class to assist in that division, and expects the * data needed to initialise that class to be present in tuning data in a @@ -247,27 +247,27 @@ int AgcMeanLuminance::parseExposureModes(const YamlObject &tuningData) return -EINVAL; } - std::vector<uint32_t> shutters = - modeValues["shutter"].getList<uint32_t>().value_or(std::vector<uint32_t>{}); + std::vector<uint32_t> exposureTimes = + modeValues["exposureTime"].getList<uint32_t>().value_or(std::vector<uint32_t>{}); std::vector<double> gains = modeValues["gain"].getList<double>().value_or(std::vector<double>{}); - if (shutters.size() != gains.size()) { + if (exposureTimes.size() != gains.size()) { LOG(AgcMeanLuminance, Error) - << "Shutter and gain array sizes unequal"; + << "Exposure time and gain array sizes unequal"; return -EINVAL; } - if (shutters.empty()) { + if (exposureTimes.empty()) { LOG(AgcMeanLuminance, Error) - << "Shutter and gain arrays are empty"; + << "Exposure time and gain arrays are empty"; return -EINVAL; } std::vector<std::pair<utils::Duration, double>> stages; - for (unsigned int i = 0; i < shutters.size(); i++) { + for (unsigned int i = 0; i < exposureTimes.size(); i++) { stages.push_back({ - std::chrono::microseconds(shutters[i]), + std::chrono::microseconds(exposureTimes[i]), gains[i] }); } @@ -283,7 +283,7 @@ int AgcMeanLuminance::parseExposureModes(const YamlObject &tuningData) /* * If we don't have any exposure modes in the tuning data we create an * ExposureModeHelper using an empty vector of stages. This will result - * in the ExposureModeHelper simply driving the shutter as high as + * in the ExposureModeHelper simply driving the exposure time as high as * possible before touching gain. */ if (availableExposureModes.empty()) { @@ -338,18 +338,18 @@ int AgcMeanLuminance::parseExposureModes(const YamlObject &tuningData) * For the AeExposureMode control the data should contain a dictionary called * AeExposureMode containing per-mode setting dictionaries with the key being a * value from \ref controls::AeExposureModeNameValueMap. Each mode dict should - * contain an array of shutter times with the key "shutter" and an array of gain - * values with the key "gain", in this format: + * contain an array of exposure times with the key "exposureTime" and an array + * of gain values with the key "gain", in this format: * * \code{.unparsed} * algorithms: * - Agc: * AeExposureMode: * ExposureNormal: - * shutter: [ 100, 10000, 30000, 60000, 120000 ] + * exposureTime: [ 100, 10000, 30000, 60000, 120000 ] * gain: [ 2.0, 4.0, 6.0, 8.0, 10.0 ] * ExposureShort: - * shutter: [ 100, 10000, 30000, 60000, 120000 ] + * exposureTime: [ 100, 10000, 30000, 60000, 120000 ] * gain: [ 2.0, 4.0, 6.0, 8.0, 10.0 ] * * \endcode @@ -371,20 +371,20 @@ int AgcMeanLuminance::parseTuningData(const YamlObject &tuningData) /** * \brief Set the ExposureModeHelper limits for this class - * \param[in] minShutter Minimum shutter time to allow - * \param[in] maxShutter Maximum shutter time to allow + * \param[in] minExposureTime Minimum exposure time to allow + * \param[in] maxExposureTime Maximum ewposure time to allow * \param[in] minGain Minimum gain to allow * \param[in] maxGain Maximum gain to allow * * This function calls \ref ExposureModeHelper::setLimits() for each * ExposureModeHelper that has been created for this class. */ -void AgcMeanLuminance::setLimits(utils::Duration minShutter, - utils::Duration maxShutter, +void AgcMeanLuminance::setLimits(utils::Duration minExposureTime, + utils::Duration maxExposureTime, double minGain, double maxGain) { for (auto &[id, helper] : exposureModeHelpers_) - helper->setLimits(minShutter, maxShutter, minGain, maxGain); + helper->setLimits(minExposureTime, maxExposureTime, minGain, maxGain); } /** @@ -513,7 +513,8 @@ utils::Duration AgcMeanLuminance::filterExposure(utils::Duration exposureValue) } /** - * \brief Calculate the new exposure value and splut it between shutter time and gain + * \brief Calculate the new exposure value and splut it between exposure time + * and gain * \param[in] constraintModeIndex The index of the current constraint mode * \param[in] exposureModeIndex The index of the current exposure mode * \param[in] yHist A Histogram from the ISP statistics to use in constraining @@ -523,9 +524,9 @@ utils::Duration AgcMeanLuminance::filterExposure(utils::Duration exposureValue) * * Calculate a new exposure value to try to obtain the target. The calculated * exposure value is filtered to prevent rapid changes from frame to frame, and - * divided into shutter time, analogue and digital gain. + * divided into exposure time, analogue and digital gain. * - * \return Tuple of shutter time, analogue gain, and digital gain + * \return Tuple of exposure time, analogue gain, and digital gain */ std::tuple<utils::Duration, double, double> AgcMeanLuminance::calculateNewEv(uint32_t constraintModeIndex, diff --git a/src/ipa/libipa/agc_mean_luminance.h b/src/ipa/libipa/agc_mean_luminance.h index 576d28be..c41391cb 100644 --- a/src/ipa/libipa/agc_mean_luminance.h +++ b/src/ipa/libipa/agc_mean_luminance.h @@ -44,7 +44,7 @@ public: int parseTuningData(const YamlObject &tuningData); - void setLimits(utils::Duration minShutter, utils::Duration maxShutter, + void setLimits(utils::Duration minExposureTime, utils::Duration maxExposureTime, double minGain, double maxGain); std::map<int32_t, std::vector<AgcConstraint>> constraintModes() diff --git a/src/ipa/libipa/awb.cpp b/src/ipa/libipa/awb.cpp new file mode 100644 index 00000000..6157bd43 --- /dev/null +++ b/src/ipa/libipa/awb.cpp @@ -0,0 +1,265 @@ +/* SPDX-License-Identifier: LGPL-2.1-or-later */ +/* + * Copyright (C) 2024 Ideas on Board Oy + * + * Generic AWB algorithms + */ + +#include "awb.h" + +#include <libcamera/base/log.h> + +#include <libcamera/control_ids.h> + +/** + * \file awb.h + * \brief Base classes for AWB algorithms + */ + +namespace libcamera { + +LOG_DEFINE_CATEGORY(Awb) + +namespace ipa { + +/** + * \class AwbResult + * \brief The result of an awb calculation + * + * This class holds the result of an auto white balance calculation. + */ + +/** + * \var AwbResult::gains + * \brief The calculated white balance gains + */ + +/** + * \var AwbResult::colourTemperature + * \brief The calculated colour temperature in Kelvin + */ + +/** + * \class AwbStats + * \brief An abstraction class wrapping hardware-specific AWB statistics + * + * Pipeline handlers using an AWB algorithm based on the AwbAlgorithm class need + * to implement this class to give the algorithm access to the hardware-specific + * statistics data. + */ + +/** + * \fn AwbStats::computeColourError + * \brief Compute an error value for when the given gains would be applied + * \param[in] gains The gains to apply + * + * Compute an error value (non-greyness) assuming the given \a gains would be + * applied. To keep the actual implementations computationally inexpensive, + * the squared colour error shall be returned. + * + * If the awb statistics provide multiple zones, the average of the individual + * squared errors shall be returned. Averaging/normalizing is necessary so that + * the numeric dimensions are the same on all hardware platforms. + * + * \return The computed error value + */ + +/** + * \fn AwbStats::getRGBMeans + * \brief Get RGB means of the statistics + * + * Fetch the RGB means from the statistics. The values of each channel are + * dimensionless and only the ratios are used for further calculations. This is + * used by the simple gray world model to calculate the gains to apply. + * + * \return The RGB means + */ + +/** + * \class AwbAlgorithm + * \brief A base class for auto white balance algorithms + * + * This class is a base class for auto white balance algorithms. It defines an + * interface for the algorithms to implement, and is used by the IPAs to + * interact with the concrete implementation. + */ + +/** + * \fn AwbAlgorithm::init + * \brief Initialize the algorithm with the given tuning data + * \param[in] tuningData The tuning data to use for the algorithm + * + * \return 0 on success, a negative error code otherwise + */ + +/** + * \fn AwbAlgorithm::calculateAwb + * \brief Calculate awb data from the given statistics + * \param[in] stats The statistics to use for the calculation + * \param[in] lux The lux value of the scene + * + * Calculate an AwbResult object from the given statistics and lux value. A \a + * lux value of 0 means it is unknown or invalid and the algorithm shall ignore + * it. + * + * \return The awb result + */ + +/** + * \fn AwbAlgorithm::gainsFromColourTemperature + * \brief Compute white balance gains from a colour temperature + * \param[in] colourTemperature The colour temperature in Kelvin + * + * Compute the white balance gains from a \a colourTemperature. This function + * does not take any statistics into account. It is used to compute the colour + * gains when the user manually specifies a colour temperature. + * + * \return The colour gains + */ + +/** + * \fn AwbAlgorithm::controls + * \brief Get the controls info map for this algorithm + * + * \return The controls info map + */ + +/** + * \fn AwbAlgorithm::handleControls + * \param[in] controls The controls to handle + * \brief Handle the controls supplied in a request + */ + +/** + * \var AwbAlgorithm::controls_ + * \brief Controls info map for the controls provided by the algorithm + */ + +/** + * \var AwbAlgorithm::modes_ + * \brief Map of all configured modes + * \sa AwbAlgorithm::parseModeConfigs + */ + +/** + * \class AwbAlgorithm::ModeConfig + * \brief Holds the configuration of a single AWB mode + * + * Awb modes limit the regulation of the AWB algorithm to a specific range of + * colour temperatures. + */ + +/** + * \var AwbAlgorithm::ModeConfig::ctLo + * \brief The lowest valid colour temperature of that mode + */ + +/** + * \var AwbAlgorithm::ModeConfig::ctHi + * \brief The highest valid colour temperature of that mode + */ + +/** + * \brief Parse the mode configurations from the tuning data + * \param[in] tuningData the YamlObject representing the tuning data + * \param[in] def The default value for the AwbMode control + * + * Utility function to parse the tuning data for an AwbMode entry and read all + * provided modes. It adds controls::AwbMode to AwbAlgorithm::controls_ and + * populates AwbAlgorithm::modes_. For a list of possible modes see \ref + * controls::AwbModeEnum. + * + * Each mode entry must contain a "lo" and "hi" key to specify the lower and + * upper colour temperature of that mode. For example: + * + * \code{.unparsed} + * algorithms: + * - Awb: + * AwbMode: + * AwbAuto: + * lo: 2500 + * hi: 8000 + * AwbIncandescent: + * lo: 2500 + * hi: 3000 + * ... + * \endcode + * + * If \a def is supplied but not contained in the the \a tuningData, -EINVAL is + * returned. + * + * \sa controls::AwbModeEnum + * \return Zero on success, negative error code otherwise + */ +int AwbAlgorithm::parseModeConfigs(const YamlObject &tuningData, + const ControlValue &def) +{ + std::vector<ControlValue> availableModes; + + const YamlObject &yamlModes = tuningData[controls::AwbMode.name()]; + if (!yamlModes.isDictionary()) { + LOG(Awb, Error) + << "AwbModes must be a dictionary."; + return -EINVAL; + } + + for (const auto &[modeName, modeDict] : yamlModes.asDict()) { + if (controls::AwbModeNameValueMap.find(modeName) == + controls::AwbModeNameValueMap.end()) { + LOG(Awb, Warning) + << "Skipping unknown awb mode '" + << modeName << "'"; + continue; + } + + if (!modeDict.isDictionary()) { + LOG(Awb, Error) + << "Invalid awb mode '" << modeName << "'"; + return -EINVAL; + } + + const auto &modeValue = static_cast<controls::AwbModeEnum>( + controls::AwbModeNameValueMap.at(modeName)); + + ModeConfig &config = modes_[modeValue]; + + auto hi = modeDict["hi"].get<double>(); + if (!hi) { + LOG(Awb, Error) << "Failed to read hi param of mode " + << modeName; + return -EINVAL; + } + config.ctHi = *hi; + + auto lo = modeDict["lo"].get<double>(); + if (!lo) { + LOG(Awb, Error) << "Failed to read low param of mode " + << modeName; + return -EINVAL; + } + config.ctLo = *lo; + + availableModes.push_back(modeValue); + } + + if (modes_.empty()) { + LOG(Awb, Error) << "No AWB modes configured"; + return -EINVAL; + } + + if (!def.isNone() && + modes_.find(def.get<controls::AwbModeEnum>()) == modes_.end()) { + const auto &names = controls::AwbMode.enumerators(); + LOG(Awb, Error) << names.at(def.get<controls::AwbModeEnum>()) + << " mode is missing in the configuration."; + return -EINVAL; + } + + controls_[&controls::AwbMode] = ControlInfo(availableModes, def); + + return 0; +} + +} /* namespace ipa */ + +} /* namespace libcamera */ diff --git a/src/ipa/libipa/awb.h b/src/ipa/libipa/awb.h new file mode 100644 index 00000000..4a1b012a --- /dev/null +++ b/src/ipa/libipa/awb.h @@ -0,0 +1,63 @@ +/* SPDX-License-Identifier: LGPL-2.1-or-later */ +/* + * Copyright (C) 2024 Ideas on Board Oy + * + * Generic AWB algorithms + */ + +#pragma once + +#include <map> + +#include <libcamera/control_ids.h> +#include <libcamera/controls.h> + +#include "libcamera/internal/vector.h" +#include "libcamera/internal/yaml_parser.h" + +namespace libcamera { + +namespace ipa { + +struct AwbResult { + RGB<double> gains; + double colourTemperature; +}; + +struct AwbStats { + virtual double computeColourError(const RGB<double> &gains) const = 0; + virtual RGB<double> getRGBMeans() const = 0; +}; + +class AwbAlgorithm +{ +public: + virtual ~AwbAlgorithm() = default; + + virtual int init(const YamlObject &tuningData) = 0; + virtual AwbResult calculateAwb(const AwbStats &stats, int lux) = 0; + virtual RGB<double> gainsFromColourTemperature(double colourTemperature) = 0; + + const ControlInfoMap::Map &controls() const + { + return controls_; + } + + virtual void handleControls([[maybe_unused]] const ControlList &controls) {} + +protected: + int parseModeConfigs(const YamlObject &tuningData, + const ControlValue &def = {}); + + struct ModeConfig { + double ctHi; + double ctLo; + }; + + ControlInfoMap::Map controls_; + std::map<controls::AwbModeEnum, AwbAlgorithm::ModeConfig> modes_; +}; + +} /* namespace ipa */ + +} /* namespace libcamera */ diff --git a/src/ipa/libipa/awb_bayes.cpp b/src/ipa/libipa/awb_bayes.cpp new file mode 100644 index 00000000..e75bfcd6 --- /dev/null +++ b/src/ipa/libipa/awb_bayes.cpp @@ -0,0 +1,499 @@ +/* SPDX-License-Identifier: LGPL-2.1-or-later */ +/* + * Copyright (C) 2019, Raspberry Pi Ltd + * Copyright (C) 2024 Ideas on Board Oy + * + * Implementation of a bayesian AWB algorithm + */ + +#include "awb_bayes.h" + +#include <cmath> + +#include <libcamera/base/log.h> +#include <libcamera/control_ids.h> + +#include "colours.h" + +/** + * \file awb_bayes.h + * \brief Implementation of bayesian auto white balance algorithm + * + * This implementation is based on the initial implementation done by + * RaspberryPi. + * \todo: Documentation + * + * \todo Not all the features implemented by RaspberryPi were ported over to + * this algorithm because they either rely on hardware features not generally + * available or were considered not important enough at the moment. + * + * The following parts are not implemented: + * + * - min_pixels: minimum proportion of pixels counted within AWB region for it + * to be "useful" + * - min_g: minimum G value of those pixels, to be regarded a "useful" + * - min_regions: number of AWB regions that must be "useful" in order to do the + * AWB calculation + * - deltaLimit: clamp on colour error term (so as not to penalize non-grey + * excessively) + * - bias_proportion: The biasProportion parameter adds a small proportion of + * the counted pixels to a region biased to the biasCT colour temperature. + * A typical value for biasProportion would be between 0.05 to 0.1. + * - bias_ct: CT target for the search bias + * - sensitivityR: red sensitivity ratio (set to canonical sensor's R/G divided + * by this sensor's R/G) + * - sensitivityB: blue sensitivity ratio (set to canonical sensor's B/G divided + * by this sensor's B/G) + */ + +namespace libcamera { + +LOG_DECLARE_CATEGORY(Awb) + +namespace { + +template<typename T> +class LimitsRecorder +{ +public: + LimitsRecorder() + : min_(std::numeric_limits<T>::max()), + max_(std::numeric_limits<T>::min()) + { + } + + void record(const T &value) + { + min_ = std::min(min_, value); + max_ = std::max(max_, value); + } + + const T &min() const { return min_; } + const T &max() const { return max_; } + +private: + T min_; + T max_; +}; + +#ifndef __DOXYGEN__ +template<typename T> +std::ostream &operator<<(std::ostream &out, const LimitsRecorder<T> &v) +{ + out << "[ " << v.min() << ", " << v.max() << " ]"; + return out; +} +#endif + +} /* namespace */ + +namespace ipa { + +/** + * \brief Step size control for CT search + */ +constexpr double kSearchStep = 0.2; + +/** + * \copydoc libcamera::ipa::Interpolator::interpolate() + */ +template<> +void Interpolator<Pwl>::interpolate(const Pwl &a, const Pwl &b, Pwl &dest, double lambda) +{ + dest = Pwl::combine(a, b, + [=](double /*x*/, double y0, double y1) -> double { + return y0 * (1.0 - lambda) + y1 * lambda; + }); +} + +/** + * \class AwbBayes + * \brief Implementation of a bayesian auto white balance algorithm + * + * In a bayesian AWB algorithm the auto white balance estimation is improved by + * taking the likelihood of a given lightsource based on the estimated lux level + * into account. E.g. If it is very bright we can assume that we are outside and + * that colour temperatures around 6500 are preferred. + * + * The second part of this algorithm is the search for the most likely colour + * temperature. It is implemented in AwbBayes::coarseSearch() and in + * AwbBayes::fineSearch(). The search works very well without prior likelihoods + * and therefore the algorithm itself provides very good results even without + * prior likelihoods. + */ + +/** + * \var AwbBayes::transversePos_ + * \brief How far to wander off CT curve towards "more purple" + */ + +/** + * \var AwbBayes::transverseNeg_ + * \brief How far to wander off CT curve towards "more green" + */ + +/** + * \var AwbBayes::currentMode_ + * \brief The currently selected mode + */ + +int AwbBayes::init(const YamlObject &tuningData) +{ + int ret = colourGainCurve_.readYaml(tuningData["colourGains"], "ct", "gains"); + if (ret) { + LOG(Awb, Error) + << "Failed to parse 'colourGains' " + << "parameter from tuning file"; + return ret; + } + + ctR_.clear(); + ctB_.clear(); + for (const auto &[ct, g] : colourGainCurve_.data()) { + ctR_.append(ct, 1.0 / g[0]); + ctB_.append(ct, 1.0 / g[1]); + } + + /* We will want the inverse functions of these too. */ + ctRInverse_ = ctR_.inverse().first; + ctBInverse_ = ctB_.inverse().first; + + ret = readPriors(tuningData); + if (ret) { + LOG(Awb, Error) << "Failed to read priors"; + return ret; + } + + ret = parseModeConfigs(tuningData, controls::AwbAuto); + if (ret) { + LOG(Awb, Error) + << "Failed to parse mode parameter from tuning file"; + return ret; + } + currentMode_ = &modes_[controls::AwbAuto]; + + transversePos_ = tuningData["transversePos"].get<double>(0.01); + transverseNeg_ = tuningData["transverseNeg"].get<double>(0.01); + if (transversePos_ <= 0 || transverseNeg_ <= 0) { + LOG(Awb, Error) << "AwbConfig: transversePos/Neg must be > 0"; + return -EINVAL; + } + + return 0; +} + +int AwbBayes::readPriors(const YamlObject &tuningData) +{ + const auto &priorsList = tuningData["priors"]; + std::map<uint32_t, Pwl> priors; + + if (!priorsList) { + LOG(Awb, Error) << "No priors specified"; + return -EINVAL; + } + + for (const auto &p : priorsList.asList()) { + if (!p.contains("lux")) { + LOG(Awb, Error) << "Missing lux value"; + return -EINVAL; + } + + uint32_t lux = p["lux"].get<uint32_t>(0); + if (priors.count(lux)) { + LOG(Awb, Error) << "Duplicate prior for lux value " << lux; + return -EINVAL; + } + + std::vector<uint32_t> temperatures = + p["ct"].getList<uint32_t>().value_or(std::vector<uint32_t>{}); + std::vector<double> probabilities = + p["probability"].getList<double>().value_or(std::vector<double>{}); + + if (temperatures.size() != probabilities.size()) { + LOG(Awb, Error) + << "Ct and probability array sizes are unequal"; + return -EINVAL; + } + + if (temperatures.empty()) { + LOG(Awb, Error) + << "Ct and probability arrays are empty"; + return -EINVAL; + } + + std::map<int, double> ctToProbability; + for (unsigned int i = 0; i < temperatures.size(); i++) { + int t = temperatures[i]; + if (ctToProbability.count(t)) { + LOG(Awb, Error) << "Duplicate ct value"; + return -EINVAL; + } + + ctToProbability[t] = probabilities[i]; + } + + auto &pwl = priors[lux]; + for (const auto &[ct, prob] : ctToProbability) { + if (prob < 1e-6) { + LOG(Awb, Error) << "Prior probability must be larger than 1e-6"; + return -EINVAL; + } + pwl.append(ct, prob); + } + } + + if (priors.empty()) { + LOG(Awb, Error) << "No priors specified"; + return -EINVAL; + } + + priors_.setData(std::move(priors)); + + return 0; +} + +void AwbBayes::handleControls(const ControlList &controls) +{ + auto mode = controls.get(controls::AwbMode); + if (mode) { + auto it = modes_.find(static_cast<controls::AwbModeEnum>(*mode)); + if (it != modes_.end()) + currentMode_ = &it->second; + else + LOG(Awb, Error) << "Unsupported AWB mode " << *mode; + } +} + +RGB<double> AwbBayes::gainsFromColourTemperature(double colourTemperature) +{ + /* + * \todo: In the RaspberryPi code, the ct curve was interpolated in + * the white point space (1/x) not in gains space. This feels counter + * intuitive, as the gains are in linear space. But I can't prove it. + */ + const auto &gains = colourGainCurve_.getInterpolated(colourTemperature); + return { { gains[0], 1.0, gains[1] } }; +} + +AwbResult AwbBayes::calculateAwb(const AwbStats &stats, int lux) +{ + ipa::Pwl prior; + if (lux > 0) { + prior = priors_.getInterpolated(lux); + prior.map([](double x, double y) { + LOG(Awb, Debug) << "(" << x << "," << y << ")"; + }); + } else { + prior.append(0, 1.0); + } + + double t = coarseSearch(prior, stats); + double r = ctR_.eval(t); + double b = ctB_.eval(t); + LOG(Awb, Debug) + << "After coarse search: r " << r << " b " << b << " (gains r " + << 1 / r << " b " << 1 / b << ")"; + + /* + * Original comment from RaspberryPi: + * Not entirely sure how to handle the fine search yet. Mostly the + * estimated CT is already good enough, but the fine search allows us to + * wander transversely off the CT curve. Under some illuminants, where + * there may be more or less green light, this may prove beneficial, + * though I probably need more real datasets before deciding exactly how + * this should be controlled and tuned. + */ + fineSearch(t, r, b, prior, stats); + LOG(Awb, Debug) + << "After fine search: r " << r << " b " << b << " (gains r " + << 1 / r << " b " << 1 / b << ")"; + + return { { { 1.0 / r, 1.0, 1.0 / b } }, t }; +} + +double AwbBayes::coarseSearch(const ipa::Pwl &prior, const AwbStats &stats) const +{ + std::vector<Pwl::Point> points; + size_t bestPoint = 0; + double t = currentMode_->ctLo; + int spanR = -1; + int spanB = -1; + LimitsRecorder<double> errorLimits; + LimitsRecorder<double> priorLogLikelihoodLimits; + + /* Step down the CT curve evaluating log likelihood. */ + while (true) { + double r = ctR_.eval(t, &spanR); + double b = ctB_.eval(t, &spanB); + RGB<double> gains({ 1 / r, 1.0, 1 / b }); + double delta2Sum = stats.computeColourError(gains); + double priorLogLikelihood = log(prior.eval(prior.domain().clamp(t))); + double finalLogLikelihood = delta2Sum - priorLogLikelihood; + + errorLimits.record(delta2Sum); + priorLogLikelihoodLimits.record(priorLogLikelihood); + + points.push_back({ { t, finalLogLikelihood } }); + if (points.back().y() < points[bestPoint].y()) + bestPoint = points.size() - 1; + + if (t == currentMode_->ctHi) + break; + + /* + * Ensure even steps along the r/b curve by scaling them by the + * current t. + */ + t = std::min(t + t / 10 * kSearchStep, currentMode_->ctHi); + } + + t = points[bestPoint].x(); + LOG(Awb, Debug) << "Coarse search found CT " << t + << " error limits:" << errorLimits + << " prior log likelihood limits:" << priorLogLikelihoodLimits; + + /* + * We have the best point of the search, but refine it with a quadratic + * interpolation around its neighbors. + */ + if (points.size() > 2) { + bestPoint = std::clamp(bestPoint, std::size_t{ 1 }, points.size() - 2); + t = interpolateQuadratic(points[bestPoint - 1], + points[bestPoint], + points[bestPoint + 1]); + LOG(Awb, Debug) + << "After quadratic refinement, coarse search has CT " + << t; + } + + return t; +} + +void AwbBayes::fineSearch(double &t, double &r, double &b, ipa::Pwl const &prior, const AwbStats &stats) const +{ + int spanR = -1; + int spanB = -1; + double step = t / 10 * kSearchStep * 0.1; + int nsteps = 5; + ctR_.eval(t, &spanR); + ctB_.eval(t, &spanB); + double rDiff = ctR_.eval(t + nsteps * step, &spanR) - + ctR_.eval(t - nsteps * step, &spanR); + double bDiff = ctB_.eval(t + nsteps * step, &spanB) - + ctB_.eval(t - nsteps * step, &spanB); + Pwl::Point transverse({ bDiff, -rDiff }); + if (transverse.length2() < 1e-6) + return; + /* + * transverse is a unit vector orthogonal to the b vs. r function + * (pointing outwards with r and b increasing) + */ + transverse = transverse / transverse.length(); + double bestLogLikelihood = 0; + double bestT = 0; + Pwl::Point bestRB(0); + double transverseRange = transverseNeg_ + transversePos_; + const int maxNumDeltas = 12; + LimitsRecorder<double> errorLimits; + LimitsRecorder<double> priorLogLikelihoodLimits; + + + /* a transverse step approximately every 0.01 r/b units */ + int numDeltas = floor(transverseRange * 100 + 0.5) + 1; + numDeltas = std::clamp(numDeltas, 3, maxNumDeltas); + + /* + * Step down CT curve. March a bit further if the transverse range is + * large. + */ + nsteps += numDeltas; + for (int i = -nsteps; i <= nsteps; i++) { + double tTest = t + i * step; + double priorLogLikelihood = + log(prior.eval(prior.domain().clamp(tTest))); + priorLogLikelihoodLimits.record(priorLogLikelihood); + Pwl::Point rbStart{ { ctR_.eval(tTest, &spanR), + ctB_.eval(tTest, &spanB) } }; + Pwl::Point samples[maxNumDeltas]; + int bestPoint = 0; + + /* + * Sample numDeltas points transversely *off* the CT curve + * in the range [-transverseNeg, transversePos]. + * The x values of a sample contains the distance and the y + * value contains the corresponding log likelihood. + */ + double transverseStep = transverseRange / (numDeltas - 1); + for (int j = 0; j < numDeltas; j++) { + auto &p = samples[j]; + p.x() = -transverseNeg_ + transverseStep * j; + Pwl::Point rbTest = rbStart + transverse * p.x(); + RGB<double> gains({ 1 / rbTest[0], 1.0, 1 / rbTest[1] }); + double delta2Sum = stats.computeColourError(gains); + errorLimits.record(delta2Sum); + p.y() = delta2Sum - priorLogLikelihood; + + if (p.y() < samples[bestPoint].y()) + bestPoint = j; + } + + /* + * We have all samples transversely across the CT curve, + * now let's do a quadratic interpolation for the best result. + */ + bestPoint = std::clamp(bestPoint, 1, numDeltas - 2); + double bestOffset = interpolateQuadratic(samples[bestPoint - 1], + samples[bestPoint], + samples[bestPoint + 1]); + Pwl::Point rbTest = rbStart + transverse * bestOffset; + RGB<double> gains({ 1 / rbTest[0], 1.0, 1 / rbTest[1] }); + double delta2Sum = stats.computeColourError(gains); + errorLimits.record(delta2Sum); + double finalLogLikelihood = delta2Sum - priorLogLikelihood; + + if (bestT == 0 || finalLogLikelihood < bestLogLikelihood) { + bestLogLikelihood = finalLogLikelihood; + bestT = tTest; + bestRB = rbTest; + } + } + + t = bestT; + r = bestRB[0]; + b = bestRB[1]; + LOG(Awb, Debug) + << "Fine search found t " << t << " r " << r << " b " << b + << " error limits: " << errorLimits + << " prior log likelihood limits: " << priorLogLikelihoodLimits; +} + +/** + * \brief Find extremum of function + * \param[in] a First point + * \param[in] b Second point + * \param[in] c Third point + * + * Given 3 points on a curve, find the extremum of the function in that interval + * by fitting a quadratic. + * + * \return The x value of the extremum clamped to the interval [a.x(), c.x()] + */ +double AwbBayes::interpolateQuadratic(Pwl::Point const &a, Pwl::Point const &b, + Pwl::Point const &c) const +{ + const double eps = 1e-3; + Pwl::Point ca = c - a; + Pwl::Point ba = b - a; + double denominator = 2 * (ba.y() * ca.x() - ca.y() * ba.x()); + if (std::abs(denominator) > eps) { + double numerator = ba.y() * ca.x() * ca.x() - ca.y() * ba.x() * ba.x(); + double result = numerator / denominator + a.x(); + return std::max(a.x(), std::min(c.x(), result)); + } + /* has degenerated to straight line segment */ + return a.y() < c.y() - eps ? a.x() : (c.y() < a.y() - eps ? c.x() : b.x()); +} + +} /* namespace ipa */ + +} /* namespace libcamera */ diff --git a/src/ipa/libipa/awb_bayes.h b/src/ipa/libipa/awb_bayes.h new file mode 100644 index 00000000..47db7243 --- /dev/null +++ b/src/ipa/libipa/awb_bayes.h @@ -0,0 +1,67 @@ +/* SPDX-License-Identifier: LGPL-2.1-or-later */ +/* + * Copyright (C) 2024 Ideas on Board Oy + * + * Base class for bayes AWB algorithms + */ + +#pragma once + +#include <map> +#include <memory> +#include <tuple> +#include <vector> + +#include <libcamera/base/utils.h> + +#include <libcamera/control_ids.h> +#include <libcamera/controls.h> + +#include "libcamera/internal/vector.h" +#include "libcamera/internal/yaml_parser.h" + +#include "awb.h" +#include "interpolator.h" +#include "pwl.h" + +namespace libcamera { + +namespace ipa { + +class AwbBayes : public AwbAlgorithm +{ +public: + AwbBayes() = default; + + int init(const YamlObject &tuningData) override; + AwbResult calculateAwb(const AwbStats &stats, int lux) override; + RGB<double> gainsFromColourTemperature(double temperatureK) override; + void handleControls(const ControlList &controls) override; + +private: + int readPriors(const YamlObject &tuningData); + + void fineSearch(double &t, double &r, double &b, ipa::Pwl const &prior, + const AwbStats &stats) const; + double coarseSearch(const ipa::Pwl &prior, const AwbStats &stats) const; + double interpolateQuadratic(ipa::Pwl::Point const &a, + ipa::Pwl::Point const &b, + ipa::Pwl::Point const &c) const; + + Interpolator<Pwl> priors_; + Interpolator<Vector<double, 2>> colourGainCurve_; + + ipa::Pwl ctR_; + ipa::Pwl ctB_; + ipa::Pwl ctRInverse_; + ipa::Pwl ctBInverse_; + + double transversePos_; + double transverseNeg_; + + ModeConfig *currentMode_ = nullptr; +}; + +} /* namespace ipa */ + +} /* namespace libcamera */ diff --git a/src/ipa/libipa/awb_grey.cpp b/src/ipa/libipa/awb_grey.cpp new file mode 100644 index 00000000..49448976 --- /dev/null +++ b/src/ipa/libipa/awb_grey.cpp @@ -0,0 +1,114 @@ +/* SPDX-License-Identifier: LGPL-2.1-or-later */ +/* + * Copyright (C) 2024 Ideas on Board Oy + * + * Base class for grey world AWB algorithm + */ + +#include "awb_grey.h" + +#include <cmath> + +#include <libcamera/base/log.h> +#include <libcamera/control_ids.h> + +#include "colours.h" + +using namespace libcamera::controls; + +/** + * \file awb_grey.h + * \brief Implementation of a grey world AWB algorithm + */ + +namespace libcamera { + +LOG_DECLARE_CATEGORY(Awb) +namespace ipa { + +/** + * \class AwbGrey + * \brief A Grey world auto white balance algorithm + */ + +/** + * \brief Initialize the algorithm with the given tuning data + * \param[in] tuningData The tuning data for the algorithm + * + * Load the colour temperature curve from the tuning data. If there is no tuning + * data available, continue with a warning. Manual colour temperature will not + * work in that case. + * + * \return 0 on success, a negative error code otherwise + */ +int AwbGrey::init(const YamlObject &tuningData) +{ + Interpolator<Vector<double, 2>> gains; + int ret = gains.readYaml(tuningData["colourGains"], "ct", "gains"); + if (ret < 0) + LOG(Awb, Warning) + << "Failed to parse 'colourGains' " + << "parameter from tuning file; " + << "manual colour temperature will not work properly"; + else + colourGainCurve_ = gains; + + return 0; +} + +/** + * \brief Calculate awb data from the given statistics + * \param[in] stats The statistics to use for the calculation + * \param[in] lux The lux value of the scene + * + * Estimates the colour temperature based on the colours::estimateCCT function. + * The gains are calculated purely based on the RGB means provided by the \a + * stats. The colour temperature is not taken into account when calculating the + * gains. + * + * The \a lux parameter is not used in this algorithm. + * + * \return The awb result + */ +AwbResult AwbGrey::calculateAwb(const AwbStats &stats, [[maybe_unused]] int lux) +{ + AwbResult result; + auto means = stats.getRGBMeans(); + result.colourTemperature = estimateCCT(means); + + /* + * Estimate the red and blue gains to apply in a grey world. The green + * gain is hardcoded to 1.0. Avoid divisions by zero by clamping the + * divisor to a minimum value of 1.0. + */ + result.gains.r() = means.g() / std::max(means.r(), 1.0); + result.gains.g() = 1.0; + result.gains.b() = means.g() / std::max(means.b(), 1.0); + return result; +} + +/** + * \brief Compute white balance gains from a colour temperature + * \param[in] colourTemperature The colour temperature in Kelvin + * + * Compute the white balance gains from a \a colourTemperature. This function + * does not take any statistics into account. It simply interpolates the colour + * gains configured in the colour temperature curve. + * + * \return The colour gains if a colour temperature curve is available, + * [1, 1, 1] otherwise. + */ +RGB<double> AwbGrey::gainsFromColourTemperature(double colourTemperature) +{ + if (!colourGainCurve_) { + LOG(Awb, Error) << "No gains defined"; + return RGB<double>({ 1.0, 1.0, 1.0 }); + } + + auto gains = colourGainCurve_->getInterpolated(colourTemperature); + return { { gains[0], 1.0, gains[1] } }; +} + +} /* namespace ipa */ + +} /* namespace libcamera */ diff --git a/src/ipa/libipa/awb_grey.h b/src/ipa/libipa/awb_grey.h new file mode 100644 index 00000000..1a365e61 --- /dev/null +++ b/src/ipa/libipa/awb_grey.h @@ -0,0 +1,35 @@ +/* SPDX-License-Identifier: LGPL-2.1-or-later */ +/* + * Copyright (C) 2024 Ideas on Board Oy + * + * AWB grey world algorithm + */ + +#pragma once + +#include "libcamera/internal/vector.h" +#include "libcamera/internal/yaml_parser.h" + +#include "awb.h" +#include "interpolator.h" + +namespace libcamera { + +namespace ipa { + +class AwbGrey : public AwbAlgorithm +{ +public: + AwbGrey() = default; + + int init(const YamlObject &tuningData) override; + AwbResult calculateAwb(const AwbStats &stats, int lux) override; + RGB<double> gainsFromColourTemperature(double colourTemperature) override; + +private: + std::optional<Interpolator<Vector<double, 2>>> colourGainCurve_; +}; + +} /* namespace ipa */ + +} /* namespace libcamera */ diff --git a/src/ipa/libipa/camera_sensor_helper.cpp b/src/ipa/libipa/camera_sensor_helper.cpp index 782ff990..7c66cd57 100644 --- a/src/ipa/libipa/camera_sensor_helper.cpp +++ b/src/ipa/libipa/camera_sensor_helper.cpp @@ -8,6 +8,7 @@ #include "camera_sensor_helper.h" #include <cmath> +#include <limits> #include <libcamera/base/log.h> @@ -40,6 +41,7 @@ namespace ipa { */ /** + * \fn CameraSensorHelper::CameraSensorHelper() * \brief Construct a CameraSensorHelper instance * * CameraSensorHelper derived class instances shall never be constructed @@ -48,6 +50,33 @@ namespace ipa { */ /** + * \fn CameraSensorHelper::blackLevel() + * \brief Fetch the black level of the sensor + * + * This function returns the black level of the sensor scaled to a 16bit pixel + * width. If it is unknown an empty optional is returned. + * + * \todo Fill the blanks and add pedestal values for all supported sensors. Once + * done, drop the std::optional<>. + * + * Black levels are typically the result of the following phenomena: + * - Pedestal added by the sensor to pixel values. They are typically fixed, + * sometimes programmable and should be reported in datasheets (but + * documentation is not always available). + * - Dark currents and other physical effects that add charge to pixels in the + * absence of light. Those can depend on the integration time and the sensor + * die temperature, and their contribution to pixel values depend on the + * sensor gains. + * + * The pedestal is usually the value with the biggest contribution to the + * overall black level. In most cases it is either known before or in rare cases + * (there is not a single driver with such a control in the linux kernel) can be + * queried from the sensor. This function provides that fixed, known value. + * + * \return The black level of the sensor, or std::nullopt if not known + */ + +/** * \brief Compute gain code from the analogue gain absolute value * \param[in] gain The real gain to pass * @@ -58,21 +87,16 @@ namespace ipa { */ uint32_t CameraSensorHelper::gainCode(double gain) const { - const AnalogueGainConstants &k = gainConstants_; - - switch (gainType_) { - case AnalogueGainLinear: - ASSERT(k.linear.m0 == 0 || k.linear.m1 == 0); + if (auto *l = std::get_if<AnalogueGainLinear>(&gain_)) { + ASSERT(l->m0 == 0 || l->m1 == 0); - return (k.linear.c0 - k.linear.c1 * gain) / - (k.linear.m1 * gain - k.linear.m0); + return (l->c0 - l->c1 * gain) / + (l->m1 * gain - l->m0); + } else if (auto *e = std::get_if<AnalogueGainExp>(&gain_)) { + ASSERT(e->a != 0 && e->m != 0); - case AnalogueGainExponential: - ASSERT(k.exp.a != 0 && k.exp.m != 0); - - return std::log2(gain / k.exp.a) / k.exp.m; - - default: + return std::log2(gain / e->a) / e->m; + } else { ASSERT(false); return 0; } @@ -90,38 +114,26 @@ uint32_t CameraSensorHelper::gainCode(double gain) const */ double CameraSensorHelper::gain(uint32_t gainCode) const { - const AnalogueGainConstants &k = gainConstants_; double gain = static_cast<double>(gainCode); - switch (gainType_) { - case AnalogueGainLinear: - ASSERT(k.linear.m0 == 0 || k.linear.m1 == 0); - - return (k.linear.m0 * gain + k.linear.c0) / - (k.linear.m1 * gain + k.linear.c1); + if (auto *l = std::get_if<AnalogueGainLinear>(&gain_)) { + ASSERT(l->m0 == 0 || l->m1 == 0); - case AnalogueGainExponential: - ASSERT(k.exp.a != 0 && k.exp.m != 0); + return (l->m0 * gain + l->c0) / + (l->m1 * gain + l->c1); + } else if (auto *e = std::get_if<AnalogueGainExp>(&gain_)) { + ASSERT(e->a != 0 && e->m != 0); - return k.exp.a * std::exp2(k.exp.m * gain); - - default: + return e->a * std::exp2(e->m * gain); + } else { ASSERT(false); return 0.0; } } /** - * \enum CameraSensorHelper::AnalogueGainType - * \brief The gain calculation modes as defined by the MIPI CCS - * - * Describes the image sensor analogue gain capabilities. - * Two modes are possible, depending on the sensor: Linear and Exponential. - */ - -/** - * \var CameraSensorHelper::AnalogueGainLinear - * \brief Gain is computed using linear gain estimation + * \struct CameraSensorHelper::AnalogueGainLinear + * \brief Analogue gain constants for the linear gain model * * The relationship between the integer gain parameter and the resulting gain * multiplier is given by the following equation: @@ -136,11 +148,27 @@ double CameraSensorHelper::gain(uint32_t gainCode) const * The full Gain equation therefore reduces to either: * * \f$gain=\frac{c0}{m1x+c1}\f$ or \f$\frac{m0x+c0}{c1}\f$ + * + * \var CameraSensorHelper::AnalogueGainLinear::m0 + * \brief Constant used in the linear gain coding/decoding + * + * \note Either m0 or m1 shall be zero. + * + * \var CameraSensorHelper::AnalogueGainLinear::c0 + * \brief Constant used in the linear gain coding/decoding + * + * \var CameraSensorHelper::AnalogueGainLinear::m1 + * \brief Constant used in the linear gain coding/decoding + * + * \note Either m0 or m1 shall be zero. + * + * \var CameraSensorHelper::AnalogueGainLinear::c1 + * \brief Constant used in the linear gain coding/decoding */ /** - * \var CameraSensorHelper::AnalogueGainExponential - * \brief Gain is expressed using an exponential model + * \struct CameraSensorHelper::AnalogueGainExp + * \brief Analogue gain constants for the exponential gain model * * The relationship between the integer gain parameter and the resulting gain * multiplier is given by the following equation: @@ -156,61 +184,22 @@ double CameraSensorHelper::gain(uint32_t gainCode) const * * When the gain is expressed in dB, 'a' is equal to 1 and 'm' to * \f$log_{2}{10^{\frac{1}{20}}}\f$. - */ - -/** - * \struct CameraSensorHelper::AnalogueGainLinearConstants - * \brief Analogue gain constants for the linear gain model - * - * \var CameraSensorHelper::AnalogueGainLinearConstants::m0 - * \brief Constant used in the linear gain coding/decoding - * - * \note Either m0 or m1 shall be zero. - * - * \var CameraSensorHelper::AnalogueGainLinearConstants::c0 - * \brief Constant used in the linear gain coding/decoding - * - * \var CameraSensorHelper::AnalogueGainLinearConstants::m1 - * \brief Constant used in the linear gain coding/decoding - * - * \note Either m0 or m1 shall be zero. * - * \var CameraSensorHelper::AnalogueGainLinearConstants::c1 - * \brief Constant used in the linear gain coding/decoding - */ - -/** - * \struct CameraSensorHelper::AnalogueGainExpConstants - * \brief Analogue gain constants for the exponential gain model - * - * \var CameraSensorHelper::AnalogueGainExpConstants::a + * \var CameraSensorHelper::AnalogueGainExp::a * \brief Constant used in the exponential gain coding/decoding * - * \var CameraSensorHelper::AnalogueGainExpConstants::m + * \var CameraSensorHelper::AnalogueGainExp::m * \brief Constant used in the exponential gain coding/decoding */ /** - * \struct CameraSensorHelper::AnalogueGainConstants - * \brief Analogue gain model constants - * - * This union stores the constants used to calculate the analogue gain. The - * CameraSensorHelper::gainType_ variable selects which union member is valid. - * - * \var CameraSensorHelper::AnalogueGainConstants::linear - * \brief Constants for the linear gain model - * - * \var CameraSensorHelper::AnalogueGainConstants::exp - * \brief Constants for the exponential gain model - */ - -/** - * \var CameraSensorHelper::gainType_ - * \brief The analogue gain model type + * \var CameraSensorHelper::blackLevel_ + * \brief The black level of the sensor + * \sa CameraSensorHelper::blackLevel() */ /** - * \var CameraSensorHelper::gainConstants_ + * \var CameraSensorHelper::gain_ * \brief The analogue gain parameters used for calculation * * The analogue gain is calculated through a formula, and its parameters are @@ -366,6 +355,99 @@ static constexpr double expGainDb(double step) return log2_10 * step / 20; } +class CameraSensorHelperAr0144 : public CameraSensorHelper +{ +public: + CameraSensorHelperAr0144() + { + /* Power-on default value: 168 at 12bits. */ + blackLevel_ = 2688; + } + + uint32_t gainCode(double gain) const override + { + /* The recommended minimum gain is 1.6842 to avoid artifacts. */ + gain = std::clamp(gain, 1.0 / (1.0 - 13.0 / 32.0), 18.45); + + /* + * The analogue gain is made of a coarse exponential gain in + * the range [2^0, 2^4] and a fine inversely linear gain in the + * range [1.0, 2.0[. There is an additional fixed 1.153125 + * multiplier when the coarse gain reaches 2^2. + */ + + if (gain > 4.0) + gain /= 1.153125; + + unsigned int coarse = std::log2(gain); + unsigned int fine = (1 - (1 << coarse) / gain) * 32; + + /* The fine gain rounding depends on the coarse gain. */ + if (coarse == 1 || coarse == 3) + fine &= ~1; + else if (coarse == 4) + fine &= ~3; + + return (coarse << 4) | (fine & 0xf); + } + + double gain(uint32_t gainCode) const override + { + unsigned int coarse = gainCode >> 4; + unsigned int fine = gainCode & 0xf; + unsigned int d1; + double d2, m; + + switch (coarse) { + default: + case 0: + d1 = 1; + d2 = 32.0; + m = 1.0; + break; + case 1: + d1 = 2; + d2 = 16.0; + m = 1.0; + break; + case 2: + d1 = 1; + d2 = 32.0; + m = 1.153125; + break; + case 3: + d1 = 2; + d2 = 16.0; + m = 1.153125; + break; + case 4: + d1 = 4; + d2 = 8.0; + m = 1.153125; + break; + } + + /* + * With infinite precision, the calculated gain would be exact, + * and the reverse conversion with gainCode() would produce the + * same gain code. In the real world, rounding errors may cause + * the calculated gain to be lower by an amount negligible for + * all purposes, except for the reverse conversion. Converting + * the gain to a gain code could then return the quantized value + * just lower than the original gain code. To avoid this, tests + * showed that adding the machine epsilon to the multiplier m is + * sufficient. + */ + m += std::numeric_limits<decltype(m)>::epsilon(); + + return m * (1 << coarse) / (1.0 - (fine / d1) / d2); + } + +private: + static constexpr double kStep_ = 16; +}; +REGISTER_CAMERA_SENSOR_HELPER("ar0144", CameraSensorHelperAr0144) + class CameraSensorHelperAr0521 : public CameraSensorHelper { public: @@ -391,13 +473,50 @@ private: }; REGISTER_CAMERA_SENSOR_HELPER("ar0521", CameraSensorHelperAr0521) +class CameraSensorHelperGc05a2 : public CameraSensorHelper +{ +public: + CameraSensorHelperGc05a2() + { + /* From datasheet: 64 at 10bits. */ + blackLevel_ = 4096; + gain_ = AnalogueGainLinear{ 100, 0, 0, 1024 }; + } +}; +REGISTER_CAMERA_SENSOR_HELPER("gc05a2", CameraSensorHelperGc05a2) + +class CameraSensorHelperGc08a3 : public CameraSensorHelper +{ +public: + CameraSensorHelperGc08a3() + { + /* From datasheet: 64 at 10bits. */ + blackLevel_ = 4096; + gain_ = AnalogueGainLinear{ 100, 0, 0, 1024 }; + } +}; +REGISTER_CAMERA_SENSOR_HELPER("gc08a3", CameraSensorHelperGc08a3) + +class CameraSensorHelperImx214 : public CameraSensorHelper +{ +public: + CameraSensorHelperImx214() + { + /* From datasheet: 64 at 10bits. */ + blackLevel_ = 4096; + gain_ = AnalogueGainLinear{ 0, 512, -1, 512 }; + } +}; +REGISTER_CAMERA_SENSOR_HELPER("imx214", CameraSensorHelperImx214) + class CameraSensorHelperImx219 : public CameraSensorHelper { public: CameraSensorHelperImx219() { - gainType_ = AnalogueGainLinear; - gainConstants_.linear = { 0, 256, -1, 256 }; + /* From datasheet: 64 at 10bits. */ + blackLevel_ = 4096; + gain_ = AnalogueGainLinear{ 0, 256, -1, 256 }; } }; REGISTER_CAMERA_SENSOR_HELPER("imx219", CameraSensorHelperImx219) @@ -407,8 +526,9 @@ class CameraSensorHelperImx258 : public CameraSensorHelper public: CameraSensorHelperImx258() { - gainType_ = AnalogueGainLinear; - gainConstants_.linear = { 0, 512, -1, 512 }; + /* From datasheet: 0x40 at 10bits. */ + blackLevel_ = 4096; + gain_ = AnalogueGainLinear{ 0, 512, -1, 512 }; } }; REGISTER_CAMERA_SENSOR_HELPER("imx258", CameraSensorHelperImx258) @@ -418,8 +538,9 @@ class CameraSensorHelperImx283 : public CameraSensorHelper public: CameraSensorHelperImx283() { - gainType_ = AnalogueGainLinear; - gainConstants_.linear = { 0, 2048, -1, 2048 }; + /* From datasheet: 0x32 at 10bits. */ + blackLevel_ = 3200; + gain_ = AnalogueGainLinear{ 0, 2048, -1, 2048 }; } }; REGISTER_CAMERA_SENSOR_HELPER("imx283", CameraSensorHelperImx283) @@ -429,8 +550,9 @@ class CameraSensorHelperImx290 : public CameraSensorHelper public: CameraSensorHelperImx290() { - gainType_ = AnalogueGainExponential; - gainConstants_.exp = { 1.0, expGainDb(0.3) }; + /* From datasheet: 0xf0 at 12bits. */ + blackLevel_ = 3840; + gain_ = AnalogueGainExp{ 1.0, expGainDb(0.3) }; } }; REGISTER_CAMERA_SENSOR_HELPER("imx290", CameraSensorHelperImx290) @@ -440,8 +562,7 @@ class CameraSensorHelperImx296 : public CameraSensorHelper public: CameraSensorHelperImx296() { - gainType_ = AnalogueGainExponential; - gainConstants_.exp = { 1.0, expGainDb(0.1) }; + gain_ = AnalogueGainExp{ 1.0, expGainDb(0.1) }; } }; REGISTER_CAMERA_SENSOR_HELPER("imx296", CameraSensorHelperImx296) @@ -456,8 +577,9 @@ class CameraSensorHelperImx335 : public CameraSensorHelper public: CameraSensorHelperImx335() { - gainType_ = AnalogueGainExponential; - gainConstants_.exp = { 1.0, expGainDb(0.3) }; + /* From datasheet: 0x32 at 10bits. */ + blackLevel_ = 3200; + gain_ = AnalogueGainExp{ 1.0, expGainDb(0.3) }; } }; REGISTER_CAMERA_SENSOR_HELPER("imx335", CameraSensorHelperImx335) @@ -467,19 +589,22 @@ class CameraSensorHelperImx415 : public CameraSensorHelper public: CameraSensorHelperImx415() { - gainType_ = AnalogueGainExponential; - gainConstants_.exp = { 1.0, expGainDb(0.3) }; + gain_ = AnalogueGainExp{ 1.0, expGainDb(0.3) }; } }; REGISTER_CAMERA_SENSOR_HELPER("imx415", CameraSensorHelperImx415) +class CameraSensorHelperImx462 : public CameraSensorHelperImx290 +{ +}; +REGISTER_CAMERA_SENSOR_HELPER("imx462", CameraSensorHelperImx462) + class CameraSensorHelperImx477 : public CameraSensorHelper { public: CameraSensorHelperImx477() { - gainType_ = AnalogueGainLinear; - gainConstants_.linear = { 0, 1024, -1, 1024 }; + gain_ = AnalogueGainLinear{ 0, 1024, -1, 1024 }; } }; REGISTER_CAMERA_SENSOR_HELPER("imx477", CameraSensorHelperImx477) @@ -493,8 +618,7 @@ public: * The Sensor Manual doesn't appear to document the gain model. * This has been validated with some empirical testing only. */ - gainType_ = AnalogueGainLinear; - gainConstants_.linear = { 1, 0, 0, 128 }; + gain_ = AnalogueGainLinear{ 1, 0, 0, 128 }; } }; REGISTER_CAMERA_SENSOR_HELPER("ov2685", CameraSensorHelperOv2685) @@ -504,8 +628,7 @@ class CameraSensorHelperOv2740 : public CameraSensorHelper public: CameraSensorHelperOv2740() { - gainType_ = AnalogueGainLinear; - gainConstants_.linear = { 1, 0, 0, 128 }; + gain_ = AnalogueGainLinear{ 1, 0, 0, 128 }; } }; REGISTER_CAMERA_SENSOR_HELPER("ov2740", CameraSensorHelperOv2740) @@ -515,8 +638,9 @@ class CameraSensorHelperOv4689 : public CameraSensorHelper public: CameraSensorHelperOv4689() { - gainType_ = AnalogueGainLinear; - gainConstants_.linear = { 1, 0, 0, 128 }; + /* From datasheet: 0x40 at 12bits. */ + blackLevel_ = 1024; + gain_ = AnalogueGainLinear{ 1, 0, 0, 128 }; } }; REGISTER_CAMERA_SENSOR_HELPER("ov4689", CameraSensorHelperOv4689) @@ -526,8 +650,9 @@ class CameraSensorHelperOv5640 : public CameraSensorHelper public: CameraSensorHelperOv5640() { - gainType_ = AnalogueGainLinear; - gainConstants_.linear = { 1, 0, 0, 16 }; + /* From datasheet: 0x10 at 10bits. */ + blackLevel_ = 1024; + gain_ = AnalogueGainLinear{ 1, 0, 0, 16 }; } }; REGISTER_CAMERA_SENSOR_HELPER("ov5640", CameraSensorHelperOv5640) @@ -537,8 +662,7 @@ class CameraSensorHelperOv5647 : public CameraSensorHelper public: CameraSensorHelperOv5647() { - gainType_ = AnalogueGainLinear; - gainConstants_.linear = { 1, 0, 0, 16 }; + gain_ = AnalogueGainLinear{ 1, 0, 0, 16 }; } }; REGISTER_CAMERA_SENSOR_HELPER("ov5647", CameraSensorHelperOv5647) @@ -548,8 +672,7 @@ class CameraSensorHelperOv5670 : public CameraSensorHelper public: CameraSensorHelperOv5670() { - gainType_ = AnalogueGainLinear; - gainConstants_.linear = { 1, 0, 0, 128 }; + gain_ = AnalogueGainLinear{ 1, 0, 0, 128 }; } }; REGISTER_CAMERA_SENSOR_HELPER("ov5670", CameraSensorHelperOv5670) @@ -559,8 +682,9 @@ class CameraSensorHelperOv5675 : public CameraSensorHelper public: CameraSensorHelperOv5675() { - gainType_ = AnalogueGainLinear; - gainConstants_.linear = { 1, 0, 0, 128 }; + /* From Linux kernel driver: 0x40 at 10bits. */ + blackLevel_ = 4096; + gain_ = AnalogueGainLinear{ 1, 0, 0, 128 }; } }; REGISTER_CAMERA_SENSOR_HELPER("ov5675", CameraSensorHelperOv5675) @@ -570,8 +694,7 @@ class CameraSensorHelperOv5693 : public CameraSensorHelper public: CameraSensorHelperOv5693() { - gainType_ = AnalogueGainLinear; - gainConstants_.linear = { 1, 0, 0, 16 }; + gain_ = AnalogueGainLinear{ 1, 0, 0, 16 }; } }; REGISTER_CAMERA_SENSOR_HELPER("ov5693", CameraSensorHelperOv5693) @@ -581,8 +704,7 @@ class CameraSensorHelperOv64a40 : public CameraSensorHelper public: CameraSensorHelperOv64a40() { - gainType_ = AnalogueGainLinear; - gainConstants_.linear = { 1, 0, 0, 128 }; + gain_ = AnalogueGainLinear{ 1, 0, 0, 128 }; } }; REGISTER_CAMERA_SENSOR_HELPER("ov64a40", CameraSensorHelperOv64a40) @@ -592,15 +714,13 @@ class CameraSensorHelperOv8858 : public CameraSensorHelper public: CameraSensorHelperOv8858() { - gainType_ = AnalogueGainLinear; - /* * \todo Validate the selected 1/128 step value as it differs * from what the sensor manual describes. * * See: https://patchwork.linuxtv.org/project/linux-media/patch/20221106171129.166892-2-nicholas@rothemail.net/#142267 */ - gainConstants_.linear = { 1, 0, 0, 128 }; + gain_ = AnalogueGainLinear{ 1, 0, 0, 128 }; } }; REGISTER_CAMERA_SENSOR_HELPER("ov8858", CameraSensorHelperOv8858) @@ -610,8 +730,7 @@ class CameraSensorHelperOv8865 : public CameraSensorHelper public: CameraSensorHelperOv8865() { - gainType_ = AnalogueGainLinear; - gainConstants_.linear = { 1, 0, 0, 128 }; + gain_ = AnalogueGainLinear{ 1, 0, 0, 128 }; } }; REGISTER_CAMERA_SENSOR_HELPER("ov8865", CameraSensorHelperOv8865) @@ -621,8 +740,7 @@ class CameraSensorHelperOv13858 : public CameraSensorHelper public: CameraSensorHelperOv13858() { - gainType_ = AnalogueGainLinear; - gainConstants_.linear = { 1, 0, 0, 128 }; + gain_ = AnalogueGainLinear{ 1, 0, 0, 128 }; } }; REGISTER_CAMERA_SENSOR_HELPER("ov13858", CameraSensorHelperOv13858) diff --git a/src/ipa/libipa/camera_sensor_helper.h b/src/ipa/libipa/camera_sensor_helper.h index 0d99073b..a9300a64 100644 --- a/src/ipa/libipa/camera_sensor_helper.h +++ b/src/ipa/libipa/camera_sensor_helper.h @@ -7,10 +7,11 @@ #pragma once -#include <stdint.h> - #include <memory> +#include <optional> +#include <stdint.h> #include <string> +#include <variant> #include <vector> #include <libcamera/base/class.h> @@ -25,34 +26,25 @@ public: CameraSensorHelper() = default; virtual ~CameraSensorHelper() = default; + std::optional<int16_t> blackLevel() const { return blackLevel_; } virtual uint32_t gainCode(double gain) const; virtual double gain(uint32_t gainCode) const; protected: - enum AnalogueGainType { - AnalogueGainLinear, - AnalogueGainExponential, - }; - - struct AnalogueGainLinearConstants { + struct AnalogueGainLinear { int16_t m0; int16_t c0; int16_t m1; int16_t c1; }; - struct AnalogueGainExpConstants { + struct AnalogueGainExp { double a; double m; }; - union AnalogueGainConstants { - AnalogueGainLinearConstants linear; - AnalogueGainExpConstants exp; - }; - - AnalogueGainType gainType_; - AnalogueGainConstants gainConstants_; + std::optional<int16_t> blackLevel_; + std::variant<std::monostate, AnalogueGainLinear, AnalogueGainExp> gain_; private: LIBCAMERA_DISABLE_COPY_AND_MOVE(CameraSensorHelper) diff --git a/src/ipa/libipa/colours.cpp b/src/ipa/libipa/colours.cpp new file mode 100644 index 00000000..97124cf4 --- /dev/null +++ b/src/ipa/libipa/colours.cpp @@ -0,0 +1,81 @@ +/* SPDX-License-Identifier: BSD-2-Clause */ +/* + * Copyright (C) 2024, Ideas on Board Oy + * + * libipa miscellaneous colour helpers + */ + +#include "colours.h" + +#include <algorithm> +#include <cmath> + +namespace libcamera { + +namespace ipa { + +/** + * \file colours.h + * \brief Functions to reduce code duplication between IPA modules + */ + +/** + * \brief Estimate luminance from RGB values following ITU-R BT.601 + * \param[in] rgb The RGB value + * + * This function estimates a luminance value from a triplet of Red, Green and + * Blue values, following the formula defined by ITU-R Recommendation BT.601-7 + * which can be found at https://www.itu.int/rec/R-REC-BT.601 + * + * \return The estimated luminance value + */ +double rec601LuminanceFromRGB(const RGB<double> &rgb) +{ + static const Vector<double, 3> rgb2y{{ + 0.299, 0.587, 0.114 + }}; + + return rgb.dot(rgb2y); +} + +/** + * \brief Estimate correlated colour temperature from RGB color space input + * \param[in] rgb The RGB value + * + * This function estimates the correlated color temperature RGB color space + * input. In physics and color science, the Planckian locus or black body locus + * is the path or locus that the color of an incandescent black body would take + * in a particular chromaticity space as the black body temperature changes. + * + * If a narrow range of color temperatures is considered (those encapsulating + * daylight being the most practical case) one can approximate the Planckian + * locus in order to calculate the CCT in terms of chromaticity coordinates. + * + * More detailed information can be found in: + * https://en.wikipedia.org/wiki/Color_temperature#Approximation + * + * \return The estimated color temperature + */ +uint32_t estimateCCT(const RGB<double> &rgb) +{ + /* + * Convert the RGB values to CIE tristimulus values (XYZ) and divide by + * the sum of X, Y and Z to calculate the CIE xy chromaticity. + */ + static const Matrix<double, 3, 3> rgb2xyz({ + -0.14282, 1.54924, -0.95641, + -0.32466, 1.57837, -0.73191, + -0.68202, 0.77073, 0.56332 + }); + + Vector<double, 3> xyz = rgb2xyz * rgb; + xyz /= xyz.sum(); + + /* Calculate CCT */ + double n = (xyz.x() - 0.3320) / (0.1858 - xyz.y()); + return 449 * n * n * n + 3525 * n * n + 6823.3 * n + 5520.33; +} + +} /* namespace ipa */ + +} /* namespace libcamera */ diff --git a/src/ipa/libipa/colours.h b/src/ipa/libipa/colours.h new file mode 100644 index 00000000..d39b2ca8 --- /dev/null +++ b/src/ipa/libipa/colours.h @@ -0,0 +1,23 @@ +/* SPDX-License-Identifier: BSD-2-Clause */ +/* + * Copyright (C) 2024, Ideas on Board Oy + * + * libipa miscellaneous colour helpers + */ + +#pragma once + +#include <stdint.h> + +#include "libcamera/internal/vector.h" + +namespace libcamera { + +namespace ipa { + +double rec601LuminanceFromRGB(const RGB<double> &rgb); +uint32_t estimateCCT(const RGB<double> &rgb); + +} /* namespace ipa */ + +} /* namespace libcamera */ diff --git a/src/ipa/libipa/exposure_mode_helper.cpp b/src/ipa/libipa/exposure_mode_helper.cpp index 683a564a..f235316d 100644 --- a/src/ipa/libipa/exposure_mode_helper.cpp +++ b/src/ipa/libipa/exposure_mode_helper.cpp @@ -14,9 +14,9 @@ * \file exposure_mode_helper.h * \brief Helper class that performs computations relating to exposure * - * AEGC algorithms have a need to split exposure between shutter time, analogue + * AEGC algorithms have a need to split exposure between exposure time, analogue * and digital gain. Multiple implementations do so based on paired stages of - * shutter time and gain limits; provide a helper to avoid duplicating the code. + * exposure time and gain limits; provide a helper to avoid duplicating the code. */ namespace libcamera { @@ -29,24 +29,24 @@ namespace ipa { /** * \class ExposureModeHelper - * \brief Class for splitting exposure into shutter time and total gain + * \brief Class for splitting exposure into exposure time and total gain * * The ExposureModeHelper class provides a standard interface through which an - * AEGC algorithm can divide exposure between shutter time and gain. It is - * configured with a set of shutter time and gain pairs and works by initially - * fixing gain at 1.0 and increasing shutter time up to the shutter time value + * AEGC algorithm can divide exposure between exposure time and gain. It is + * configured with a set of exposure time and gain pairs and works by initially + * fixing gain at 1.0 and increasing exposure time up to the exposure time value * from the first pair in the set in an attempt to meet the required exposure * value. * - * If the required exposure is not achievable by the first shutter time value + * If the required exposure is not achievable by the first exposure time value * alone it ramps gain up to the value from the first pair in the set. If the - * required exposure is still not met it then allows shutter time to ramp up to - * the shutter time value from the second pair in the set, and continues in this + * required exposure is still not met it then allows exposure time to ramp up to + * the exposure time value from the second pair in the set, and continues in this * vein until either the required exposure time is met, or else the hardware's - * shutter time or gain limits are reached. + * exposure time or gain limits are reached. * * This method allows users to strike a balance between a well-exposed image and - * an acceptable frame-rate, as opposed to simply maximising shutter time + * an acceptable frame-rate, as opposed to simply maximising exposure time * followed by gain. The same helpers can be used to perform the latter * operation if needed by passing an empty set of pairs to the initialisation * function. @@ -61,56 +61,56 @@ namespace ipa { /** * \brief Construct an ExposureModeHelper instance - * \param[in] stages The vector of paired shutter time and gain limits + * \param[in] stages The vector of paired exposure time and gain limits * - * The input stages are shutter time and _total_ gain pairs; the gain + * The input stages are exposure time and _total_ gain pairs; the gain * encompasses both analogue and digital gain. * * The vector of stages may be empty. In that case, the helper will simply use - * the runtime limits set through setShutterGainLimits() instead. + * the runtime limits set through setLimits() instead. */ ExposureModeHelper::ExposureModeHelper(const Span<std::pair<utils::Duration, double>> stages) { - minShutter_ = 0us; - maxShutter_ = 0us; + minExposureTime_ = 0us; + maxExposureTime_ = 0us; minGain_ = 0; maxGain_ = 0; for (const auto &[s, g] : stages) { - shutters_.push_back(s); + exposureTimes_.push_back(s); gains_.push_back(g); } } /** - * \brief Set the shutter time and gain limits - * \param[in] minShutter The minimum shutter time supported - * \param[in] maxShutter The maximum shutter time supported + * \brief Set the exposure time and gain limits + * \param[in] minExposureTime The minimum exposure time supported + * \param[in] maxExposureTime The maximum exposure time supported * \param[in] minGain The minimum analogue gain supported * \param[in] maxGain The maximum analogue gain supported * - * This function configures the shutter time and analogue gain limits that need + * This function configures the exposure time and analogue gain limits that need * to be adhered to as the helper divides up exposure. Note that this function * *must* be called whenever those limits change and before splitExposure() is * used. * - * If the algorithm using the helpers needs to indicate that either shutter time + * If the algorithm using the helpers needs to indicate that either exposure time * or analogue gain or both should be fixed it can do so by setting both the * minima and maxima to the same value. */ -void ExposureModeHelper::setLimits(utils::Duration minShutter, - utils::Duration maxShutter, +void ExposureModeHelper::setLimits(utils::Duration minExposureTime, + utils::Duration maxExposureTime, double minGain, double maxGain) { - minShutter_ = minShutter; - maxShutter_ = maxShutter; + minExposureTime_ = minExposureTime; + maxExposureTime_ = maxExposureTime; minGain_ = minGain; maxGain_ = maxGain; } -utils::Duration ExposureModeHelper::clampShutter(utils::Duration shutter) const +utils::Duration ExposureModeHelper::clampExposureTime(utils::Duration exposureTime) const { - return std::clamp(shutter, minShutter_, maxShutter_); + return std::clamp(exposureTime, minExposureTime_, maxExposureTime_); } double ExposureModeHelper::clampGain(double gain) const @@ -119,125 +119,119 @@ double ExposureModeHelper::clampGain(double gain) const } /** - * \brief Split exposure time into shutter time and gain - * \param[in] exposure Exposure time + * \brief Split exposure into exposure time and gain + * \param[in] exposure Exposure value * - * This function divides a given exposure time into shutter time, analogue and - * digital gain by iterating through stages of shutter time and gain limits. At - * each stage the current stage's shutter time limit is multiplied by the + * This function divides a given exposure into exposure time, analogue and + * digital gain by iterating through stages of exposure time and gain limits. + * At each stage the current stage's exposure time limit is multiplied by the * previous stage's gain limit (or 1.0 initially) to see if the combination of - * the two can meet the required exposure time. If they cannot then the current - * stage's shutter time limit is multiplied by the same stage's gain limit to + * the two can meet the required exposure. If they cannot then the current + * stage's exposure time limit is multiplied by the same stage's gain limit to * see if that combination can meet the required exposure time. If they cannot * then the function moves to consider the next stage. * - * When a combination of shutter time and gain _stage_ limits are found that are - * sufficient to meet the required exposure time, the function attempts to - * reduce shutter time as much as possible whilst fixing gain and still meeting - * the exposure time. If a _runtime_ limit prevents shutter time from being - * lowered enough to meet the exposure time with gain fixed at the stage limit, - * gain is also lowered to compensate. + * When a combination of exposure time and gain _stage_ limits are found that + * are sufficient to meet the required exposure, the function attempts to reduce + * exposure time as much as possible whilst fixing gain and still meeting the + * exposure. If a _runtime_ limit prevents exposure time from being lowered + * enough to meet the exposure with gain fixed at the stage limit, gain is also + * lowered to compensate. * - * Once the shutter time and gain values are ascertained, gain is assigned as + * Once the exposure time and gain values are ascertained, gain is assigned as * analogue gain as much as possible, with digital gain only in use if the * maximum analogue gain runtime limit is unable to accommodate the exposure * value. * - * If no combination of shutter time and gain limits is found that meets the - * required exposure time, the helper falls-back to simply maximising the - * shutter time first, followed by analogue gain, followed by digital gain. + * If no combination of exposure time and gain limits is found that meets the + * required exposure, the helper falls-back to simply maximising the exposure + * time first, followed by analogue gain, followed by digital gain. * - * \return Tuple of shutter time, analogue gain, and digital gain + * \return Tuple of exposure time, analogue gain, and digital gain */ std::tuple<utils::Duration, double, double> ExposureModeHelper::splitExposure(utils::Duration exposure) const { - ASSERT(maxShutter_); + ASSERT(maxExposureTime_); ASSERT(maxGain_); bool gainFixed = minGain_ == maxGain_; - bool shutterFixed = minShutter_ == maxShutter_; + bool exposureTimeFixed = minExposureTime_ == maxExposureTime_; /* * There's no point entering the loop if we cannot change either gain - * nor shutter anyway. + * nor exposure time anyway. */ - if (shutterFixed && gainFixed) - return { minShutter_, minGain_, exposure / (minShutter_ * minGain_) }; + if (exposureTimeFixed && gainFixed) + return { minExposureTime_, minGain_, exposure / (minExposureTime_ * minGain_) }; - utils::Duration shutter; - double stageGain; + utils::Duration exposureTime; + double stageGain = 1.0; double gain; for (unsigned int stage = 0; stage < gains_.size(); stage++) { double lastStageGain = stage == 0 ? 1.0 : clampGain(gains_[stage - 1]); - utils::Duration stageShutter = clampShutter(shutters_[stage]); + utils::Duration stageExposureTime = clampExposureTime(exposureTimes_[stage]); stageGain = clampGain(gains_[stage]); /* - * We perform the clamping on both shutter and gain in case the - * helper has had limits set that prevent those values being - * lowered beyond a certain minimum...this can happen at runtime - * for various reasons and so would not be known when the stage - * limits are initialised. + * We perform the clamping on both exposure time and gain in + * case the helper has had limits set that prevent those values + * being lowered beyond a certain minimum...this can happen at + * runtime for various reasons and so would not be known when + * the stage limits are initialised. */ - if (stageShutter * lastStageGain >= exposure) { - shutter = clampShutter(exposure / clampGain(lastStageGain)); - gain = clampGain(exposure / shutter); + if (stageExposureTime * lastStageGain >= exposure) { + exposureTime = clampExposureTime(exposure / clampGain(lastStageGain)); + gain = clampGain(exposure / exposureTime); - return { shutter, gain, exposure / (shutter * gain) }; + return { exposureTime, gain, exposure / (exposureTime * gain) }; } - if (stageShutter * stageGain >= exposure) { - shutter = clampShutter(exposure / clampGain(stageGain)); - gain = clampGain(exposure / shutter); + if (stageExposureTime * stageGain >= exposure) { + exposureTime = clampExposureTime(exposure / clampGain(stageGain)); + gain = clampGain(exposure / exposureTime); - return { shutter, gain, exposure / (shutter * gain) }; + return { exposureTime, gain, exposure / (exposureTime * gain) }; } } /* - * From here on all we can do is max out the shutter time, followed by + * From here on all we can do is max out the exposure time, followed by * the analogue gain. If we still haven't achieved the target we send * the rest of the exposure time to digital gain. If we were given no - * stages to use then set stageGain to 1.0 so that shutter time is maxed - * before gain touched at all. + * stages to use then the default stageGain of 1.0 is used so that + * exposure time is maxed before gain is touched at all. */ - if (gains_.empty()) - stageGain = 1.0; + exposureTime = clampExposureTime(exposure / clampGain(stageGain)); + gain = clampGain(exposure / exposureTime); - shutter = clampShutter(exposure / clampGain(stageGain)); - gain = clampGain(exposure / shutter); - - return { shutter, gain, exposure / (shutter * gain) }; + return { exposureTime, gain, exposure / (exposureTime * gain) }; } /** - * \fn ExposureModeHelper::minShutter() - * \brief Retrieve the configured minimum shutter time limit set through - * setShutterGainLimits() - * \return The minShutter_ value + * \fn ExposureModeHelper::minExposureTime() + * \brief Retrieve the configured minimum exposure time limit set through + * setLimits() + * \return The minExposureTime_ value */ /** - * \fn ExposureModeHelper::maxShutter() - * \brief Retrieve the configured maximum shutter time set through - * setShutterGainLimits() - * \return The maxShutter_ value + * \fn ExposureModeHelper::maxExposureTime() + * \brief Retrieve the configured maximum exposure time set through setLimits() + * \return The maxExposureTime_ value */ /** * \fn ExposureModeHelper::minGain() - * \brief Retrieve the configured minimum gain set through - * setShutterGainLimits() + * \brief Retrieve the configured minimum gain set through setLimits() * \return The minGain_ value */ /** * \fn ExposureModeHelper::maxGain() - * \brief Retrieve the configured maximum gain set through - * setShutterGainLimits() + * \brief Retrieve the configured maximum gain set through setLimits() * \return The maxGain_ value */ diff --git a/src/ipa/libipa/exposure_mode_helper.h b/src/ipa/libipa/exposure_mode_helper.h index 85c665d7..c5be1b67 100644 --- a/src/ipa/libipa/exposure_mode_helper.h +++ b/src/ipa/libipa/exposure_mode_helper.h @@ -24,26 +24,26 @@ public: ExposureModeHelper(const Span<std::pair<utils::Duration, double>> stages); ~ExposureModeHelper() = default; - void setLimits(utils::Duration minShutter, utils::Duration maxShutter, + void setLimits(utils::Duration minExposureTime, utils::Duration maxExposureTime, double minGain, double maxGain); std::tuple<utils::Duration, double, double> splitExposure(utils::Duration exposure) const; - utils::Duration minShutter() const { return minShutter_; } - utils::Duration maxShutter() const { return maxShutter_; } + utils::Duration minExposureTime() const { return minExposureTime_; } + utils::Duration maxExposureTime() const { return maxExposureTime_; } double minGain() const { return minGain_; } double maxGain() const { return maxGain_; } private: - utils::Duration clampShutter(utils::Duration shutter) const; + utils::Duration clampExposureTime(utils::Duration exposureTime) const; double clampGain(double gain) const; - std::vector<utils::Duration> shutters_; + std::vector<utils::Duration> exposureTimes_; std::vector<double> gains_; - utils::Duration minShutter_; - utils::Duration maxShutter_; + utils::Duration minExposureTime_; + utils::Duration maxExposureTime_; double minGain_; double maxGain_; }; diff --git a/src/ipa/libipa/fc_queue.h b/src/ipa/libipa/fc_queue.h index 24d9e82b..a1d13652 100644 --- a/src/ipa/libipa/fc_queue.h +++ b/src/ipa/libipa/fc_queue.h @@ -25,6 +25,7 @@ struct FrameContext { private: template<typename T> friend class FCQueue; uint32_t frame; + bool initialised = false; }; template<typename FrameContext> @@ -38,8 +39,10 @@ public: void clear() { - for (FrameContext &ctx : contexts_) + for (FrameContext &ctx : contexts_) { + ctx.initialised = false; ctx.frame = 0; + } } FrameContext &alloc(const uint32_t frame) @@ -83,6 +86,21 @@ public: << " has been overwritten by " << frameContext.frame; + if (frame == 0 && !frameContext.initialised) { + /* + * If the IPA calls get() at start() time it will get an + * un-intialized FrameContext as the below "frame == + * frameContext.frame" check will return success because + * FrameContexts are zeroed at creation time. + * + * Make sure the FrameContext gets initialised if get() + * is called before alloc() by the IPA for frame#0. + */ + init(frameContext, frame); + + return frameContext; + } + if (frame == frameContext.frame) return frameContext; @@ -108,6 +126,7 @@ private: { frameContext = {}; frameContext.frame = frame; + frameContext.initialised = true; } std::vector<FrameContext> contexts_; diff --git a/src/ipa/libipa/fixedpoint.cpp b/src/ipa/libipa/fixedpoint.cpp new file mode 100644 index 00000000..6b698fc5 --- /dev/null +++ b/src/ipa/libipa/fixedpoint.cpp @@ -0,0 +1,42 @@ +/* SPDX-License-Identifier: LGPL-2.1-or-later */ +/* + * Copyright (C) 2024, Paul Elder <paul.elder@ideasonboard.com> + * + * Fixed / floating point conversions + */ + +#include "fixedpoint.h" + +/** + * \file fixedpoint.h + */ + +namespace libcamera { + +namespace ipa { + +/** + * \fn R floatingToFixedPoint(T number) + * \brief Convert a floating point number to a fixed-point representation + * \tparam I Bit width of the integer part of the fixed-point + * \tparam F Bit width of the fractional part of the fixed-point + * \tparam R Return type of the fixed-point representation + * \tparam T Input type of the floating point representation + * \param number The floating point number to convert to fixed point + * \return The converted value + */ + +/** + * \fn R fixedToFloatingPoint(T number) + * \brief Convert a fixed-point number to a floating point representation + * \tparam I Bit width of the integer part of the fixed-point + * \tparam F Bit width of the fractional part of the fixed-point + * \tparam R Return type of the floating point representation + * \tparam T Input type of the fixed-point representation + * \param number The fixed point number to convert to floating point + * \return The converted value + */ + +} /* namespace ipa */ + +} /* namespace libcamera */ diff --git a/src/ipa/libipa/fixedpoint.h b/src/ipa/libipa/fixedpoint.h new file mode 100644 index 00000000..709cf50f --- /dev/null +++ b/src/ipa/libipa/fixedpoint.h @@ -0,0 +1,65 @@ +/* SPDX-License-Identifier: LGPL-2.1-or-later */ +/* + * Copyright (C) 2024, Paul Elder <paul.elder@ideasonboard.com> + * + * Fixed / floating point conversions + */ + +#pragma once + +#include <cmath> +#include <type_traits> + +namespace libcamera { + +namespace ipa { + +#ifndef __DOXYGEN__ +template<unsigned int I, unsigned int F, typename R, typename T, + std::enable_if_t<std::is_integral_v<R> && + std::is_floating_point_v<T>> * = nullptr> +#else +template<unsigned int I, unsigned int F, typename R, typename T> +#endif +constexpr R floatingToFixedPoint(T number) +{ + static_assert(sizeof(int) >= sizeof(R)); + static_assert(I + F <= sizeof(R) * 8); + + /* + * The intermediate cast to int is needed on arm platforms to properly + * cast negative values. See + * https://embeddeduse.com/2013/08/25/casting-a-negative-float-to-an-unsigned-int/ + */ + R mask = (1 << (F + I)) - 1; + R frac = static_cast<R>(static_cast<int>(std::round(number * (1 << F)))) & mask; + + return frac; +} + +#ifndef __DOXYGEN__ +template<unsigned int I, unsigned int F, typename R, typename T, + std::enable_if_t<std::is_floating_point_v<R> && + std::is_integral_v<T>> * = nullptr> +#else +template<unsigned int I, unsigned int F, typename R, typename T> +#endif +constexpr R fixedToFloatingPoint(T number) +{ + static_assert(sizeof(int) >= sizeof(T)); + static_assert(I + F <= sizeof(T) * 8); + + /* + * Recreate the upper bits in case of a negative number by shifting the sign + * bit from the fixed point to the first bit of the unsigned and then right shifting + * by the same amount which keeps the sign bit in place. + * This can be optimized by the compiler quite well. + */ + int remaining_bits = sizeof(int) * 8 - (I + F); + int t = static_cast<int>(static_cast<unsigned>(number) << remaining_bits) >> remaining_bits; + return static_cast<R>(t) / static_cast<R>(1 << F); +} + +} /* namespace ipa */ + +} /* namespace libcamera */ diff --git a/src/ipa/libipa/histogram.cpp b/src/ipa/libipa/histogram.cpp index 5fbfadf5..10e44b54 100644 --- a/src/ipa/libipa/histogram.cpp +++ b/src/ipa/libipa/histogram.cpp @@ -63,6 +63,12 @@ Histogram::Histogram(Span<const uint32_t> data) */ /** + * \fn Histogram::data() + * \brief Retrieve the internal data + * \return The data + */ + +/** * \fn Histogram::total() * \brief Retrieve the total number of values in the data set * \return Number of values diff --git a/src/ipa/libipa/histogram.h b/src/ipa/libipa/histogram.h index 032adca0..a926002c 100644 --- a/src/ipa/libipa/histogram.h +++ b/src/ipa/libipa/histogram.h @@ -7,7 +7,6 @@ #pragma once -#include <assert.h> #include <limits.h> #include <stdint.h> #include <type_traits> @@ -37,6 +36,7 @@ public: } size_t bins() const { return cumulative_.size() - 1; } + const Span<const uint64_t> data() const { return cumulative_; } uint64_t total() const { return cumulative_[cumulative_.size() - 1]; } uint64_t cumulativeFrequency(double bin) const; double quantile(double q, uint32_t first = 0, uint32_t last = UINT_MAX) const; diff --git a/src/ipa/libipa/interpolator.cpp b/src/ipa/libipa/interpolator.cpp new file mode 100644 index 00000000..f901a86e --- /dev/null +++ b/src/ipa/libipa/interpolator.cpp @@ -0,0 +1,163 @@ +/* SPDX-License-Identifier: LGPL-2.1-or-later */ +/* + * Copyright (C) 2024, Paul Elder <paul.elder@ideasonboard.com> + * + * Helper class for interpolating objects + */ +#include "interpolator.h" + +#include <algorithm> +#include <string> + +#include <libcamera/base/log.h> + +#include "libcamera/internal/yaml_parser.h" + +#include "interpolator.h" + +/** + * \file interpolator.h + * \brief Helper class for linear interpolating a set of objects + */ + +namespace libcamera { + +LOG_DEFINE_CATEGORY(Interpolator) + +namespace ipa { + +/** + * \class Interpolator + * \brief Class for storing, retrieving, and interpolating objects + * \tparam T Type of objects stored in the interpolator + * + * The main use case is to pass a map from color temperatures to corresponding + * objects (eg. matrices for color correction), and then requesting a + * interpolated object for a specific color temperature. This class will + * abstract away the interpolation portion. + */ + +/** + * \fn Interpolator::Interpolator() + * \brief Construct an empty interpolator + */ + +/** + * \fn Interpolator::Interpolator(const std::map<unsigned int, T> &data) + * \brief Construct an interpolator from a map of objects + * \param data Map from which to construct the interpolator + */ + +/** + * \fn Interpolator::Interpolator(std::map<unsigned int, T> &&data) + * \brief Construct an interpolator from a map of objects + * \param data Map from which to construct the interpolator + */ + +/** + * \fn int Interpolator<T>::readYaml(const libcamera::YamlObject &yaml, + const std::string &key_name, + const std::string &value_name) + * \brief Initialize an Interpolator instance from yaml + * \tparam T Type of data stored in the interpolator + * \param[in] yaml The yaml object that contains the map of unsigned integers to + * objects + * \param[in] key_name The name of the key in the yaml object + * \param[in] value_name The name of the value in the yaml object + * + * The yaml object is expected to be a list of maps. Each map has two or more + * pairs: one of \a key_name to the key value (usually color temperature), and + * one or more of \a value_name to the object. This is a bit difficult to + * explain, so here is an example (in python, as it is easier to parse than + * yaml): + * [ + * { + * 'ct': 2860, + * 'ccm': [ 2.12089, -0.52461, -0.59629, + * -0.85342, 2.80445, -0.95103, + * -0.26897, -1.14788, 2.41685 ], + * 'offsets': [ 0, 0, 0 ] + * }, + * + * { + * 'ct': 2960, + * 'ccm': [ 2.26962, -0.54174, -0.72789, + * -0.77008, 2.60271, -0.83262, + * -0.26036, -1.51254, 2.77289 ], + * 'offsets': [ 0, 0, 0 ] + * }, + * + * { + * 'ct': 3603, + * 'ccm': [ 2.18644, -0.66148, -0.52496, + * -0.77828, 2.69474, -0.91645, + * -0.25239, -0.83059, 2.08298 ], + * 'offsets': [ 0, 0, 0 ] + * }, + * ] + * + * In this case, \a key_name would be 'ct', and \a value_name can be either + * 'ccm' or 'offsets'. This way multiple interpolators can be defined in + * one set of color temperature ranges in the tuning file, and they can be + * retrieved separately with the \a value_name parameter. + * + * \return Zero on success, negative error code otherwise + */ + +/** + * \fn void Interpolator<T>::setQuantization(const unsigned int q) + * \brief Set the quantization value + * \param[in] q The quantization value + * + * Sets the quantization value. When this is set, 'key' gets quantized to this + * size, before doing the interpolation. This can help in reducing the number of + * updates pushed to the hardware. + * + * Note that normally a threshold needs to be combined with quantization. + * Otherwise a value that swings around the edge of the quantization step will + * lead to constant updates. + */ + +/** + * \fn void Interpolator<T>::setData(std::map<unsigned int, T> &&data) + * \brief Set the internal map + * + * Overwrites the internal map using move semantics. + */ + +/** + * \fn std::map<unsigned int, T> &Interpolator<T>::data() const + * \brief Access the internal map + * + * \return The internal map + */ + +/** + * \fn const T& Interpolator<T>::getInterpolated() + * \brief Retrieve an interpolated value for the given key + * \param[in] key The unsigned integer key of the object to retrieve + * \param[out] quantizedKey If provided, the key value after quantization + * \return The object corresponding to the key. The object is cached internally, + * so on successive calls with the same key (after quantization) interpolation + * is not recalculated. + */ + +/** + * \fn void Interpolator<T>::interpolate(const T &a, const T &b, T &dest, double lambda) + * \brief Interpolate between two instances of T + * \param a The first value to interpolate + * \param b The second value to interpolate + * \param dest The destination for the interpolated value + * \param lambda The interpolation factor (0..1) + * + * Interpolates between \a a and \a b according to \a lambda. It calculates + * dest = a * (1.0 - lambda) + b * lambda; + * + * If T supports multiplication with double and addition, this function can be + * used as is. For other types this function can be overwritten using partial + * template specialization. + */ + +} /* namespace ipa */ + +} /* namespace libcamera */ diff --git a/src/ipa/libipa/interpolator.h b/src/ipa/libipa/interpolator.h new file mode 100644 index 00000000..7880db69 --- /dev/null +++ b/src/ipa/libipa/interpolator.h @@ -0,0 +1,136 @@ +/* SPDX-License-Identifier: LGPL-2.1-or-later */ +/* + * Copyright (C) 2024, Paul Elder <paul.elder@ideasonboard.com> + * + * Helper class for interpolating maps of objects + */ + +#pragma once + +#include <algorithm> +#include <cmath> +#include <map> +#include <string> +#include <tuple> + +#include <libcamera/base/log.h> + +#include "libcamera/internal/yaml_parser.h" + +namespace libcamera { + +LOG_DECLARE_CATEGORY(Interpolator) + +namespace ipa { + +template<typename T> +class Interpolator +{ +public: + Interpolator() = default; + Interpolator(const std::map<unsigned int, T> &data) + : data_(data) + { + } + Interpolator(std::map<unsigned int, T> &&data) + : data_(std::move(data)) + { + } + + ~Interpolator() = default; + + int readYaml(const libcamera::YamlObject &yaml, + const std::string &key_name, + const std::string &value_name) + { + data_.clear(); + lastInterpolatedKey_.reset(); + + if (!yaml.isList()) { + LOG(Interpolator, Error) << "yaml object must be a list"; + return -EINVAL; + } + + for (const auto &value : yaml.asList()) { + unsigned int ct = std::stoul(value[key_name].get<std::string>("")); + std::optional<T> data = + value[value_name].get<T>(); + if (!data) { + return -EINVAL; + } + + data_[ct] = *data; + } + + if (data_.size() < 1) { + LOG(Interpolator, Error) << "Need at least one element"; + return -EINVAL; + } + + return 0; + } + + void setQuantization(const unsigned int q) + { + quantization_ = q; + } + + void setData(std::map<unsigned int, T> &&data) + { + data_ = std::move(data); + lastInterpolatedKey_.reset(); + } + + const std::map<unsigned int, T> &data() const + { + return data_; + } + + const T &getInterpolated(unsigned int key, unsigned int *quantizedKey = nullptr) + { + ASSERT(data_.size() > 0); + + if (quantization_ > 0) + key = std::lround(key / static_cast<double>(quantization_)) * quantization_; + + if (quantizedKey) + *quantizedKey = key; + + if (lastInterpolatedKey_.has_value() && + *lastInterpolatedKey_ == key) + return lastInterpolatedValue_; + + auto it = data_.lower_bound(key); + + if (it == data_.begin()) + return it->second; + + if (it == data_.end()) + return std::prev(it)->second; + + if (it->first == key) + return it->second; + + auto it2 = std::prev(it); + double lambda = (key - it2->first) / static_cast<double>(it->first - it2->first); + interpolate(it2->second, it->second, lastInterpolatedValue_, lambda); + lastInterpolatedKey_ = key; + + return lastInterpolatedValue_; + } + + void interpolate(const T &a, const T &b, T &dest, double lambda) + { + dest = a * (1.0 - lambda) + b * lambda; + } + +private: + std::map<unsigned int, T> data_; + T lastInterpolatedValue_; + std::optional<unsigned int> lastInterpolatedKey_; + unsigned int quantization_ = 0; +}; + +} /* namespace ipa */ + +} /* namespace libcamera */ diff --git a/src/ipa/libipa/lsc_polynomial.cpp b/src/ipa/libipa/lsc_polynomial.cpp new file mode 100644 index 00000000..f607d86c --- /dev/null +++ b/src/ipa/libipa/lsc_polynomial.cpp @@ -0,0 +1,81 @@ +/* SPDX-License-Identifier: LGPL-2.1-or-later */ +/* + * Copyright (C) 2024, Ideas On Board + * + * Polynomial class to represent lens shading correction + */ + +#include "lsc_polynomial.h" + +#include <libcamera/base/log.h> + +/** + * \file lsc_polynomial.h + * \brief LscPolynomial class + */ + +namespace libcamera { + +LOG_DEFINE_CATEGORY(LscPolynomial) + +namespace ipa { + +/** + * \class LscPolynomial + * \brief Class for handling even polynomials used in lens shading correction + * + * Shading artifacts of camera lenses can be modeled using even radial + * polynomials. This class implements a polynomial with 5 coefficients which + * follows the definition of the FixVignetteRadial opcode in the Adobe DNG + * specification. + */ + +/** + * \fn LscPolynomial::LscPolynomial(double cx = 0.0, double cy = 0.0, double k0 = 0.0, + double k1 = 0.0, double k2 = 0.0, double k3 = 0.0, + double k4 = 0.0) + * \brief Construct a polynomial using the given coefficients + * \param cx Center-x relative to the image in normalized coordinates (0..1) + * \param cy Center-y relative to the image in normalized coordinates (0..1) + * \param k0 Coefficient of the polynomial + * \param k1 Coefficient of the polynomial + * \param k2 Coefficient of the polynomial + * \param k3 Coefficient of the polynomial + * \param k4 Coefficient of the polynomial + */ + +/** + * \fn LscPolynomial::sampleAtNormalizedPixelPos(double x, double y) + * \brief Sample the polynomial at the given normalized pixel position + * + * This functions samples the polynomial at the given pixel position divided by + * the value returned by getM(). + * + * \param x x position in normalized coordinates + * \param y y position in normalized coordinates + * \return The sampled value + */ + +/** + * \fn LscPolynomial::getM() + * \brief Get the value m as described in the dng specification + * + * Returns m according to dng spec. m represents the Euclidean distance + * (in pixels) from the optical center to the farthest pixel in the + * image. + * + * \return The sampled value + */ + +/** + * \fn LscPolynomial::setReferenceImageSize(const Size &size) + * \brief Set the reference image size + * + * Set the reference image size that is used for subsequent calls to getM() and + * sampleAtNormalizedPixelPos() + * + * \param size The size of the reference image + */ + +} // namespace ipa +} // namespace libcamera diff --git a/src/ipa/libipa/lsc_polynomial.h b/src/ipa/libipa/lsc_polynomial.h new file mode 100644 index 00000000..c898faeb --- /dev/null +++ b/src/ipa/libipa/lsc_polynomial.h @@ -0,0 +1,105 @@ +/* SPDX-License-Identifier: LGPL-2.1-or-later */ +/* + * Copyright (C) 2024, Ideas On Board + * + * Helper for radial polynomial used in lens shading correction. + */ +#pragma once + +#include <algorithm> +#include <array> +#include <assert.h> +#include <cmath> + +#include <libcamera/base/log.h> +#include <libcamera/base/span.h> + +#include "libcamera/internal/yaml_parser.h" + +namespace libcamera { + +LOG_DECLARE_CATEGORY(LscPolynomial) + +namespace ipa { + +class LscPolynomial +{ +public: + LscPolynomial(double cx = 0.0, double cy = 0.0, double k0 = 0.0, + double k1 = 0.0, double k2 = 0.0, double k3 = 0.0, + double k4 = 0.0) + : cx_(cx), cy_(cy), cnx_(0), cny_(0), + coefficients_({ k0, k1, k2, k3, k4 }) + { + } + + double sampleAtNormalizedPixelPos(double x, double y) const + { + double dx = x - cnx_; + double dy = y - cny_; + double r = sqrt(dx * dx + dy * dy); + double res = 1.0; + for (unsigned int i = 0; i < coefficients_.size(); i++) { + res += coefficients_[i] * std::pow(r, (i + 1) * 2); + } + return res; + } + + double getM() const + { + double cpx = imageSize_.width * cx_; + double cpy = imageSize_.height * cy_; + double mx = std::max(cpx, std::fabs(imageSize_.width - cpx)); + double my = std::max(cpy, std::fabs(imageSize_.height - cpy)); + + return sqrt(mx * mx + my * my); + } + + void setReferenceImageSize(const Size &size) + { + assert(!size.isNull()); + imageSize_ = size; + + /* Calculate normalized centers */ + double m = getM(); + cnx_ = (size.width * cx_) / m; + cny_ = (size.height * cy_) / m; + } + +private: + double cx_; + double cy_; + double cnx_; + double cny_; + std::array<double, 5> coefficients_; + + Size imageSize_; +}; + +} /* namespace ipa */ + +#ifndef __DOXYGEN__ + +template<> +struct YamlObject::Getter<ipa::LscPolynomial> { + std::optional<ipa::LscPolynomial> get(const YamlObject &obj) const + { + std::optional<double> cx = obj["cx"].get<double>(); + std::optional<double> cy = obj["cy"].get<double>(); + std::optional<double> k0 = obj["k0"].get<double>(); + std::optional<double> k1 = obj["k1"].get<double>(); + std::optional<double> k2 = obj["k2"].get<double>(); + std::optional<double> k3 = obj["k3"].get<double>(); + std::optional<double> k4 = obj["k4"].get<double>(); + + if (!(cx && cy && k0 && k1 && k2 && k3 && k4)) + LOG(LscPolynomial, Error) + << "Polynomial is missing a parameter"; + + return ipa::LscPolynomial(*cx, *cy, *k0, *k1, *k2, *k3, *k4); + } +}; + +#endif + +} /* namespace libcamera */ diff --git a/src/ipa/libipa/lux.cpp b/src/ipa/libipa/lux.cpp new file mode 100644 index 00000000..899e8824 --- /dev/null +++ b/src/ipa/libipa/lux.cpp @@ -0,0 +1,173 @@ +/* SPDX-License-Identifier: BSD-2-Clause */ +/* + * Copyright (C) 2019, Raspberry Pi Ltd + * Copyright (C) 2024, Paul Elder <paul.elder@ideasonboard.com> + * + * Helper class that implements lux estimation + */ +#include "lux.h" + +#include <algorithm> +#include <chrono> + +#include <libcamera/base/log.h> + +#include "libcamera/internal/yaml_parser.h" + +#include "histogram.h" + +/** + * \file lux.h + * \brief Helper class that implements lux estimation + * + * Estimating the lux level of an image is a common operation that can for + * instance be used to adjust the target Y value in AGC or for Bayesian AWB + * estimation. + */ + +namespace libcamera { + +using namespace std::literals::chrono_literals; + +LOG_DEFINE_CATEGORY(Lux) + +namespace ipa { + +/** + * \class Lux + * \brief Class that implements lux estimation + * + * IPAs that wish to use lux estimation should create a Lux algorithm module + * that lightly wraps this module by providing the platform-specific luminance + * histogram. The Lux entry in the tuning file must then precede the algorithms + * that depend on the estimated lux value. + */ + +/** + * \var Lux::referenceExposureTime_ + * \brief The exposure time of the reference image, in microseconds + */ + +/** + * \var Lux::referenceAnalogueGain_ + * \brief The analogue gain of the reference image + */ + +/** + * \var Lux::referenceDigitalGain_ + * \brief The analogue gain of the reference image + */ + +/** + * \var Lux::referenceY_ + * \brief The measured luminance of the reference image, normalized to 1 + * + */ + +/** + * \var Lux::referenceLux_ + * \brief The estimated lux level of the reference image + */ + +/** + * \brief Construct the Lux helper module + */ +Lux::Lux() +{ +} + +/** + * \brief Parse tuning data + * \param[in] tuningData The YamlObject representing the tuning data + * + * This function parses yaml tuning data for the common Lux module. It requires + * reference exposure time, analogue gain, digital gain, and lux values. + * + * \code{.unparsed} + * algorithms: + * - Lux: + * referenceExposureTime: 10000 + * referenceAnalogueGain: 4.0 + * referenceDigitalGain: 1.0 + * referenceY: 0.1831 + * referenceLux: 1000 + * \endcode + * + * \return 0 on success or a negative error code + */ +int Lux::parseTuningData(const YamlObject &tuningData) +{ + auto value = tuningData["referenceExposureTime"].get<double>(); + if (!value) { + LOG(Lux, Error) << "Missing tuning parameter: " + << "'referenceExposureTime'"; + return -EINVAL; + } + referenceExposureTime_ = *value * 1.0us; + + value = tuningData["referenceAnalogueGain"].get<double>(); + if (!value) { + LOG(Lux, Error) << "Missing tuning parameter: " + << "'referenceAnalogueGain'"; + return -EINVAL; + } + referenceAnalogueGain_ = *value; + + value = tuningData["referenceDigitalGain"].get<double>(); + if (!value) { + LOG(Lux, Error) << "Missing tuning parameter: " + << "'referenceDigitalGain'"; + return -EINVAL; + } + referenceDigitalGain_ = *value; + + value = tuningData["referenceY"].get<double>(); + if (!value) { + LOG(Lux, Error) << "Missing tuning parameter: " + << "'referenceY'"; + return -EINVAL; + } + referenceY_ = *value; + + value = tuningData["referenceLux"].get<double>(); + if (!value) { + LOG(Lux, Error) << "Missing tuning parameter: " + << "'referenceLux'"; + return -EINVAL; + } + referenceLux_ = *value; + + return 0; +} + +/** + * \brief Estimate lux given runtime values + * \param[in] exposureTime Exposure time applied to the frame + * \param[in] aGain Analogue gain applied to the frame + * \param[in] dGain Digital gain applied to the frame + * \param[in] yHist Histogram from the ISP statistics + * + * Estimate the lux given the exposure time, gain, and histogram. + * + * \return Estimated lux value + */ +double Lux::estimateLux(utils::Duration exposureTime, + double aGain, double dGain, + const Histogram &yHist) const +{ + double currentY = yHist.interQuantileMean(0, 1); + double exposureTimeRatio = referenceExposureTime_ / exposureTime; + double aGainRatio = referenceAnalogueGain_ / aGain; + double dGainRatio = referenceDigitalGain_ / dGain; + double yRatio = (currentY / yHist.bins()) / referenceY_; + + double estimatedLux = exposureTimeRatio * aGainRatio * dGainRatio * + yRatio * referenceLux_; + + LOG(Lux, Debug) << "Estimated lux " << estimatedLux; + return estimatedLux; +} + +} /* namespace ipa */ + +} /* namespace libcamera */ diff --git a/src/ipa/libipa/lux.h b/src/ipa/libipa/lux.h new file mode 100644 index 00000000..d95bcdaf --- /dev/null +++ b/src/ipa/libipa/lux.h @@ -0,0 +1,41 @@ +/* SPDX-License-Identifier: BSD-2-Clause */ +/* + * Copyright (C) 2019, Raspberry Pi Ltd + * Copyright (C) 2024, Paul Elder <paul.elder@ideasonboard.com> + * + * Helper class that implements lux estimation + */ + +#pragma once + +#include <libcamera/base/utils.h> + +namespace libcamera { + +class YamlObject; + +namespace ipa { + +class Histogram; + +class Lux +{ +public: + Lux(); + + int parseTuningData(const YamlObject &tuningData); + double estimateLux(utils::Duration exposureTime, + double aGain, double dGain, + const Histogram &yHist) const; + +private: + utils::Duration referenceExposureTime_; + double referenceAnalogueGain_; + double referenceDigitalGain_; + double referenceY_; + double referenceLux_; +}; + +} /* namespace ipa */ + +} /* namespace libcamera */ diff --git a/src/ipa/libipa/matrix.cpp b/src/ipa/libipa/matrix.cpp deleted file mode 100644 index 8346f0d3..00000000 --- a/src/ipa/libipa/matrix.cpp +++ /dev/null @@ -1,149 +0,0 @@ -/* SPDX-License-Identifier: LGPL-2.1-or-later */ -/* - * Copyright (C) 2024, Paul Elder <paul.elder@ideasonboard.com> - * - * Matrix and related operations - */ - -#include "matrix.h" - -#include <libcamera/base/log.h> - -/** - * \file matrix.h - * \brief Matrix class - */ - -namespace libcamera { - -LOG_DEFINE_CATEGORY(Matrix) - -namespace ipa { - -/** - * \class Matrix - * \brief Matrix class - * \tparam T Type of numerical values to be stored in the matrix - * \tparam Rows Number of rows in the matrix - * \tparam Cols Number of columns in the matrix - */ - -/** - * \fn Matrix::Matrix() - * \brief Construct a zero matrix - */ - -/** - * \fn Matrix::Matrix(const std::vector<T> &data) - * \brief Construct a matrix from supplied data - * \param[in] data Data from which to construct a matrix - * - * \a data is a one-dimensional vector and will be turned into a matrix in - * row-major order. The size of \a data must be equal to the product of the - * number of rows and columns of the matrix (Rows x Cols). - */ - -/** - * \fn Matrix::identity() - * \brief Construct an identity matrix - */ - -/** - * \fn Matrix::toString() - * \brief Assemble and return a string describing the matrix - * \return A string describing the matrix - */ - -/** - * \fn Span<const T, Cols> Matrix::operator[](size_t i) const - * \brief Index to a row in the matrix - * \param[in] i Index of row to retrieve - * - * This operator[] returns a Span, which can then be indexed into again with - * another operator[], allowing a convenient m[i][j] to access elements of the - * matrix. Note that the lifetime of the Span returned by this first-level - * operator[] is bound to that of the Matrix itself, so it is not recommended - * to save the Span that is the result of this operator[]. - * - * \return Row \a i from the matrix, as a Span - */ - -/** - * \fn Matrix::operator[](size_t i) - * \copydoc Matrix::operator[](size_t i) const - */ - -/** - * \fn Matrix<T, Rows, Cols> &Matrix::operator*=(U d) - * \brief Multiply the matrix by a scalar in-place - * \tparam U Type of the numerical scalar value - * \param d The scalar multiplier - * \return Product of this matrix and scalar \a d - */ - -/** - * \fn Matrix::Matrix<U, Rows, Cols> operator*(T d, const Matrix<U, Rows, Cols> &m) - * \brief Multiply the matrix by a scalar - * \tparam T Type of the numerical scalar value - * \tparam U Type of numerical values in the matrix - * \tparam Rows Number of rows in the matrix - * \tparam Cols Number of columns in the matrix - * \param d The scalar multiplier - * \param m The matrix - * \return Product of scalar \a d and matrix \a m - */ - -/** - * \fn Matrix::Matrix<U, Rows, Cols> operator*(const Matrix<U, Rows, Cols> &m, T d) - * \copydoc operator*(T d, const Matrix<U, Rows, Cols> &m) - */ - -/** - * \fn Matrix<T, R1, C2> operator*(const Matrix<T, R1, C1> &m1, const Matrix<T, R2, C2> &m2) - * \brief Matrix multiplication - * \tparam T Type of numerical values in the matrices - * \tparam R1 Number of rows in the first matrix - * \tparam C1 Number of columns in the first matrix - * \tparam R2 Number of rows in the second matrix - * \tparam C2 Number of columns in the second matrix - * \param m1 Multiplicand matrix - * \param m2 Multiplier matrix - * \return Matrix product of matrices \a m1 and \a m2 - */ - -/** - * \fn Matrix<T, Rows, Cols> operator+(const Matrix<T, Rows, Cols> &m1, const Matrix<T, Rows, Cols> &m2) - * \brief Matrix addition - * \tparam T Type of numerical values in the matrices - * \tparam Rows Number of rows in the matrices - * \tparam Cols Number of columns in the matrices - * \param m1 Summand matrix - * \param m2 Summand matrix - * \return Matrix sum of matrices \a m1 and \a m2 - */ - -#ifndef __DOXYGEN__ -/* - * The YAML data shall be a list of numerical values. Its size shall be equal - * to the product of the number of rows and columns of the matrix (Rows x - * Cols). The values shall be stored in row-major order. - */ -bool matrixValidateYaml(const YamlObject &obj, unsigned int size) -{ - if (!obj.isList()) - return false; - - if (obj.size() != size) { - LOG(Matrix, Error) - << "Wrong number of values in matrix: expected " - << size << ", got " << obj.size(); - return false; - } - - return true; -} -#endif /* __DOXYGEN__ */ - -} /* namespace ipa */ - -} /* namespace libcamera */ diff --git a/src/ipa/libipa/matrix.h b/src/ipa/libipa/matrix.h deleted file mode 100644 index 8aa8f343..00000000 --- a/src/ipa/libipa/matrix.h +++ /dev/null @@ -1,204 +0,0 @@ -/* SPDX-License-Identifier: LGPL-2.1-or-later */ -/* - * Copyright (C) 2024, Paul Elder <paul.elder@ideasonboard.com> - * - * Matrix and related operations - */ -#pragma once - -#include <algorithm> -#include <cmath> -#include <sstream> -#include <vector> - -#include <libcamera/base/log.h> -#include <libcamera/base/span.h> - -#include "libcamera/internal/yaml_parser.h" - -namespace libcamera { - -LOG_DECLARE_CATEGORY(Matrix) - -namespace ipa { - -#ifndef __DOXYGEN__ -template<typename T, unsigned int Rows, unsigned int Cols, - std::enable_if_t<std::is_arithmetic_v<T>> * = nullptr> -#else -template<typename T, unsigned int Rows, unsigned int Cols> -#endif /* __DOXYGEN__ */ -class Matrix -{ -public: - Matrix() - { - data_.fill(static_cast<T>(0)); - } - - Matrix(const std::vector<T> &data) - { - std::copy(data.begin(), data.end(), data_.begin()); - } - - static Matrix identity() - { - Matrix ret; - for (size_t i = 0; i < std::min(Rows, Cols); i++) - ret[i][i] = static_cast<T>(1); - return ret; - } - - ~Matrix() = default; - - const std::string toString() const - { - std::stringstream out; - - out << "Matrix { "; - for (unsigned int i = 0; i < Rows; i++) { - out << "[ "; - for (unsigned int j = 0; j < Cols; j++) { - out << (*this)[i][j]; - out << ((j + 1 < Cols) ? ", " : " "); - } - out << ((i + 1 < Rows) ? "], " : "]"); - } - out << " }"; - - return out.str(); - } - - Span<const T, Cols> operator[](size_t i) const - { - return Span<const T, Cols>{ &data_.data()[i * Cols], Cols }; - } - - Span<T, Cols> operator[](size_t i) - { - return Span<T, Cols>{ &data_.data()[i * Cols], Cols }; - } - -#ifndef __DOXYGEN__ - template<typename U, std::enable_if_t<std::is_arithmetic_v<U>>> -#else - template<typename U> -#endif /* __DOXYGEN__ */ - Matrix<T, Rows, Cols> &operator*=(U d) - { - for (unsigned int i = 0; i < Rows * Cols; i++) - data_[i] *= d; - return *this; - } - -private: - std::array<T, Rows * Cols> data_; -}; - -#ifndef __DOXYGEN__ -template<typename T, typename U, unsigned int Rows, unsigned int Cols, - std::enable_if_t<std::is_arithmetic_v<T>> * = nullptr> -#else -template<typename T, typename U, unsigned int Rows, unsigned int Cols> -#endif /* __DOXYGEN__ */ -Matrix<U, Rows, Cols> operator*(T d, const Matrix<U, Rows, Cols> &m) -{ - Matrix<U, Rows, Cols> result; - - for (unsigned int i = 0; i < Rows; i++) { - for (unsigned int j = 0; j < Cols; j++) - result[i][j] = d * m[i][j]; - } - - return result; -} - -#ifndef __DOXYGEN__ -template<typename T, typename U, unsigned int Rows, unsigned int Cols, - std::enable_if_t<std::is_arithmetic_v<T>> * = nullptr> -#else -template<typename T, typename U, unsigned int Rows, unsigned int Cols> -#endif /* __DOXYGEN__ */ -Matrix<U, Rows, Cols> operator*(const Matrix<U, Rows, Cols> &m, T d) -{ - return d * m; -} - -#ifndef __DOXYGEN__ -template<typename T, - unsigned int R1, unsigned int C1, - unsigned int R2, unsigned int C2, - std::enable_if_t<C1 == R2> * = nullptr> -#else -template<typename T, unsigned int R1, unsigned int C1, unsigned int R2, unsigned in C2> -#endif /* __DOXYGEN__ */ -Matrix<T, R1, C2> operator*(const Matrix<T, R1, C1> &m1, const Matrix<T, R2, C2> &m2) -{ - Matrix<T, R1, C2> result; - - for (unsigned int i = 0; i < R1; i++) { - for (unsigned int j = 0; j < C2; j++) { - T sum = 0; - - for (unsigned int k = 0; k < C1; k++) - sum += m1[i][k] * m2[k][j]; - - result[i][j] = sum; - } - } - - return result; -} - -template<typename T, unsigned int Rows, unsigned int Cols> -Matrix<T, Rows, Cols> operator+(const Matrix<T, Rows, Cols> &m1, const Matrix<T, Rows, Cols> &m2) -{ - Matrix<T, Rows, Cols> result; - - for (unsigned int i = 0; i < Rows; i++) { - for (unsigned int j = 0; j < Cols; j++) - result[i][j] = m1[i][j] + m2[i][j]; - } - - return result; -} - -#ifndef __DOXYGEN__ -bool matrixValidateYaml(const YamlObject &obj, unsigned int size); -#endif /* __DOXYGEN__ */ - -} /* namespace ipa */ - -#ifndef __DOXYGEN__ -template<typename T, unsigned int Rows, unsigned int Cols> -std::ostream &operator<<(std::ostream &out, const ipa::Matrix<T, Rows, Cols> &m) -{ - out << m.toString(); - return out; -} - -template<typename T, unsigned int Rows, unsigned int Cols> -struct YamlObject::Getter<ipa::Matrix<T, Rows, Cols>> { - std::optional<ipa::Matrix<T, Rows, Cols>> get(const YamlObject &obj) const - { - if (!ipa::matrixValidateYaml(obj, Rows * Cols)) - return std::nullopt; - - ipa::Matrix<T, Rows, Cols> matrix; - T *data = &matrix[0][0]; - - unsigned int i = 0; - for (const YamlObject &entry : obj.asList()) { - const auto value = entry.get<T>(); - if (!value) - return std::nullopt; - - data[i++] = *value; - } - - return matrix; - } -}; -#endif /* __DOXYGEN__ */ - -} /* namespace libcamera */ diff --git a/src/ipa/libipa/matrix_interpolator.cpp b/src/ipa/libipa/matrix_interpolator.cpp deleted file mode 100644 index 04ca177f..00000000 --- a/src/ipa/libipa/matrix_interpolator.cpp +++ /dev/null @@ -1,110 +0,0 @@ -/* SPDX-License-Identifier: LGPL-2.1-or-later */ -/* - * Copyright (C) 2024, Paul Elder <paul.elder@ideasonboard.com> - * - * Helper class for interpolating maps of matrices - */ -#include "matrix_interpolator.h" - -#include <algorithm> -#include <string> - -#include <libcamera/base/log.h> - -#include "libcamera/internal/yaml_parser.h" - -#include "matrix.h" - -/** - * \file matrix_interpolator.h - * \brief Helper class for interpolating maps of matrices - */ - -namespace libcamera { - -LOG_DEFINE_CATEGORY(MatrixInterpolator) - -namespace ipa { - -/** - * \class MatrixInterpolator - * \brief Class for storing, retrieving, and interpolating matrices - * \tparam T Type of numerical values to be stored in the matrices - * \tparam R Number of rows in the matrices - * \tparam C Number of columns in the matrices - * - * The main use case is to pass a map from color temperatures to corresponding - * matrices (eg. color correction), and then requesting a matrix for a specific - * color temperature. This class will abstract away the interpolation portion. - */ - -/** - * \fn MatrixInterpolator::MatrixInterpolator(const std::map<unsigned int, Matrix<T, R, C>> &matrices) - * \brief Construct a matrix interpolator from a map of matrices - * \param matrices Map from which to construct the matrix interpolator - */ - -/** - * \fn MatrixInterpolator::reset() - * \brief Reset the matrix interpolator content to a single identity matrix - */ - -/** - * \fn int MatrixInterpolator<T, R, C>::readYaml() - * \brief Initialize an MatrixInterpolator instance from yaml - * \tparam T Type of data stored in the matrices - * \tparam R Number of rows of the matrices - * \tparam C Number of columns of the matrices - * \param[in] yaml The yaml object that contains the map of unsigned integers to matrices - * \param[in] key_name The name of the key in the yaml object - * \param[in] matrix_name The name of the matrix in the yaml object - * - * The yaml object is expected to be a list of maps. Each map has two or more - * pairs: one of \a key_name to the key value (usually color temperature), and - * one or more of \a matrix_name to the matrix. This is a bit difficult to - * explain, so here is an example (in python, as it is easier to parse than - * yaml): - * [ - * { - * 'ct': 2860, - * 'ccm': [ 2.12089, -0.52461, -0.59629, - * -0.85342, 2.80445, -0.95103, - * -0.26897, -1.14788, 2.41685 ], - * 'offsets': [ 0, 0, 0 ] - * }, - * - * { - * 'ct': 2960, - * 'ccm': [ 2.26962, -0.54174, -0.72789, - * -0.77008, 2.60271, -0.83262, - * -0.26036, -1.51254, 2.77289 ], - * 'offsets': [ 0, 0, 0 ] - * }, - * - * { - * 'ct': 3603, - * 'ccm': [ 2.18644, -0.66148, -0.52496, - * -0.77828, 2.69474, -0.91645, - * -0.25239, -0.83059, 2.08298 ], - * 'offsets': [ 0, 0, 0 ] - * }, - * ] - * - * In this case, \a key_name would be 'ct', and \a matrix_name can be either - * 'ccm' or 'offsets'. This way multiple matrix interpolators can be defined in - * one set of color temperature ranges in the tuning file, and they can be - * retrieved separately with the \a matrix_name parameter. - * - * \return Zero on success, negative error code otherwise - */ - -/** - * \fn Matrix<T, R, C> MatrixInterpolator<T, R, C>::get(unsigned int key) - * \brief Retrieve a matrix from the list of matrices, interpolating if necessary - * \param[in] key The unsigned integer key of the matrix to retrieve - * \return The matrix corresponding to the color temperature - */ - -} /* namespace ipa */ - -} /* namespace libcamera */ diff --git a/src/ipa/libipa/matrix_interpolator.h b/src/ipa/libipa/matrix_interpolator.h deleted file mode 100644 index 087c4fd1..00000000 --- a/src/ipa/libipa/matrix_interpolator.h +++ /dev/null @@ -1,122 +0,0 @@ -/* SPDX-License-Identifier: LGPL-2.1-or-later */ -/* - * Copyright (C) 2024, Paul Elder <paul.elder@ideasonboard.com> - * - * Helper class for interpolating maps of matrices - */ - -#pragma once - -#include <algorithm> -#include <map> -#include <string> -#include <tuple> - -#include <libcamera/base/log.h> - -#include "libcamera/internal/yaml_parser.h" - -#include "matrix.h" - -namespace libcamera { - -LOG_DECLARE_CATEGORY(MatrixInterpolator) - -namespace ipa { - -#ifndef __DOXYGEN__ -template<typename T, unsigned int R, unsigned int C, - std::enable_if_t<std::is_arithmetic_v<T>> * = nullptr> -#else -template<typename T, unsigned int R, unsigned int C> -#endif /* __DOXYGEN__ */ -class MatrixInterpolator -{ -public: - MatrixInterpolator() - { - reset(); - } - - MatrixInterpolator(const std::map<unsigned int, Matrix<T, R, C>> &matrices) - { - for (const auto &pair : matrices) - matrices_[pair.first] = pair.second; - } - - ~MatrixInterpolator() {} - - void reset() - { - matrices_.clear(); - matrices_[0] = Matrix<T, R, C>::identity(); - } - - int readYaml(const libcamera::YamlObject &yaml, - const std::string &key_name, - const std::string &matrix_name) - { - matrices_.clear(); - - if (!yaml.isList()) { - LOG(MatrixInterpolator, Error) << "yaml object must be a list"; - return -EINVAL; - } - - for (const auto &value : yaml.asList()) { - unsigned int ct = std::stoul(value[key_name].get<std::string>("")); - std::optional<Matrix<T, R, C>> matrix = - value[matrix_name].get<Matrix<T, R, C>>(); - if (!matrix) { - LOG(MatrixInterpolator, Error) << "Failed to read matrix"; - return -EINVAL; - } - - matrices_[ct] = *matrix; - - LOG(MatrixInterpolator, Debug) - << "Read matrix '" << matrix_name << "' for key '" - << key_name << "' " << ct << ": " - << matrices_[ct].toString(); - } - - if (matrices_.size() < 1) { - LOG(MatrixInterpolator, Error) << "Need at least one matrix"; - return -EINVAL; - } - - return 0; - } - - Matrix<T, R, C> get(unsigned int ct) - { - ASSERT(matrices_.size() > 0); - - if (matrices_.size() == 1 || - ct <= matrices_.begin()->first) - return matrices_.begin()->second; - - if (ct >= matrices_.rbegin()->first) - return matrices_.rbegin()->second; - - if (matrices_.find(ct) != matrices_.end()) - return matrices_[ct]; - - /* The above four guarantee that this will succeed */ - auto iter = matrices_.upper_bound(ct); - unsigned int ctUpper = iter->first; - unsigned int ctLower = (--iter)->first; - - double lambda = (ct - ctLower) / static_cast<double>(ctUpper - ctLower); - Matrix<T, R, C> ret = - lambda * matrices_[ctUpper] + (1.0 - lambda) * matrices_[ctLower]; - return ret; - } - -private: - std::map<unsigned int, Matrix<T, R, C>> matrices_; -}; - -} /* namespace ipa */ - -} /* namespace libcamera */ diff --git a/src/ipa/libipa/meson.build b/src/ipa/libipa/meson.build index eff8ce26..660be940 100644 --- a/src/ipa/libipa/meson.build +++ b/src/ipa/libipa/meson.build @@ -3,29 +3,39 @@ libipa_headers = files([ 'agc_mean_luminance.h', 'algorithm.h', + 'awb_bayes.h', + 'awb_grey.h', + 'awb.h', 'camera_sensor_helper.h', + 'colours.h', 'exposure_mode_helper.h', 'fc_queue.h', + 'fixedpoint.h', 'histogram.h', - 'matrix.h', - 'matrix_interpolator.h', + 'interpolator.h', + 'lsc_polynomial.h', + 'lux.h', 'module.h', 'pwl.h', - 'vector.h', ]) libipa_sources = files([ 'agc_mean_luminance.cpp', 'algorithm.cpp', + 'awb_bayes.cpp', + 'awb_grey.cpp', + 'awb.cpp', 'camera_sensor_helper.cpp', + 'colours.cpp', 'exposure_mode_helper.cpp', 'fc_queue.cpp', + 'fixedpoint.cpp', 'histogram.cpp', - 'matrix.cpp', - 'matrix_interpolator.cpp', + 'interpolator.cpp', + 'lsc_polynomial.cpp', + 'lux.cpp', 'module.cpp', 'pwl.cpp', - 'vector.cpp', ]) libipa_includes = include_directories('..') diff --git a/src/ipa/libipa/pwl.cpp b/src/ipa/libipa/pwl.cpp index 9b213754..3fa005ba 100644 --- a/src/ipa/libipa/pwl.cpp +++ b/src/ipa/libipa/pwl.cpp @@ -8,10 +8,8 @@ #include "pwl.h" -#include <assert.h> #include <cmath> #include <sstream> -#include <stdexcept> /** * \file pwl.h @@ -162,6 +160,11 @@ void Pwl::prepend(double x, double y, const double eps) */ /** + * \fn Pwl::clear() + * \brief Clear the piecewise linear function + */ + +/** * \fn Pwl::size() const * \brief Retrieve the number of points in the piecewise linear function * \return The number of points in the piecewise linear function diff --git a/src/ipa/libipa/pwl.h b/src/ipa/libipa/pwl.h index b6f93494..c1496c30 100644 --- a/src/ipa/libipa/pwl.h +++ b/src/ipa/libipa/pwl.h @@ -7,15 +7,12 @@ #pragma once #include <algorithm> -#include <cmath> #include <functional> #include <string> #include <utility> #include <vector> -#include "libcamera/internal/yaml_parser.h" - -#include "vector.h" +#include "libcamera/internal/vector.h" namespace libcamera { @@ -52,6 +49,7 @@ public: void append(double x, double y, double eps = 1e-6); bool empty() const { return points_.empty(); } + void clear() { points_.clear(); } size_t size() const { return points_.size(); } Interval domain() const; diff --git a/src/ipa/libipa/vector.cpp b/src/ipa/libipa/vector.cpp deleted file mode 100644 index bd00b019..00000000 --- a/src/ipa/libipa/vector.cpp +++ /dev/null @@ -1,168 +0,0 @@ -/* SPDX-License-Identifier: LGPL-2.1-or-later */ -/* - * Copyright (C) 2024, Paul Elder <paul.elder@ideasonboard.com> - * - * Vector and related operations - */ - -#include "vector.h" - -#include <libcamera/base/log.h> - -/** - * \file vector.h - * \brief Vector class - */ - -namespace libcamera { - -LOG_DEFINE_CATEGORY(Vector) - -namespace ipa { - -/** - * \class Vector - * \brief Vector class - * \tparam T Type of numerical values to be stored in the vector - * \tparam Rows Number of dimension of the vector (= number of elements) - */ - -/** - * \fn Vector::Vector() - * \brief Construct a zero vector - */ - -/** - * \fn Vector::Vector(const std::array<T, Rows> &data) - * \brief Construct vector from supplied data - * \param data Data from which to construct a vector - * - * The size of \a data must be equal to the dimension size Rows of the vector. - */ - -/** - * \fn T Vector::operator[](size_t i) const - * \brief Index to an element in the vector - * \param i Index of element to retrieve - * \return Element at index \a i from the vector - */ - -/** - * \fn T &Vector::operator[](size_t i) - * \copydoc Vector::operator[](size_t i) const - */ - -/** - * \fn Vector::x() - * \brief Convenience function to access the first element of the vector - * \return The first element of the vector - */ - -/** - * \fn Vector::y() - * \brief Convenience function to access the second element of the vector - * \return The second element of the vector - */ - -/** - * \fn Vector::z() - * \brief Convenience function to access the third element of the vector - * \return The third element of the vector - */ - -/** - * \fn Vector::operator-() const - * \brief Negate a Vector by negating both all of its coordinates - * \return The negated vector - */ - -/** - * \fn Vector::operator-(Vector const &other) const - * \brief Subtract one vector from another - * \param[in] other The other vector - * \return The difference of \a other from this vector - */ - -/** - * \fn Vector::operator+() - * \brief Add two vectors together - * \param[in] other The other vector - * \return The sum of the two vectors - */ - -/** - * \fn Vector::operator*(const Vector<T, Rows> &other) const - * \brief Compute the dot product - * \param[in] other The other vector - * \return The dot product of the two vectors - */ - -/** - * \fn Vector::operator*(T factor) const - * \brief Multiply the vector by a scalar - * \param[in] factor The factor - * \return The vector multiplied by \a factor - */ - -/** - * \fn Vector::operator/() - * \brief Divide the vector by a scalar - * \param[in] factor The factor - * \return The vector divided by \a factor - */ - -/** - * \fn Vector::length2() - * \brief Get the squared length of the vector - * \return The squared length of the vector - */ - -/** - * \fn Vector::length() - * \brief Get the length of the vector - * \return The length of the vector - */ - -/** - * \fn Vector<T, Rows> operator*(const Matrix<T, Rows, Cols> &m, const Vector<T, Cols> &v) - * \brief Multiply a matrix by a vector - * \tparam T Numerical type of the contents of the matrix and vector - * \tparam Rows The number of rows in the matrix - * \tparam Cols The number of columns in the matrix (= rows in the vector) - * \param m The matrix - * \param v The vector - * \return Product of matrix \a m and vector \a v - */ - -/** - * \fn bool operator==(const Vector<T, Rows> &lhs, const Vector<T, Rows> &rhs) - * \brief Compare vectors for equality - * \return True if the two vectors are equal, false otherwise - */ - -/** - * \fn bool operator!=(const Vector<T, Rows> &lhs, const Vector<T, Rows> &rhs) - * \brief Compare vectors for inequality - * \return True if the two vectors are not equal, false otherwise - */ - -#ifndef __DOXYGEN__ -bool vectorValidateYaml(const YamlObject &obj, unsigned int size) -{ - if (!obj.isList()) - return false; - - if (obj.size() != size) { - LOG(Vector, Error) - << "Wrong number of values in YAML vector: expected " - << size << ", got " << obj.size(); - return false; - } - - return true; -} -#endif /* __DOXYGEN__ */ - -} /* namespace ipa */ - -} /* namespace libcamera */ diff --git a/src/ipa/libipa/vector.h b/src/ipa/libipa/vector.h deleted file mode 100644 index 556e0967..00000000 --- a/src/ipa/libipa/vector.h +++ /dev/null @@ -1,219 +0,0 @@ -/* SPDX-License-Identifier: LGPL-2.1-or-later */ -/* - * Copyright (C) 2024, Paul Elder <paul.elder@ideasonboard.com> - * - * Vector and related operations - */ -#pragma once - -#include <algorithm> -#include <array> -#include <cmath> -#include <sstream> - -#include <libcamera/base/log.h> -#include <libcamera/base/span.h> - -#include "libcamera/internal/yaml_parser.h" - -#include "matrix.h" - -namespace libcamera { - -LOG_DECLARE_CATEGORY(Vector) - -namespace ipa { - -#ifndef __DOXYGEN__ -template<typename T, unsigned int Rows, - std::enable_if_t<std::is_arithmetic_v<T>> * = nullptr> -#else -template<typename T, unsigned int Rows> -#endif /* __DOXYGEN__ */ -class Vector -{ -public: - constexpr Vector() = default; - - constexpr Vector(const std::array<T, Rows> &data) - { - for (unsigned int i = 0; i < Rows; i++) - data_[i] = data[i]; - } - - const T &operator[](size_t i) const - { - ASSERT(i < data_.size()); - return data_[i]; - } - - T &operator[](size_t i) - { - ASSERT(i < data_.size()); - return data_[i]; - } - -#ifndef __DOXYGEN__ - template<bool Dependent = false, typename = std::enable_if_t<Dependent || Rows >= 1>> -#endif /* __DOXYGEN__ */ - constexpr T x() const - { - return data_[0]; - } - -#ifndef __DOXYGEN__ - template<bool Dependent = false, typename = std::enable_if_t<Dependent || Rows >= 2>> -#endif /* __DOXYGEN__ */ - constexpr T y() const - { - return data_[1]; - } - -#ifndef __DOXYGEN__ - template<bool Dependent = false, typename = std::enable_if_t<Dependent || Rows >= 3>> -#endif /* __DOXYGEN__ */ - constexpr T z() const - { - return data_[2]; - } - - constexpr Vector<T, Rows> operator-() const - { - Vector<T, Rows> ret; - for (unsigned int i = 0; i < Rows; i++) - ret[i] = -data_[i]; - return ret; - } - - constexpr Vector<T, Rows> operator-(const Vector<T, Rows> &other) const - { - Vector<T, Rows> ret; - for (unsigned int i = 0; i < Rows; i++) - ret[i] = data_[i] - other[i]; - return ret; - } - - constexpr Vector<T, Rows> operator+(const Vector<T, Rows> &other) const - { - Vector<T, Rows> ret; - for (unsigned int i = 0; i < Rows; i++) - ret[i] = data_[i] + other[i]; - return ret; - } - - constexpr T operator*(const Vector<T, Rows> &other) const - { - T ret = 0; - for (unsigned int i = 0; i < Rows; i++) - ret += data_[i] * other[i]; - return ret; - } - - constexpr Vector<T, Rows> operator*(T factor) const - { - Vector<T, Rows> ret; - for (unsigned int i = 0; i < Rows; i++) - ret[i] = data_[i] * factor; - return ret; - } - - constexpr Vector<T, Rows> operator/(T factor) const - { - Vector<T, Rows> ret; - for (unsigned int i = 0; i < Rows; i++) - ret[i] = data_[i] / factor; - return ret; - } - - constexpr double length2() const - { - double ret = 0; - for (unsigned int i = 0; i < Rows; i++) - ret += data_[i] * data_[i]; - return ret; - } - - constexpr double length() const - { - return std::sqrt(length2()); - } - -private: - std::array<T, Rows> data_; -}; - -template<typename T, unsigned int Rows, unsigned int Cols> -Vector<T, Rows> operator*(const Matrix<T, Rows, Cols> &m, const Vector<T, Cols> &v) -{ - Vector<T, Rows> result; - - for (unsigned int i = 0; i < Rows; i++) { - T sum = 0; - for (unsigned int j = 0; j < Cols; j++) - sum += m[i][j] * v[j]; - result[i] = sum; - } - - return result; -} - -template<typename T, unsigned int Rows> -bool operator==(const Vector<T, Rows> &lhs, const Vector<T, Rows> &rhs) -{ - for (unsigned int i = 0; i < Rows; i++) { - if (lhs[i] != rhs[i]) - return false; - } - - return true; -} - -template<typename T, unsigned int Rows> -bool operator!=(const Vector<T, Rows> &lhs, const Vector<T, Rows> &rhs) -{ - return !(lhs == rhs); -} - -#ifndef __DOXYGEN__ -bool vectorValidateYaml(const YamlObject &obj, unsigned int size); -#endif /* __DOXYGEN__ */ - -} /* namespace ipa */ - -#ifndef __DOXYGEN__ -template<typename T, unsigned int Rows> -std::ostream &operator<<(std::ostream &out, const ipa::Vector<T, Rows> &v) -{ - out << "Vector { "; - for (unsigned int i = 0; i < Rows; i++) { - out << v[i]; - out << ((i + 1 < Rows) ? ", " : " "); - } - out << " }"; - - return out; -} - -template<typename T, unsigned int Rows> -struct YamlObject::Getter<ipa::Vector<T, Rows>> { - std::optional<ipa::Vector<T, Rows>> get(const YamlObject &obj) const - { - if (!ipa::vectorValidateYaml(obj, Rows)) - return std::nullopt; - - ipa::Vector<T, Rows> vector; - - unsigned int i = 0; - for (const YamlObject &entry : obj.asList()) { - const auto value = entry.get<T>(); - if (!value) - return std::nullopt; - vector[i++] = *value; - } - - return vector; - } -}; -#endif /* __DOXYGEN__ */ - -} /* namespace libcamera */ |