pipeline: ipa: raspberrypi: Refactor and move the Raspberry Pi code

Split the Raspberry Pi pipeline handler and IPA source code into common
and VC4/BCM2835 specific file structures.

For the pipeline handler, the common code files now live in
src/libcamera/pipeline/rpi/common/
and the VC4-specific files in src/libcamera/pipeline/rpi/vc4/.

For the IPA, the common code files now live in
src/ipa/rpi/{cam_helper,controller}/
and the vc4 specific files in src/ipa/rpi/vc4/. With this change, the
camera tuning files are now installed under share/libcamera/ipa/rpi/vc4/.

To build the pipeline and IPA, the meson configuration options have now
changed from "raspberrypi" to "rpi/vc4":

meson setup build -Dipas=rpi/vc4 -Dpipelines=rpi/vc4

Signed-off-by: Naushir Patuck <naush@raspberrypi.com>
Reviewed-by: Jacopo Mondi <jacopo.mondi@ideasonboard.com>
Reviewed-by: Laurent Pinchart <laurent.pinchart@ideasonboard.com>
Signed-off-by: Laurent Pinchart <laurent.pinchart@ideasonboard.com>

src/ipa/rpi/controller/af_algorithm.h

@@ -0,0 +1,76 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2022, Raspberry Pi Ltd
+ *
+ * af_algorithm.hpp - auto focus algorithm interface
+ */
+#pragma once
+
+#include <optional>
+
+#include <libcamera/base/span.h>
+
+#include "algorithm.h"
+
+namespace RPiController {
+
+class AfAlgorithm : public Algorithm
+{
+public:
+	AfAlgorithm(Controller *controller)
+		: Algorithm(controller) {}
+
+	/*
+	 * An autofocus algorithm should provide the following calls.
+	 *
+	 * Where a ControlList combines a change of AfMode with other AF
+	 * controls, setMode() should be called first, to ensure the
+	 * algorithm will be in the correct state to handle controls.
+	 *
+	 * setLensPosition() returns true if the mode was AfModeManual and
+	 * the lens position has changed, otherwise returns false. When it
+	 * returns true, hwpos should be sent immediately to the lens driver.
+	 *
+	 * getMode() is provided mainly for validating controls.
+	 * getLensPosition() is provided for populating DeviceStatus.
+	 */
+
+	enum AfRange { AfRangeNormal = 0,
+		       AfRangeMacro,
+		       AfRangeFull,
+		       AfRangeMax };
+
+	enum AfSpeed { AfSpeedNormal = 0,
+		       AfSpeedFast,
+		       AfSpeedMax };
+
+	enum AfMode { AfModeManual = 0,
+		      AfModeAuto,
+		      AfModeContinuous };
+
+	enum AfPause { AfPauseImmediate = 0,
+		       AfPauseDeferred,
+		       AfPauseResume };
+
+	virtual void setRange([[maybe_unused]] AfRange range)
+	{
+	}
+	virtual void setSpeed([[maybe_unused]] AfSpeed speed)
+	{
+	}
+	virtual void setMetering([[maybe_unused]] bool use_windows)
+	{
+	}
+	virtual void setWindows([[maybe_unused]] libcamera::Span<libcamera::Rectangle const> const &wins)
+	{
+	}
+	virtual void setMode(AfMode mode) = 0;
+	virtual AfMode getMode() const = 0;
+	virtual bool setLensPosition(double dioptres, int32_t *hwpos) = 0;
+	virtual std::optional<double> getLensPosition() const = 0;
+	virtual void triggerScan() = 0;
+	virtual void cancelScan() = 0;
+	virtual void pause(AfPause pause) = 0;
+};
+
+} // namespace RPiController

src/ipa/rpi/controller/af_status.h

@@ -0,0 +1,35 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2022, Raspberry Pi Ltd
+ *
+ * af_status.h - AF control algorithm status
+ */
+#pragma once
+
+#include <optional>
+
+/*
+ * The AF algorithm should post the following structure into the image's
+ * "af.status" metadata. lensSetting should control the lens.
+ */
+
+enum class AfState {
+	Idle = 0,
+	Scanning,
+	Focused,
+	Failed
+};
+
+enum class AfPauseState {
+	Running = 0,
+	Pausing,
+	Paused
+};
+
+struct AfStatus {
+	/* state for reporting */
+	AfState state;
+	AfPauseState pauseState;
+	/* lensSetting should be sent to the lens driver, when valid */
+	std::optional<int> lensSetting;
+};

src/ipa/rpi/controller/agc_algorithm.h

@@ -0,0 +1,33 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2019, Raspberry Pi Ltd
+ *
+ * agc_algorithm.h - AGC/AEC control algorithm interface
+ */
+#pragma once
+
+#include <libcamera/base/utils.h>
+
+#include "algorithm.h"
+
+namespace RPiController {
+
+class AgcAlgorithm : public Algorithm
+{
+public:
+	AgcAlgorithm(Controller *controller) : Algorithm(controller) {}
+	/* An AGC algorithm must provide the following: */
+	virtual unsigned int getConvergenceFrames() const = 0;
+	virtual void setEv(double ev) = 0;
+	virtual void setFlickerPeriod(libcamera::utils::Duration flickerPeriod) = 0;
+	virtual void setFixedShutter(libcamera::utils::Duration fixedShutter) = 0;
+	virtual void setMaxShutter(libcamera::utils::Duration maxShutter) = 0;
+	virtual void setFixedAnalogueGain(double fixedAnalogueGain) = 0;
+	virtual void setMeteringMode(std::string const &meteringModeName) = 0;
+	virtual void setExposureMode(std::string const &exposureModeName) = 0;
+	virtual void setConstraintMode(std::string const &contraintModeName) = 0;
+	virtual void enableAuto() = 0;
+	virtual void disableAuto() = 0;
+};
+
+} /* namespace RPiController */

src/ipa/rpi/controller/agc_status.h

@@ -0,0 +1,37 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2019, Raspberry Pi Ltd
+ *
+ * agc_status.h - AGC/AEC control algorithm status
+ */
+#pragma once
+
+#include <libcamera/base/utils.h>
+
+/*
+ * The AGC algorithm should post the following structure into the image's
+ * "agc.status" metadata.
+ */
+
+/*
+ * Note: total_exposure_value will be reported as zero until the algorithm has
+ * seen statistics and calculated meaningful values. The contents should be
+ * ignored until then.
+ */
+
+struct AgcStatus {
+	libcamera::utils::Duration totalExposureValue; /* value for all exposure and gain for this image */
+	libcamera::utils::Duration targetExposureValue; /* (unfiltered) target total exposure AGC is aiming for */
+	libcamera::utils::Duration shutterTime;
+	double analogueGain;
+	char exposureMode[32];
+	char constraintMode[32];
+	char meteringMode[32];
+	double ev;
+	libcamera::utils::Duration flickerPeriod;
+	int floatingRegionEnable;
+	libcamera::utils::Duration fixedShutter;
+	double fixedAnalogueGain;
+	double digitalGain;
+	int locked;
+};

src/ipa/rpi/controller/algorithm.cpp

@@ -0,0 +1,56 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2019, Raspberry Pi Ltd
+ *
+ * algorithm.cpp - ISP control algorithms
+ */
+
+#include "algorithm.h"
+
+using namespace RPiController;
+
+int Algorithm::read([[maybe_unused]] const libcamera::YamlObject &params)
+{
+	return 0;
+}
+
+void Algorithm::initialise()
+{
+}
+
+void Algorithm::switchMode([[maybe_unused]] CameraMode const &cameraMode,
+			   [[maybe_unused]] Metadata *metadata)
+{
+}
+
+void Algorithm::prepare([[maybe_unused]] Metadata *imageMetadata)
+{
+}
+
+void Algorithm::process([[maybe_unused]] StatisticsPtr &stats,
+			[[maybe_unused]] Metadata *imageMetadata)
+{
+}
+
+/* For registering algorithms with the system: */
+
+namespace {
+
+std::map<std::string, AlgoCreateFunc> &algorithms()
+{
+	static std::map<std::string, AlgoCreateFunc> algorithms;
+	return algorithms;
+}
+
+} /* namespace */
+
+std::map<std::string, AlgoCreateFunc> const &RPiController::getAlgorithms()
+{
+	return algorithms();
+}
+
+RegisterAlgorithm::RegisterAlgorithm(char const *name,
+				     AlgoCreateFunc createFunc)
+{
+	algorithms()[std::string(name)] = createFunc;
+}

src/ipa/rpi/controller/algorithm.h

@@ -0,0 +1,68 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2019, Raspberry Pi Ltd
+ *
+ * algorithm.h - ISP control algorithm interface
+ */
+#pragma once
+
+/*
+ * All algorithms should be derived from this class and made available to the
+ * Controller.
+ */
+
+#include <string>
+#include <memory>
+#include <map>
+
+#include "libcamera/internal/yaml_parser.h"
+
+#include "controller.h"
+
+namespace RPiController {
+
+/* This defines the basic interface for all control algorithms. */
+
+class Algorithm
+{
+public:
+	Algorithm(Controller *controller)
+		: controller_(controller)
+	{
+	}
+	virtual ~Algorithm() = default;
+	virtual char const *name() const = 0;
+	virtual int read(const libcamera::YamlObject &params);
+	virtual void initialise();
+	virtual void switchMode(CameraMode const &cameraMode, Metadata *metadata);
+	virtual void prepare(Metadata *imageMetadata);
+	virtual void process(StatisticsPtr &stats, Metadata *imageMetadata);
+	Metadata &getGlobalMetadata() const
+	{
+		return controller_->getGlobalMetadata();
+	}
+	const std::string &getTarget() const
+	{
+		return controller_->getTarget();
+	}
+	const Controller::HardwareConfig &getHardwareConfig() const
+	{
+		return controller_->getHardwareConfig();
+	}
+
+private:
+	Controller *controller_;
+};
+
+/*
+ * This code is for automatic registration of Front End algorithms with the
+ * system.
+ */
+
+typedef Algorithm *(*AlgoCreateFunc)(Controller *controller);
+struct RegisterAlgorithm {
+	RegisterAlgorithm(char const *name, AlgoCreateFunc createFunc);
+};
+std::map<std::string, AlgoCreateFunc> const &getAlgorithms();
+
+} /* namespace RPiController */

src/ipa/rpi/controller/alsc_status.h

@@ -0,0 +1,22 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2019, Raspberry Pi Ltd
+ *
+ * alsc_status.h - ALSC (auto lens shading correction) control algorithm status
+ */
+#pragma once
+
+#include <vector>
+
+/*
+ * The ALSC algorithm should post the following structure into the image's
+ * "alsc.status" metadata.
+ */
+
+struct AlscStatus {
+	std::vector<double> r;
+	std::vector<double> g;
+	std::vector<double> b;
+	unsigned int rows;
+	unsigned int cols;
+};

src/ipa/rpi/controller/awb_algorithm.h

@@ -0,0 +1,25 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2019, Raspberry Pi Ltd
+ *
+ * awb_algorithm.h - AWB control algorithm interface
+ */
+#pragma once
+
+#include "algorithm.h"
+
+namespace RPiController {
+
+class AwbAlgorithm : public Algorithm
+{
+public:
+	AwbAlgorithm(Controller *controller) : Algorithm(controller) {}
+	/* An AWB algorithm must provide the following: */
+	virtual unsigned int getConvergenceFrames() const = 0;
+	virtual void setMode(std::string const &modeName) = 0;
+	virtual void setManualGains(double manualR, double manualB) = 0;
+	virtual void enableAuto() = 0;
+	virtual void disableAuto() = 0;
+};
+
+} /* namespace RPiController */

src/ipa/rpi/controller/awb_status.h

@@ -0,0 +1,20 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2019, Raspberry Pi Ltd
+ *
+ * awb_status.h - AWB control algorithm status
+ */
+#pragma once
+
+/*
+ * The AWB algorithm places its results into both the image and global metadata,
+ * under the tag "awb.status".
+ */
+
+struct AwbStatus {
+	char mode[32];
+	double temperatureK;
+	double gainR;
+	double gainG;
+	double gainB;
+};

src/ipa/rpi/controller/black_level_status.h

@@ -0,0 +1,15 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2019, Raspberry Pi Ltd
+ *
+ * black_level_status.h - black level control algorithm status
+ */
+#pragma once
+
+/* The "black level" algorithm stores the black levels to use. */
+
+struct BlackLevelStatus {
+	uint16_t blackLevelR; /* out of 16 bits */
+	uint16_t blackLevelG;
+	uint16_t blackLevelB;
+};

src/ipa/rpi/controller/camera_mode.h

@@ -0,0 +1,59 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2019-2020, Raspberry Pi Ltd
+ *
+ * camera_mode.h - description of a particular operating mode of a sensor
+ */
+#pragma once
+
+#include <libcamera/transform.h>
+
+#include <libcamera/base/utils.h>
+
+/*
+ * Description of a "camera mode", holding enough information for control
+ * algorithms to adapt their behaviour to the different modes of the camera,
+ * including binning, scaling, cropping etc.
+ */
+
+struct CameraMode {
+	/* bit depth of the raw camera output */
+	uint32_t bitdepth;
+	/* size in pixels of frames in this mode */
+	uint16_t width;
+	uint16_t height;
+	/* size of full resolution uncropped frame ("sensor frame") */
+	uint16_t sensorWidth;
+	uint16_t sensorHeight;
+	/* binning factor (1 = no binning, 2 = 2-pixel binning etc.) */
+	uint8_t binX;
+	uint8_t binY;
+	/* location of top left pixel in the sensor frame */
+	uint16_t cropX;
+	uint16_t cropY;
+	/* scaling factor (so if uncropped, width*scaleX is sensorWidth) */
+	double scaleX;
+	double scaleY;
+	/* scaling of the noise compared to the native sensor mode */
+	double noiseFactor;
+	/* minimum and maximum line time and frame durations */
+	libcamera::utils::Duration minLineLength;
+	libcamera::utils::Duration maxLineLength;
+	libcamera::utils::Duration minFrameDuration;
+	libcamera::utils::Duration maxFrameDuration;
+	/* any camera transform *not* reflected already in the camera tuning */
+	libcamera::Transform transform;
+	/* minimum and maximum frame lengths in units of lines */
+	uint32_t minFrameLength;
+	uint32_t maxFrameLength;
+	/* sensitivity of this mode */
+	double sensitivity;
+	/* pixel clock rate */
+	uint64_t pixelRate;
+	/* Mode specific shutter speed limits */
+	libcamera::utils::Duration minShutter;
+	libcamera::utils::Duration maxShutter;
+	/* Mode specific analogue gain limits */
+	double minAnalogueGain;
+	double maxAnalogueGain;
+};

src/ipa/rpi/controller/ccm_algorithm.h

@@ -0,0 +1,21 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2019, Raspberry Pi Ltd
+ *
+ * ccm_algorithm.h - CCM (colour correction matrix) control algorithm interface
+ */
+#pragma once
+
+#include "algorithm.h"
+
+namespace RPiController {
+
+class CcmAlgorithm : public Algorithm
+{
+public:
+	CcmAlgorithm(Controller *controller) : Algorithm(controller) {}
+	/* A CCM algorithm must provide the following: */
+	virtual void setSaturation(double saturation) = 0;
+};
+
+} /* namespace RPiController */

src/ipa/rpi/controller/ccm_status.h

@@ -0,0 +1,14 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2019, Raspberry Pi Ltd
+ *
+ * ccm_status.h - CCM (colour correction matrix) control algorithm status
+ */
+#pragma once
+
+/* The "ccm" algorithm generates an appropriate colour matrix. */
+
+struct CcmStatus {
+	double matrix[9];
+	double saturation;
+};

src/ipa/rpi/controller/contrast_algorithm.h

@@ -0,0 +1,22 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2019, Raspberry Pi Ltd
+ *
+ * contrast_algorithm.h - contrast (gamma) control algorithm interface
+ */
+#pragma once
+
+#include "algorithm.h"
+
+namespace RPiController {
+
+class ContrastAlgorithm : public Algorithm
+{
+public:
+	ContrastAlgorithm(Controller *controller) : Algorithm(controller) {}
+	/* A contrast algorithm must provide the following: */
+	virtual void setBrightness(double brightness) = 0;
+	virtual void setContrast(double contrast) = 0;
+};
+
+} /* namespace RPiController */

src/ipa/rpi/controller/contrast_status.h

@@ -0,0 +1,20 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2019, Raspberry Pi Ltd
+ *
+ * contrast_status.h - contrast (gamma) control algorithm status
+ */
+#pragma once
+
+#include "pwl.h"
+
+/*
+ * The "contrast" algorithm creates a gamma curve, optionally doing a little bit
+ * of contrast stretching based on the AGC histogram.
+ */
+
+struct ContrastStatus {
+	RPiController::Pwl gammaCurve;
+	double brightness;
+	double contrast;
+};

src/ipa/rpi/controller/controller.cpp

@@ -0,0 +1,181 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2019, Raspberry Pi Ltd
+ *
+ * controller.cpp - ISP controller
+ */
+
+#include <assert.h>
+
+#include <libcamera/base/file.h>
+#include <libcamera/base/log.h>
+
+#include "libcamera/internal/yaml_parser.h"
+
+#include "algorithm.h"
+#include "controller.h"
+
+using namespace RPiController;
+using namespace libcamera;
+
+LOG_DEFINE_CATEGORY(RPiController)
+
+static const std::map<std::string, Controller::HardwareConfig> HardwareConfigMap = {
+	{
+		"bcm2835",
+		{
+			/*
+			 * There are only ever 15 AGC regions computed by the firmware
+			 * due to zoning, but the HW defines AGC_REGIONS == 16!
+			 */
+			.agcRegions = { 15 , 1 },
+			.agcZoneWeights = { 15 , 1 },
+			.awbRegions = { 16, 12 },
+			.focusRegions = { 4, 3 },
+			.numHistogramBins = 128,
+			.numGammaPoints = 33,
+			.pipelineWidth = 13
+		}
+	},
+};
+
+Controller::Controller()
+	: switchModeCalled_(false)
+{
+}
+
+Controller::~Controller() {}
+
+int Controller::read(char const *filename)
+{
+	File file(filename);
+	if (!file.open(File::OpenModeFlag::ReadOnly)) {
+		LOG(RPiController, Warning)
+			<< "Failed to open tuning file '" << filename << "'";
+		return -EINVAL;
+	}
+
+	std::unique_ptr<YamlObject> root = YamlParser::parse(file);
+	double version = (*root)["version"].get<double>(1.0);
+	target_ = (*root)["target"].get<std::string>("bcm2835");
+
+	if (version < 2.0) {
+		LOG(RPiController, Warning)
+			<< "This format of the tuning file will be deprecated soon!"
+			<< " Please use the convert_tuning.py utility to update to version 2.0.";
+
+		for (auto const &[key, value] : root->asDict()) {
+			int ret = createAlgorithm(key, value);
+			if (ret)
+				return ret;
+		}
+	} else if (version < 3.0) {
+		if (!root->contains("algorithms")) {
+			LOG(RPiController, Error)
+				<< "Tuning file " << filename
+				<< " does not have an \"algorithms\" list!";
+			return -EINVAL;
+		}
+
+		for (auto const &rootAlgo : (*root)["algorithms"].asList())
+			for (auto const &[key, value] : rootAlgo.asDict()) {
+				int ret = createAlgorithm(key, value);
+				if (ret)
+					return ret;
+			}
+	} else {
+		LOG(RPiController, Error)
+			<< "Unrecognised version " << version
+			<< " for the tuning file " << filename;
+		return -EINVAL;
+	}
+
+	return 0;
+}
+
+int Controller::createAlgorithm(const std::string &name, const YamlObject &params)
+{
+	auto it = getAlgorithms().find(name);
+	if (it == getAlgorithms().end()) {
+		LOG(RPiController, Warning)
+			<< "No algorithm found for \"" << name << "\"";
+		return 0;
+	}
+
+	Algorithm *algo = (*it->second)(this);
+	int ret = algo->read(params);
+	if (ret)
+		return ret;
+
+	algorithms_.push_back(AlgorithmPtr(algo));
+	return 0;
+}
+
+void Controller::initialise()
+{
+	for (auto &algo : algorithms_)
+		algo->initialise();
+}
+
+void Controller::switchMode(CameraMode const &cameraMode, Metadata *metadata)
+{
+	for (auto &algo : algorithms_)
+		algo->switchMode(cameraMode, metadata);
+	switchModeCalled_ = true;
+}
+
+void Controller::prepare(Metadata *imageMetadata)
+{
+	assert(switchModeCalled_);
+	for (auto &algo : algorithms_)
+		algo->prepare(imageMetadata);
+}
+
+void Controller::process(StatisticsPtr stats, Metadata *imageMetadata)
+{
+	assert(switchModeCalled_);
+	for (auto &algo : algorithms_)
+		algo->process(stats, imageMetadata);
+}
+
+Metadata &Controller::getGlobalMetadata()
+{
+	return globalMetadata_;
+}
+
+Algorithm *Controller::getAlgorithm(std::string const &name) const
+{
+	/*
+	 * The passed name must be the entire algorithm name, or must match the
+	 * last part of it with a period (.) just before.
+	 */
+	size_t nameLen = name.length();
+	for (auto &algo : algorithms_) {
+		char const *algoName = algo->name();
+		size_t algoNameLen = strlen(algoName);
+		if (algoNameLen >= nameLen &&
+		    strcasecmp(name.c_str(),
+			       algoName + algoNameLen - nameLen) == 0 &&
+		    (nameLen == algoNameLen ||
+		     algoName[algoNameLen - nameLen - 1] == '.'))
+			return algo.get();
+	}
+	return nullptr;
+}
+
+const std::string &Controller::getTarget() const
+{
+	return target_;
+}
+
+const Controller::HardwareConfig &Controller::getHardwareConfig() const
+{
+	auto cfg = HardwareConfigMap.find(getTarget());
+
+	/*
+	 * This really should not happen, the IPA ought to validate the target
+	 * on initialisation.
+	 */
+	ASSERT(cfg != HardwareConfigMap.end());
+	return cfg->second;
+}

src/ipa/rpi/controller/controller.h

@@ -0,0 +1,73 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2019, Raspberry Pi Ltd
+ *
+ * controller.h - ISP controller interface
+ */
+#pragma once
+
+/*
+ * The Controller is simply a container for a collecting together a number of
+ * "control algorithms" (such as AWB etc.) and for running them all in a
+ * convenient manner.
+ */
+
+#include <vector>
+#include <string>
+
+#include "libcamera/internal/yaml_parser.h"
+
+#include "camera_mode.h"
+#include "device_status.h"
+#include "metadata.h"
+#include "statistics.h"
+
+namespace RPiController {
+
+class Algorithm;
+typedef std::unique_ptr<Algorithm> AlgorithmPtr;
+
+/*
+ * The Controller holds a pointer to some global_metadata, which is how
+ * different controllers and control algorithms within them can exchange
+ * information. The Prepare function returns a pointer to metadata for this
+ * specific image, and which should be passed on to the Process function.
+ */
+
+class Controller
+{
+public:
+	struct HardwareConfig {
+		libcamera::Size agcRegions;
+		libcamera::Size agcZoneWeights;
+		libcamera::Size awbRegions;
+		libcamera::Size focusRegions;
+		unsigned int numHistogramBins;
+		unsigned int numGammaPoints;
+		unsigned int pipelineWidth;
+	};
+
+	Controller();
+	~Controller();
+	int read(char const *filename);
+	void initialise();
+	void switchMode(CameraMode const &cameraMode, Metadata *metadata);
+	void prepare(Metadata *imageMetadata);
+	void process(StatisticsPtr stats, Metadata *imageMetadata);
+	Metadata &getGlobalMetadata();
+	Algorithm *getAlgorithm(std::string const &name) const;
+	const std::string &getTarget() const;
+	const HardwareConfig &getHardwareConfig() const;
+
+protected:
+	int createAlgorithm(const std::string &name, const libcamera::YamlObject &params);
+
+	Metadata globalMetadata_;
+	std::vector<AlgorithmPtr> algorithms_;
+	bool switchModeCalled_;
+
+private:
+	std::string target_;
+};
+
+} /* namespace RPiController */

src/ipa/rpi/controller/denoise_algorithm.h

@@ -0,0 +1,23 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2021, Raspberry Pi Ltd
+ *
+ * denoise.h - Denoise control algorithm interface
+ */
+#pragma once
+
+#include "algorithm.h"
+
+namespace RPiController {
+
+enum class DenoiseMode { Off, ColourOff, ColourFast, ColourHighQuality };
+
+class DenoiseAlgorithm : public Algorithm
+{
+public:
+	DenoiseAlgorithm(Controller *controller) : Algorithm(controller) {}
+	/* A Denoise algorithm must provide the following: */
+	virtual void setMode(DenoiseMode mode) = 0;
+};
+
+} /* namespace RPiController */

src/ipa/rpi/controller/denoise_status.h

@@ -0,0 +1,16 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2019-2021, Raspberry Pi Ltd
+ *
+ * denoise_status.h - Denoise control algorithm status
+ */
+#pragma once
+
+/* This stores the parameters required for Denoise. */
+
+struct DenoiseStatus {
+	double noiseConstant;
+	double noiseSlope;
+	double strength;
+	unsigned int mode;
+};

src/ipa/rpi/controller/device_status.cpp

@@ -0,0 +1,31 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2021, Raspberry Pi Ltd
+ *
+ * device_status.cpp - device (image sensor) status
+ */
+#include "device_status.h"
+
+using namespace libcamera; /* for the Duration operator<< overload */
+
+std::ostream &operator<<(std::ostream &out, const DeviceStatus &d)
+{
+	out << "Exposure: " << d.shutterSpeed
+	    << " Frame length: " << d.frameLength
+	    << " Line length: " << d.lineLength
+	    << " Gain: " << d.analogueGain;
+
+	if (d.aperture)
+		out << " Aperture: " << *d.aperture;
+
+	if (d.lensPosition)
+		out << " Lens: " << *d.lensPosition;
+
+	if (d.flashIntensity)
+		out << " Flash: " << *d.flashIntensity;
+
+	if (d.sensorTemperature)
+		out << " Temperature: " << *d.sensorTemperature;
+
+	return out;
+}

src/ipa/rpi/controller/device_status.h

@@ -0,0 +1,43 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2019-2021, Raspberry Pi Ltd
+ *
+ * device_status.h - device (image sensor) status
+ */
+#pragma once
+
+#include <iostream>
+#include <optional>
+
+#include <libcamera/base/utils.h>
+
+/*
+ * Definition of "device metadata" which stores things like shutter time and
+ * analogue gain that downstream control algorithms will want to know.
+ */
+
+struct DeviceStatus {
+	DeviceStatus()
+		: shutterSpeed(std::chrono::seconds(0)), frameLength(0),
+		  lineLength(std::chrono::seconds(0)), analogueGain(0.0)
+	{
+	}
+
+	friend std::ostream &operator<<(std::ostream &out, const DeviceStatus &d);
+
+	/* time shutter is open */
+	libcamera::utils::Duration shutterSpeed;
+	/* frame length given in number of lines */
+	uint32_t frameLength;
+	/* line length for the current frame */
+	libcamera::utils::Duration lineLength;
+	double analogueGain;
+	/* 1.0/distance-in-metres */
+	std::optional<double> lensPosition;
+	/* 1/f so that brightness quadruples when this doubles */
+	std::optional<double> aperture;
+	/* proportional to brightness with 0 = no flash, 1 = maximum flash */
+	std::optional<double> flashIntensity;
+	/* Sensor reported temperature value (in degrees) */
+	std::optional<double> sensorTemperature;
+};

src/ipa/rpi/controller/dpc_status.h

@@ -0,0 +1,13 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2019, Raspberry Pi Ltd
+ *
+ * dpc_status.h - DPC (defective pixel correction) control algorithm status
+ */
+#pragma once
+
+/* The "DPC" algorithm sets defective pixel correction strength. */
+
+struct DpcStatus {
+	int strength; /* 0 = "off", 1 = "normal", 2 = "strong" */
+};

src/ipa/rpi/controller/geq_status.h

@@ -0,0 +1,14 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2019, Raspberry Pi Ltd
+ *
+ * geq_status.h - GEQ (green equalisation) control algorithm status
+ */
+#pragma once
+
+/* The "GEQ" algorithm calculates the green equalisation thresholds */
+
+struct GeqStatus {
+	uint16_t offset;
+	double slope;
+};

src/ipa/rpi/controller/histogram.cpp

@@ -0,0 +1,64 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2019, Raspberry Pi Ltd
+ *
+ * histogram.cpp - histogram calculations
+ */
+#include <math.h>
+#include <stdio.h>
+
+#include "histogram.h"
+
+using namespace RPiController;
+
+uint64_t Histogram::cumulativeFreq(double bin) const
+{
+	if (bin <= 0)
+		return 0;
+	else if (bin >= bins())
+		return total();
+	int b = (int)bin;
+	return cumulative_[b] +
+	       (bin - b) * (cumulative_[b + 1] - cumulative_[b]);
+}
+
+double Histogram::quantile(double q, int first, int last) const
+{
+	if (first == -1)
+		first = 0;
+	if (last == -1)
+		last = cumulative_.size() - 2;
+	assert(first <= last);
+	uint64_t items = q * total();
+	while (first < last) /* binary search to find the right bin */
+	{
+		int middle = (first + last) / 2;
+		if (cumulative_[middle + 1] > items)
+			last = middle; /* between first and middle */
+		else
+			first = middle + 1; /* after middle */
+	}
+	assert(items >= cumulative_[first] && items <= cumulative_[last + 1]);
+	double frac = cumulative_[first + 1] == cumulative_[first] ? 0
+		      : (double)(items - cumulative_[first]) /
+				  (cumulative_[first + 1] - cumulative_[first]);
+	return first + frac;
+}
+
+double Histogram::interQuantileMean(double qLo, double qHi) const
+{
+	assert(qHi > qLo);
+	double pLo = quantile(qLo);
+	double pHi = quantile(qHi, (int)pLo);
+	double sumBinFreq = 0, cumulFreq = 0;
+	for (double pNext = floor(pLo) + 1.0; pNext <= ceil(pHi);
+	     pLo = pNext, pNext += 1.0) {
+		int bin = floor(pLo);
+		double freq = (cumulative_[bin + 1] - cumulative_[bin]) *
+			      (std::min(pNext, pHi) - pLo);
+		sumBinFreq += bin * freq;
+		cumulFreq += freq;
+	}
+	/* add 0.5 to give an average for bin mid-points */
+	return sumBinFreq / cumulFreq + 0.5;
+}

src/ipa/rpi/controller/histogram.h

@@ -0,0 +1,53 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2019, Raspberry Pi Ltd
+ *
+ * histogram.h - histogram calculation interface
+ */
+#pragma once
+
+#include <stdint.h>
+#include <vector>
+#include <cassert>
+
+/*
+ * A simple histogram class, for use in particular to find "quantiles" and
+ * averages between "quantiles".
+ */
+
+namespace RPiController {
+
+class Histogram
+{
+public:
+	Histogram()
+	{
+		cumulative_.push_back(0);
+	}
+
+	template<typename T> Histogram(T *histogram, int num)
+	{
+		assert(num);
+		cumulative_.reserve(num + 1);
+		cumulative_.push_back(0);
+		for (int i = 0; i < num; i++)
+			cumulative_.push_back(cumulative_.back() +
+					      histogram[i]);
+	}
+	uint32_t bins() const { return cumulative_.size() - 1; }
+	uint64_t total() const { return cumulative_[cumulative_.size() - 1]; }
+	/* Cumulative frequency up to a (fractional) point in a bin. */
+	uint64_t cumulativeFreq(double bin) const;
+	/*
+	 * Return the (fractional) bin of the point q (0 <= q <= 1) through the
+	 * histogram. Optionally provide limits to help.
+	 */
+	double quantile(double q, int first = -1, int last = -1) const;
+	/* Return the average histogram bin value between the two quantiles. */
+	double interQuantileMean(double qLo, double qHi) const;
+
+private:
+	std::vector<uint64_t> cumulative_;
+};
+
+} /* namespace RPiController */

src/ipa/rpi/controller/lux_status.h

@@ -0,0 +1,23 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2019, Raspberry Pi Ltd
+ *
+ * lux_status.h - Lux control algorithm status
+ */
+#pragma once
+
+/*
+ * The "lux" algorithm looks at the (AGC) histogram statistics of the frame and
+ * estimates the current lux level of the scene. It does this by a simple ratio
+ * calculation comparing to a reference image that was taken in known conditions
+ * with known statistics and a properly measured lux level. There is a slight
+ * problem with aperture, in that it may be variable without the system knowing
+ * or being aware of it. In this case an external application may set a
+ * "current_aperture" value if it wishes, which would be used in place of the
+ * (presumably meaningless) value in the image metadata.
+ */
+
+struct LuxStatus {
+	double lux;
+	double aperture;
+};

src/ipa/rpi/controller/meson.build

@@ -0,0 +1,29 @@
+# SPDX-License-Identifier: CC0-1.0
+
+rpi_ipa_controller_sources = files([
+    'algorithm.cpp',
+    'controller.cpp',
+    'device_status.cpp',
+    'histogram.cpp',
+    'pwl.cpp',
+    'rpi/af.cpp',
+    'rpi/agc.cpp',
+    'rpi/alsc.cpp',
+    'rpi/awb.cpp',
+    'rpi/black_level.cpp',
+    'rpi/ccm.cpp',
+    'rpi/contrast.cpp',
+    'rpi/dpc.cpp',
+    'rpi/geq.cpp',
+    'rpi/lux.cpp',
+    'rpi/noise.cpp',
+    'rpi/sdn.cpp',
+    'rpi/sharpen.cpp',
+])
+
+rpi_ipa_controller_deps = [
+    libcamera_private,
+]
+
+rpi_ipa_controller_lib = static_library('rpi_ipa_controller', rpi_ipa_controller_sources,
+                                        dependencies : rpi_ipa_controller_deps)

src/ipa/rpi/controller/metadata.h

@@ -0,0 +1,126 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2019-2021, Raspberry Pi Ltd
+ *
+ * metadata.h - general metadata class
+ */
+#pragma once
+
+/* A simple class for carrying arbitrary metadata, for example about an image. */
+
+#include <any>
+#include <map>
+#include <mutex>
+#include <string>
+
+#include <libcamera/base/thread_annotations.h>
+
+namespace RPiController {
+
+class LIBCAMERA_TSA_CAPABILITY("mutex") Metadata
+{
+public:
+	Metadata() = default;
+
+	Metadata(Metadata const &other)
+	{
+		std::scoped_lock otherLock(other.mutex_);
+		data_ = other.data_;
+	}
+
+	Metadata(Metadata &&other)
+	{
+		std::scoped_lock otherLock(other.mutex_);
+		data_ = std::move(other.data_);
+		other.data_.clear();
+	}
+
+	template<typename T>
+	void set(std::string const &tag, T const &value)
+	{
+		std::scoped_lock lock(mutex_);
+		data_[tag] = value;
+	}
+
+	template<typename T>
+	int get(std::string const &tag, T &value) const
+	{
+		std::scoped_lock lock(mutex_);
+		auto it = data_.find(tag);
+		if (it == data_.end())
+			return -1;
+		value = std::any_cast<T>(it->second);
+		return 0;
+	}
+
+	void clear()
+	{
+		std::scoped_lock lock(mutex_);
+		data_.clear();
+	}
+
+	Metadata &operator=(Metadata const &other)
+	{
+		std::scoped_lock lock(mutex_, other.mutex_);
+		data_ = other.data_;
+		return *this;
+	}
+
+	Metadata &operator=(Metadata &&other)
+	{
+		std::scoped_lock lock(mutex_, other.mutex_);
+		data_ = std::move(other.data_);
+		other.data_.clear();
+		return *this;
+	}
+
+	void merge(Metadata &other)
+	{
+		std::scoped_lock lock(mutex_, other.mutex_);
+		data_.merge(other.data_);
+	}
+
+	void mergeCopy(const Metadata &other)
+	{
+		std::scoped_lock lock(mutex_, other.mutex_);
+		/*
+		 * If the metadata key exists, ignore this item and copy only
+		 * unique key/value pairs.
+		 */
+		data_.insert(other.data_.begin(), other.data_.end());
+	}
+
+	template<typename T>
+	T *getLocked(std::string const &tag)
+	{
+		/*
+		 * This allows in-place access to the Metadata contents,
+		 * for which you should be holding the lock.
+		 */
+		auto it = data_.find(tag);
+		if (it == data_.end())
+			return nullptr;
+		return std::any_cast<T>(&it->second);
+	}
+
+	template<typename T>
+	void setLocked(std::string const &tag, T const &value)
+	{
+		/* Use this only if you're holding the lock yourself. */
+		data_[tag] = value;
+	}
+
+	/*
+	 * Note: use of (lowercase) lock and unlock means you can create scoped
+	 * locks with the standard lock classes.
+	 * e.g. std::lock_guard<RPiController::Metadata> lock(metadata)
+	 */
+	void lock() LIBCAMERA_TSA_ACQUIRE() { mutex_.lock(); }
+	void unlock() LIBCAMERA_TSA_RELEASE() { mutex_.unlock(); }
+
+private:
+	mutable std::mutex mutex_;
+	std::map<std::string, std::any> data_;
+};
+
+} /* namespace RPiController */

src/ipa/rpi/controller/noise_status.h

@@ -0,0 +1,14 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2019, Raspberry Pi Ltd
+ *
+ * noise_status.h - Noise control algorithm status
+ */
+#pragma once
+
+/* The "noise" algorithm stores an estimate of the noise profile for this image. */
+
+struct NoiseStatus {
+	double noiseConstant;
+	double noiseSlope;
+};

src/ipa/rpi/controller/pdaf_data.h

@@ -0,0 +1,24 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2022, Raspberry Pi Ltd
+ *
+ * pdaf_data.h - PDAF Metadata
+ */
+#pragma once
+
+#include <stdint.h>
+
+#include "region_stats.h"
+
+namespace RPiController {
+
+struct PdafData {
+	/* Confidence, in arbitrary units */
+	uint16_t conf;
+	/* Phase error, in s16 Q4 format (S.11.4) */
+	int16_t phase;
+};
+
+using PdafRegions = RegionStats<PdafData>;
+
+} /* namespace RPiController */

src/ipa/rpi/controller/pwl.cpp

@@ -0,0 +1,269 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2019, Raspberry Pi Ltd
+ *
+ * pwl.cpp - piecewise linear functions
+ */
+
+#include <cassert>
+#include <cmath>
+#include <stdexcept>
+
+#include "pwl.h"
+
+using namespace RPiController;
+
+int Pwl::read(const libcamera::YamlObject &params)
+{
+	if (!params.size() || params.size() % 2)
+		return -EINVAL;
+
+	const auto &list = params.asList();
+
+	for (auto it = list.begin(); it != list.end(); it++) {
+		auto x = it->get<double>();
+		if (!x)
+			return -EINVAL;
+		if (it != list.begin() && *x <= points_.back().x)
+			return -EINVAL;
+
+		auto y = (++it)->get<double>();
+		if (!y)
+			return -EINVAL;
+
+		points_.push_back(Point(*x, *y));
+	}
+
+	return 0;
+}
+
+void Pwl::append(double x, double y, const double eps)
+{
+	if (points_.empty() || points_.back().x + eps < x)
+		points_.push_back(Point(x, y));
+}
+
+void Pwl::prepend(double x, double y, const double eps)
+{
+	if (points_.empty() || points_.front().x - eps > x)
+		points_.insert(points_.begin(), Point(x, y));
+}
+
+Pwl::Interval Pwl::domain() const
+{
+	return Interval(points_[0].x, points_[points_.size() - 1].x);
+}
+
+Pwl::Interval Pwl::range() const
+{
+	double lo = points_[0].y, hi = lo;
+	for (auto &p : points_)
+		lo = std::min(lo, p.y), hi = std::max(hi, p.y);
+	return Interval(lo, hi);
+}
+
+bool Pwl::empty() const
+{
+	return points_.empty();
+}
+
+double Pwl::eval(double x, int *spanPtr, bool updateSpan) const
+{
+	int span = findSpan(x, spanPtr && *spanPtr != -1 ? *spanPtr : points_.size() / 2 - 1);
+	if (spanPtr && updateSpan)
+		*spanPtr = span;
+	return points_[span].y +
+	       (x - points_[span].x) * (points_[span + 1].y - points_[span].y) /
+		       (points_[span + 1].x - points_[span].x);
+}
+
+int Pwl::findSpan(double x, int span) const
+{
+	/*
+	 * Pwls are generally small, so linear search may well be faster than
+	 * binary, though could review this if large PWls start turning up.
+	 */
+	int lastSpan = points_.size() - 2;
+	/*
+	 * some algorithms may call us with span pointing directly at the last
+	 * control point
+	 */
+	span = std::max(0, std::min(lastSpan, span));
+	while (span < lastSpan && x >= points_[span + 1].x)
+		span++;
+	while (span && x < points_[span].x)
+		span--;
+	return span;
+}
+
+Pwl::PerpType Pwl::invert(Point const &xy, Point &perp, int &span,
+			  const double eps) const
+{
+	assert(span >= -1);
+	bool prevOffEnd = false;
+	for (span = span + 1; span < (int)points_.size() - 1; span++) {
+		Point spanVec = points_[span + 1] - points_[span];
+		double t = ((xy - points_[span]) % spanVec) / spanVec.len2();
+		if (t < -eps) /* off the start of this span */
+		{
+			if (span == 0) {
+				perp = points_[span];
+				return PerpType::Start;
+			} else if (prevOffEnd) {
+				perp = points_[span];
+				return PerpType::Vertex;
+			}
+		} else if (t > 1 + eps) /* off the end of this span */
+		{
+			if (span == (int)points_.size() - 2) {
+				perp = points_[span + 1];
+				return PerpType::End;
+			}
+			prevOffEnd = true;
+		} else /* a true perpendicular */
+		{
+			perp = points_[span] + spanVec * t;
+			return PerpType::Perpendicular;
+		}
+	}
+	return PerpType::None;
+}
+
+Pwl Pwl::inverse(bool *trueInverse, const double eps) const
+{
+	bool appended = false, prepended = false, neither = false;
+	Pwl inverse;
+
+	for (Point const &p : points_) {
+		if (inverse.empty())
+			inverse.append(p.y, p.x, eps);
+		else if (std::abs(inverse.points_.back().x - p.y) <= eps ||
+			 std::abs(inverse.points_.front().x - p.y) <= eps)
+			/* do nothing */;
+		else if (p.y > inverse.points_.back().x) {
+			inverse.append(p.y, p.x, eps);
+			appended = true;
+		} else if (p.y < inverse.points_.front().x) {
+			inverse.prepend(p.y, p.x, eps);
+			prepended = true;
+		} else
+			neither = true;
+	}
+
+	/*
+	 * This is not a proper inverse if we found ourselves putting points
+	 * onto both ends of the inverse, or if there were points that couldn't
+	 * go on either.
+	 */
+	if (trueInverse)
+		*trueInverse = !(neither || (appended && prepended));
+
+	return inverse;
+}
+
+Pwl Pwl::compose(Pwl const &other, const double eps) const
+{
+	double thisX = points_[0].x, thisY = points_[0].y;
+	int thisSpan = 0, otherSpan = other.findSpan(thisY, 0);
+	Pwl result({ { thisX, other.eval(thisY, &otherSpan, false) } });
+	while (thisSpan != (int)points_.size() - 1) {
+		double dx = points_[thisSpan + 1].x - points_[thisSpan].x,
+		       dy = points_[thisSpan + 1].y - points_[thisSpan].y;
+		if (std::abs(dy) > eps &&
+		    otherSpan + 1 < (int)other.points_.size() &&
+		    points_[thisSpan + 1].y >=
+			    other.points_[otherSpan + 1].x + eps) {
+			/*
+			 * next control point in result will be where this
+			 * function's y reaches the next span in other
+			 */
+			thisX = points_[thisSpan].x +
+				(other.points_[otherSpan + 1].x -
+				 points_[thisSpan].y) *
+					dx / dy;
+			thisY = other.points_[++otherSpan].x;
+		} else if (std::abs(dy) > eps && otherSpan > 0 &&
+			   points_[thisSpan + 1].y <=
+				   other.points_[otherSpan - 1].x - eps) {
+			/*
+			 * next control point in result will be where this
+			 * function's y reaches the previous span in other
+			 */
+			thisX = points_[thisSpan].x +
+				(other.points_[otherSpan + 1].x -
+				 points_[thisSpan].y) *
+					dx / dy;
+			thisY = other.points_[--otherSpan].x;
+		} else {
+			/* we stay in the same span in other */
+			thisSpan++;
+			thisX = points_[thisSpan].x,
+			thisY = points_[thisSpan].y;
+		}
+		result.append(thisX, other.eval(thisY, &otherSpan, false),
+			      eps);
+	}
+	return result;
+}
+
+void Pwl::map(std::function<void(double x, double y)> f) const
+{
+	for (auto &pt : points_)
+		f(pt.x, pt.y);
+}
+
+void Pwl::map2(Pwl const &pwl0, Pwl const &pwl1,
+	       std::function<void(double x, double y0, double y1)> f)
+{
+	int span0 = 0, span1 = 0;
+	double x = std::min(pwl0.points_[0].x, pwl1.points_[0].x);
+	f(x, pwl0.eval(x, &span0, false), pwl1.eval(x, &span1, false));
+	while (span0 < (int)pwl0.points_.size() - 1 ||
+	       span1 < (int)pwl1.points_.size() - 1) {
+		if (span0 == (int)pwl0.points_.size() - 1)
+			x = pwl1.points_[++span1].x;
+		else if (span1 == (int)pwl1.points_.size() - 1)
+			x = pwl0.points_[++span0].x;
+		else if (pwl0.points_[span0 + 1].x > pwl1.points_[span1 + 1].x)
+			x = pwl1.points_[++span1].x;
+		else
+			x = pwl0.points_[++span0].x;
+		f(x, pwl0.eval(x, &span0, false), pwl1.eval(x, &span1, false));
+	}
+}
+
+Pwl Pwl::combine(Pwl const &pwl0, Pwl const &pwl1,
+		 std::function<double(double x, double y0, double y1)> f,
+		 const double eps)
+{
+	Pwl result;
+	map2(pwl0, pwl1, [&](double x, double y0, double y1) {
+		result.append(x, f(x, y0, y1), eps);
+	});
+	return result;
+}
+
+void Pwl::matchDomain(Interval const &domain, bool clip, const double eps)
+{
+	int span = 0;
+	prepend(domain.start, eval(clip ? points_[0].x : domain.start, &span),
+		eps);
+	span = points_.size() - 2;
+	append(domain.end, eval(clip ? points_.back().x : domain.end, &span),
+	       eps);
+}
+
+Pwl &Pwl::operator*=(double d)
+{
+	for (auto &pt : points_)
+		pt.y *= d;
+	return *this;
+}
+
+void Pwl::debug(FILE *fp) const
+{
+	fprintf(fp, "Pwl {\n");
+	for (auto &p : points_)
+		fprintf(fp, "\t(%g, %g)\n", p.x, p.y);
+	fprintf(fp, "}\n");
+}

src/ipa/rpi/controller/pwl.h

@@ -0,0 +1,127 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2019, Raspberry Pi Ltd
+ *
+ * pwl.h - piecewise linear functions interface
+ */
+#pragma once
+
+#include <functional>
+#include <math.h>
+#include <vector>
+
+#include "libcamera/internal/yaml_parser.h"
+
+namespace RPiController {
+
+class Pwl
+{
+public:
+	struct Interval {
+		Interval(double _start, double _end)
+			: start(_start), end(_end)
+		{
+		}
+		double start, end;
+		bool contains(double value)
+		{
+			return value >= start && value <= end;
+		}
+		double clip(double value)
+		{
+			return value < start ? start
+					     : (value > end ? end : value);
+		}
+		double len() const { return end - start; }
+	};
+	struct Point {
+		Point() : x(0), y(0) {}
+		Point(double _x, double _y)
+			: x(_x), y(_y) {}
+		double x, y;
+		Point operator-(Point const &p) const
+		{
+			return Point(x - p.x, y - p.y);
+		}
+		Point operator+(Point const &p) const
+		{
+			return Point(x + p.x, y + p.y);
+		}
+		double operator%(Point const &p) const
+		{
+			return x * p.x + y * p.y;
+		}
+		Point operator*(double f) const { return Point(x * f, y * f); }
+		Point operator/(double f) const { return Point(x / f, y / f); }
+		double len2() const { return x * x + y * y; }
+		double len() const { return sqrt(len2()); }
+	};
+	Pwl() {}
+	Pwl(std::vector<Point> const &points) : points_(points) {}
+	int read(const libcamera::YamlObject &params);
+	void append(double x, double y, const double eps = 1e-6);
+	void prepend(double x, double y, const double eps = 1e-6);
+	Interval domain() const;
+	Interval range() const;
+	bool empty() const;
+	/*
+	 * Evaluate Pwl, optionally supplying an initial guess for the
+	 * "span". The "span" may be optionally be updated.  If you want to know
+	 * the "span" value but don't have an initial guess you can set it to
+	 * -1.
+	 */
+	double eval(double x, int *spanPtr = nullptr,
+		    bool updateSpan = true) const;
+	/*
+	 * Find perpendicular closest to xy, starting from span+1 so you can
+	 * call it repeatedly to check for multiple closest points (set span to
+	 * -1 on the first call). Also returns "pseudo" perpendiculars; see
+	 * PerpType enum.
+	 */
+	enum class PerpType {
+		None, /* no perpendicular found */
+		Start, /* start of Pwl is closest point */
+		End, /* end of Pwl is closest point */
+		Vertex, /* vertex of Pwl is closest point */
+		Perpendicular /* true perpendicular found */
+	};
+	PerpType invert(Point const &xy, Point &perp, int &span,
+			const double eps = 1e-6) const;
+	/*
+	 * Compute the inverse function. Indicate if it is a proper (true)
+	 * inverse, or only a best effort (e.g. input was non-monotonic).
+	 */
+	Pwl inverse(bool *trueInverse = nullptr, const double eps = 1e-6) const;
+	/* Compose two Pwls together, doing "this" first and "other" after. */
+	Pwl compose(Pwl const &other, const double eps = 1e-6) const;
+	/* Apply function to (x,y) values at every control point. */
+	void map(std::function<void(double x, double y)> f) const;
+	/*
+	 * Apply function to (x, y0, y1) values wherever either Pwl has a
+	 * control point.
+	 */
+	static void map2(Pwl const &pwl0, Pwl const &pwl1,
+			 std::function<void(double x, double y0, double y1)> f);
+	/*
+	 * Combine two Pwls, meaning we create a new Pwl where the y values are
+	 * given by running f wherever either has a knot.
+	 */
+	static Pwl
+	combine(Pwl const &pwl0, Pwl const &pwl1,
+		std::function<double(double x, double y0, double y1)> f,
+		const double eps = 1e-6);
+	/*
+	 * Make "this" match (at least) the given domain. Any extension my be
+	 * clipped or linear.
+	 */
+	void matchDomain(Interval const &domain, bool clip = true,
+			 const double eps = 1e-6);
+	Pwl &operator*=(double d);
+	void debug(FILE *fp = stdout) const;
+
+private:
+	int findSpan(double x, int span) const;
+	std::vector<Point> points_;
+};
+
+} /* namespace RPiController */

src/ipa/rpi/controller/region_stats.h

@@ -0,0 +1,123 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2022, Raspberry Pi Ltd
+ *
+ * region_stats.h - Raspberry Pi region based statistics container
+ */
+#pragma once
+
+#include <array>
+#include <stdint.h>
+#include <vector>
+
+#include <libcamera/geometry.h>
+
+namespace RPiController {
+
+template<typename T>
+class RegionStats
+{
+public:
+	struct Region {
+		T val;
+		uint32_t counted;
+		uint32_t uncounted;
+	};
+
+	RegionStats()
+		: size_({}), numFloating_(0), default_({})
+	{
+	}
+
+	void init(const libcamera::Size &size, unsigned int numFloating = 0)
+	{
+		size_ = size;
+		numFloating_ = numFloating;
+		regions_.clear();
+		regions_.resize(size_.width * size_.height + numFloating_);
+	}
+
+	void init(unsigned int num)
+	{
+		size_ = libcamera::Size(num, 1);
+		numFloating_ = 0;
+		regions_.clear();
+		regions_.resize(num);
+	}
+
+	unsigned int numRegions() const
+	{
+		return size_.width * size_.height;
+	}
+
+	unsigned int numFloatingRegions() const
+	{
+		return numFloating_;
+	}
+
+	libcamera::Size size() const
+	{
+		return size_;
+	}
+
+	void set(unsigned int index, const Region &region)
+	{
+		if (index >= numRegions())
+			return;
+		set_(index, region);
+	}
+
+	void set(const libcamera::Point &pos, const Region &region)
+	{
+		set(pos.y * size_.width + pos.x, region);
+	}
+
+	void setFloating(unsigned int index, const Region &region)
+	{
+		if (index >= numFloatingRegions())
+			return;
+		set(numRegions() + index, region);
+	}
+
+	const Region &get(unsigned int index) const
+	{
+		if (index >= numRegions())
+			return default_;
+		return get_(index);
+	}
+
+	const Region &get(const libcamera::Point &pos) const
+	{
+		return get(pos.y * size_.width + pos.x);
+	}
+
+	const Region &getFloating(unsigned int index) const
+	{
+		if (index >= numFloatingRegions())
+			return default_;
+		return get_(numRegions() + index);
+	}
+
+	typename std::vector<Region>::iterator begin() { return regions_.begin(); }
+	typename std::vector<Region>::iterator end() { return regions_.end(); }
+	typename std::vector<Region>::const_iterator begin() const { return regions_.begin(); }
+	typename std::vector<Region>::const_iterator end() const { return regions_.end(); }
+
+private:
+	void set_(unsigned int index, const Region &region)
+	{
+		regions_[index] = region;
+	}
+
+	const Region &get_(unsigned int index) const
+	{
+		return regions_[index];
+	}
+
+	libcamera::Size size_;
+	unsigned int numFloating_;
+	std::vector<Region> regions_;
+	Region default_;
+};
+
+} /* namespace RPiController */

src/ipa/rpi/controller/rpi/af.cpp

@@ -0,0 +1,797 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2022-2023, Raspberry Pi Ltd
+ *
+ * af.cpp - Autofocus control algorithm
+ */
+
+#include "af.h"
+
+#include <iomanip>
+#include <math.h>
+#include <stdlib.h>
+
+#include <libcamera/base/log.h>
+
+#include <libcamera/control_ids.h>
+
+using namespace RPiController;
+using namespace libcamera;
+
+LOG_DEFINE_CATEGORY(RPiAf)
+
+#define NAME "rpi.af"
+
+/*
+ * Default values for parameters. All may be overridden in the tuning file.
+ * Many of these values are sensor- or module-dependent; the defaults here
+ * assume IMX708 in a Raspberry Pi V3 camera with the standard lens.
+ *
+ * Here all focus values are in dioptres (1/m). They are converted to hardware
+ * units when written to status.lensSetting or returned from setLensPosition().
+ *
+ * Gain and delay values are relative to the update rate, since much (not all)
+ * of the delay is in the sensor and (for CDAF) ISP, not the lens mechanism;
+ * but note that algorithms are updated at no more than 30 Hz.
+ */
+
+Af::RangeDependentParams::RangeDependentParams()
+	: focusMin(0.0),
+	  focusMax(12.0),
+	  focusDefault(1.0)
+{
+}
+
+Af::SpeedDependentParams::SpeedDependentParams()
+	: stepCoarse(1.0),
+	  stepFine(0.25),
+	  contrastRatio(0.75),
+	  pdafGain(-0.02),
+	  pdafSquelch(0.125),
+	  maxSlew(2.0),
+	  pdafFrames(20),
+	  dropoutFrames(6),
+	  stepFrames(4)
+{
+}
+
+Af::CfgParams::CfgParams()
+	: confEpsilon(8),
+	  confThresh(16),
+	  confClip(512),
+	  skipFrames(5),
+	  map()
+{
+}
+
+template<typename T>
+static void readNumber(T &dest, const libcamera::YamlObject &params, char const *name)
+{
+	auto value = params[name].get<T>();
+	if (value)
+		dest = *value;
+	else
+		LOG(RPiAf, Warning) << "Missing parameter \"" << name << "\"";
+}
+
+void Af::RangeDependentParams::read(const libcamera::YamlObject &params)
+{
+
+	readNumber<double>(focusMin, params, "min");
+	readNumber<double>(focusMax, params, "max");
+	readNumber<double>(focusDefault, params, "default");
+}
+
+void Af::SpeedDependentParams::read(const libcamera::YamlObject &params)
+{
+	readNumber<double>(stepCoarse, params, "step_coarse");
+	readNumber<double>(stepFine, params, "step_fine");
+	readNumber<double>(contrastRatio, params, "contrast_ratio");
+	readNumber<double>(pdafGain, params, "pdaf_gain");
+	readNumber<double>(pdafSquelch, params, "pdaf_squelch");
+	readNumber<double>(maxSlew, params, "max_slew");
+	readNumber<uint32_t>(pdafFrames, params, "pdaf_frames");
+	readNumber<uint32_t>(dropoutFrames, params, "dropout_frames");
+	readNumber<uint32_t>(stepFrames, params, "step_frames");
+}
+
+int Af::CfgParams::read(const libcamera::YamlObject &params)
+{
+	if (params.contains("ranges")) {
+		auto &rr = params["ranges"];
+
+		if (rr.contains("normal"))
+			ranges[AfRangeNormal].read(rr["normal"]);
+		else
+			LOG(RPiAf, Warning) << "Missing range \"normal\"";
+
+		ranges[AfRangeMacro] = ranges[AfRangeNormal];
+		if (rr.contains("macro"))
+			ranges[AfRangeMacro].read(rr["macro"]);
+
+		ranges[AfRangeFull].focusMin = std::min(ranges[AfRangeNormal].focusMin,
+							ranges[AfRangeMacro].focusMin);
+		ranges[AfRangeFull].focusMax = std::max(ranges[AfRangeNormal].focusMax,
+							ranges[AfRangeMacro].focusMax);
+		ranges[AfRangeFull].focusDefault = ranges[AfRangeNormal].focusDefault;
+		if (rr.contains("full"))
+			ranges[AfRangeFull].read(rr["full"]);
+	} else
+		LOG(RPiAf, Warning) << "No ranges defined";
+
+	if (params.contains("speeds")) {
+		auto &ss = params["speeds"];
+
+		if (ss.contains("normal"))
+			speeds[AfSpeedNormal].read(ss["normal"]);
+		else
+			LOG(RPiAf, Warning) << "Missing speed \"normal\"";
+
+		speeds[AfSpeedFast] = speeds[AfSpeedNormal];
+		if (ss.contains("fast"))
+			speeds[AfSpeedFast].read(ss["fast"]);
+	} else
+		LOG(RPiAf, Warning) << "No speeds defined";
+
+	readNumber<uint32_t>(confEpsilon, params, "conf_epsilon");
+	readNumber<uint32_t>(confThresh, params, "conf_thresh");
+	readNumber<uint32_t>(confClip, params, "conf_clip");
+	readNumber<uint32_t>(skipFrames, params, "skip_frames");
+
+	if (params.contains("map"))
+		map.read(params["map"]);
+	else
+		LOG(RPiAf, Warning) << "No map defined";
+
+	return 0;
+}
+
+void Af::CfgParams::initialise()
+{
+	if (map.empty()) {
+		/* Default mapping from dioptres to hardware setting */
+		static constexpr double DefaultMapX0 = 0.0;
+		static constexpr double DefaultMapY0 = 445.0;
+		static constexpr double DefaultMapX1 = 15.0;
+		static constexpr double DefaultMapY1 = 925.0;
+
+		map.append(DefaultMapX0, DefaultMapY0);
+		map.append(DefaultMapX1, DefaultMapY1);
+	}
+}
+
+/* Af Algorithm class */
+
+static constexpr unsigned MaxWindows = 10;
+
+Af::Af(Controller *controller)
+	: AfAlgorithm(controller),
+	  cfg_(),
+	  range_(AfRangeNormal),
+	  speed_(AfSpeedNormal),
+	  mode_(AfAlgorithm::AfModeManual),
+	  pauseFlag_(false),
+	  statsRegion_(0, 0, 0, 0),
+	  windows_(),
+	  useWindows_(false),
+	  phaseWeights_(),
+	  contrastWeights_(),
+	  scanState_(ScanState::Idle),
+	  initted_(false),
+	  ftarget_(-1.0),
+	  fsmooth_(-1.0),
+	  prevContrast_(0.0),
+	  skipCount_(0),
+	  stepCount_(0),
+	  dropCount_(0),
+	  scanMaxContrast_(0.0),
+	  scanMinContrast_(1.0e9),
+	  scanData_(),
+	  reportState_(AfState::Idle)
+{
+	/*
+	 * Reserve space for data, to reduce memory fragmentation. It's too early
+	 * to query the size of the PDAF (from camera) and Contrast (from ISP)
+	 * statistics, but these are plausible upper bounds.
+	 */
+	phaseWeights_.w.reserve(16 * 12);
+	contrastWeights_.w.reserve(getHardwareConfig().focusRegions.width *
+				   getHardwareConfig().focusRegions.height);
+	scanData_.reserve(32);
+}
+
+Af::~Af()
+{
+}
+
+char const *Af::name() const
+{
+	return NAME;
+}
+
+int Af::read(const libcamera::YamlObject &params)
+{
+	return cfg_.read(params);
+}
+
+void Af::initialise()
+{
+	cfg_.initialise();
+}
+
+void Af::switchMode(CameraMode const &cameraMode, [[maybe_unused]] Metadata *metadata)
+{
+	(void)metadata;
+
+	/* Assume that PDAF and Focus stats grids cover the visible area */
+	statsRegion_.x = (int)cameraMode.cropX;
+	statsRegion_.y = (int)cameraMode.cropY;
+	statsRegion_.width = (unsigned)(cameraMode.width * cameraMode.scaleX);
+	statsRegion_.height = (unsigned)(cameraMode.height * cameraMode.scaleY);
+	LOG(RPiAf, Debug) << "switchMode: statsRegion: "
+			  << statsRegion_.x << ','
+			  << statsRegion_.y << ','
+			  << statsRegion_.width << ','
+			  << statsRegion_.height;
+	invalidateWeights();
+
+	if (scanState_ >= ScanState::Coarse && scanState_ < ScanState::Settle) {
+		/*
+		 * If a scan was in progress, re-start it, as CDAF statistics
+		 * may have changed. Though if the application is just about
+		 * to take a still picture, this will not help...
+		 */
+		startProgrammedScan();
+	}
+	skipCount_ = cfg_.skipFrames;
+}
+
+void Af::computeWeights(RegionWeights *wgts, unsigned rows, unsigned cols)
+{
+	wgts->rows = rows;
+	wgts->cols = cols;
+	wgts->sum = 0;
+	wgts->w.resize(rows * cols);
+	std::fill(wgts->w.begin(), wgts->w.end(), 0);
+
+	if (rows > 0 && cols > 0 && useWindows_ &&
+	    statsRegion_.height >= rows && statsRegion_.width >= cols) {
+		/*
+		 * Here we just merge all of the given windows, weighted by area.
+		 * \todo Perhaps a better approach might be to find the phase in each
+		 * window and choose either the closest or the highest-confidence one?
+		 * Ensure weights sum to less than (1<<16). 46080 is a "round number"
+		 * below 65536, for better rounding when window size is a simple
+		 * fraction of image dimensions.
+		 */
+		const unsigned maxCellWeight = 46080u / (MaxWindows * rows * cols);
+		const unsigned cellH = statsRegion_.height / rows;
+		const unsigned cellW = statsRegion_.width / cols;
+		const unsigned cellA = cellH * cellW;
+
+		for (auto &w : windows_) {
+			for (unsigned r = 0; r < rows; ++r) {
+				int y0 = std::max(statsRegion_.y + (int)(cellH * r), w.y);
+				int y1 = std::min(statsRegion_.y + (int)(cellH * (r + 1)),
+						  w.y + (int)(w.height));
+				if (y0 >= y1)
+					continue;
+				y1 -= y0;
+				for (unsigned c = 0; c < cols; ++c) {
+					int x0 = std::max(statsRegion_.x + (int)(cellW * c), w.x);
+					int x1 = std::min(statsRegion_.x + (int)(cellW * (c + 1)),
+							  w.x + (int)(w.width));
+					if (x0 >= x1)
+						continue;
+					unsigned a = y1 * (x1 - x0);
+					a = (maxCellWeight * a + cellA - 1) / cellA;
+					wgts->w[r * cols + c] += a;
+					wgts->sum += a;
+				}
+			}
+		}
+	}
+
+	if (wgts->sum == 0) {
+		/* Default AF window is the middle 1/2 width of the middle 1/3 height */
+		for (unsigned r = rows / 3; r < rows - rows / 3; ++r) {
+			for (unsigned c = cols / 4; c < cols - cols / 4; ++c) {
+				wgts->w[r * cols + c] = 1;
+				wgts->sum += 1;
+			}
+		}
+	}
+}
+
+void Af::invalidateWeights()
+{
+	phaseWeights_.sum = 0;
+	contrastWeights_.sum = 0;
+}
+
+bool Af::getPhase(PdafRegions const &regions, double &phase, double &conf)
+{
+	libcamera::Size size = regions.size();
+	if (size.height != phaseWeights_.rows || size.width != phaseWeights_.cols ||
+	    phaseWeights_.sum == 0) {
+		LOG(RPiAf, Debug) << "Recompute Phase weights " << size.width << 'x' << size.height;
+		computeWeights(&phaseWeights_, size.height, size.width);
+	}
+
+	uint32_t sumWc = 0;
+	int64_t sumWcp = 0;
+	for (unsigned i = 0; i < regions.numRegions(); ++i) {
+		unsigned w = phaseWeights_.w[i];
+		if (w) {
+			const PdafData &data = regions.get(i).val;
+			unsigned c = data.conf;
+			if (c >= cfg_.confThresh) {
+				if (c > cfg_.confClip)
+					c = cfg_.confClip;
+				c -= (cfg_.confThresh >> 2);
+				sumWc += w * c;
+				c -= (cfg_.confThresh >> 2);
+				sumWcp += (int64_t)(w * c) * (int64_t)data.phase;
+			}
+		}
+	}
+
+	if (0 < phaseWeights_.sum && phaseWeights_.sum <= sumWc) {
+		phase = (double)sumWcp / (double)sumWc;
+		conf = (double)sumWc / (double)phaseWeights_.sum;
+		return true;
+	} else {
+		phase = 0.0;
+		conf = 0.0;
+		return false;
+	}
+}
+
+double Af::getContrast(const FocusRegions &focusStats)
+{
+	libcamera::Size size = focusStats.size();
+	if (size.height != contrastWeights_.rows ||
+	    size.width != contrastWeights_.cols || contrastWeights_.sum == 0) {
+		LOG(RPiAf, Debug) << "Recompute Contrast weights "
+				  << size.width << 'x' << size.height;
+		computeWeights(&contrastWeights_, size.height, size.width);
+	}
+
+	uint64_t sumWc = 0;
+	for (unsigned i = 0; i < focusStats.numRegions(); ++i)
+		sumWc += contrastWeights_.w[i] * focusStats.get(i).val;
+
+	return (contrastWeights_.sum > 0) ? ((double)sumWc / (double)contrastWeights_.sum) : 0.0;
+}
+
+void Af::doPDAF(double phase, double conf)
+{
+	/* Apply loop gain */
+	phase *= cfg_.speeds[speed_].pdafGain;
+
+	if (mode_ == AfModeContinuous) {
+		/*
+		 * PDAF in Continuous mode. Scale down lens movement when
+		 * delta is small or confidence is low, to suppress wobble.
+		 */
+		phase *= conf / (conf + cfg_.confEpsilon);
+		if (std::abs(phase) < cfg_.speeds[speed_].pdafSquelch) {
+			double a = phase / cfg_.speeds[speed_].pdafSquelch;
+			phase *= a * a;
+		}
+	} else {
+		/*
+		 * PDAF in triggered-auto mode. Allow early termination when
+		 * phase delta is small; scale down lens movements towards
+		 * the end of the sequence, to ensure a stable image.
+		 */
+		if (stepCount_ >= cfg_.speeds[speed_].stepFrames) {
+			if (std::abs(phase) < cfg_.speeds[speed_].pdafSquelch)
+				stepCount_ = cfg_.speeds[speed_].stepFrames;
+		} else
+			phase *= stepCount_ / cfg_.speeds[speed_].stepFrames;
+	}
+
+	/* Apply slew rate limit. Report failure if out of bounds. */
+	if (phase < -cfg_.speeds[speed_].maxSlew) {
+		phase = -cfg_.speeds[speed_].maxSlew;
+		reportState_ = (ftarget_ <= cfg_.ranges[range_].focusMin) ? AfState::Failed
+									  : AfState::Scanning;
+	} else if (phase > cfg_.speeds[speed_].maxSlew) {
+		phase = cfg_.speeds[speed_].maxSlew;
+		reportState_ = (ftarget_ >= cfg_.ranges[range_].focusMax) ? AfState::Failed
+									  : AfState::Scanning;
+	} else
+		reportState_ = AfState::Focused;
+
+	ftarget_ = fsmooth_ + phase;
+}
+
+bool Af::earlyTerminationByPhase(double phase)
+{
+	if (scanData_.size() > 0 &&
+	    scanData_[scanData_.size() - 1].conf >= cfg_.confEpsilon) {
+		double oldFocus = scanData_[scanData_.size() - 1].focus;
+		double oldPhase = scanData_[scanData_.size() - 1].phase;
+
+		/*
+		 * Check that the gradient is finite and has the expected sign;
+		 * Interpolate/extrapolate the lens position for zero phase.
+		 * Check that the extrapolation is well-conditioned.
+		 */
+		if ((ftarget_ - oldFocus) * (phase - oldPhase) > 0.0) {
+			double param = phase / (phase - oldPhase);
+			if (-3.0 <= param && param <= 3.5) {
+				ftarget_ += param * (oldFocus - ftarget_);
+				LOG(RPiAf, Debug) << "ETBP: param=" << param;
+				return true;
+			}
+		}
+	}
+
+	return false;
+}
+
+double Af::findPeak(unsigned i) const
+{
+	double f = scanData_[i].focus;
+
+	if (i > 0 && i + 1 < scanData_.size()) {
+		double dropLo = scanData_[i].contrast - scanData_[i - 1].contrast;
+		double dropHi = scanData_[i].contrast - scanData_[i + 1].contrast;
+		if (0.0 <= dropLo && dropLo < dropHi) {
+			double param = 0.3125 * (1.0 - dropLo / dropHi) * (1.6 - dropLo / dropHi);
+			f += param * (scanData_[i - 1].focus - f);
+		} else if (0.0 <= dropHi && dropHi < dropLo) {
+			double param = 0.3125 * (1.0 - dropHi / dropLo) * (1.6 - dropHi / dropLo);
+			f += param * (scanData_[i + 1].focus - f);
+		}
+	}
+
+	LOG(RPiAf, Debug) << "FindPeak: " << f;
+	return f;
+}
+
+void Af::doScan(double contrast, double phase, double conf)
+{
+	/* Record lens position, contrast and phase values for the current scan */
+	if (scanData_.empty() || contrast > scanMaxContrast_) {
+		scanMaxContrast_ = contrast;
+		scanMaxIndex_ = scanData_.size();
+	}
+	if (contrast < scanMinContrast_)
+		scanMinContrast_ = contrast;
+	scanData_.emplace_back(ScanRecord{ ftarget_, contrast, phase, conf });
+
+	if (scanState_ == ScanState::Coarse) {
+		if (ftarget_ >= cfg_.ranges[range_].focusMax ||
+		    contrast < cfg_.speeds[speed_].contrastRatio * scanMaxContrast_) {
+			/*
+			 * Finished course scan, or termination based on contrast.
+			 * Jump to just after max contrast and start fine scan.
+			 */
+			ftarget_ = std::min(ftarget_, findPeak(scanMaxIndex_) +
+					2.0 * cfg_.speeds[speed_].stepFine);
+			scanState_ = ScanState::Fine;
+			scanData_.clear();
+		} else
+			ftarget_ += cfg_.speeds[speed_].stepCoarse;
+	} else { /* ScanState::Fine */
+		if (ftarget_ <= cfg_.ranges[range_].focusMin || scanData_.size() >= 5 ||
+		    contrast < cfg_.speeds[speed_].contrastRatio * scanMaxContrast_) {
+			/*
+			 * Finished fine scan, or termination based on contrast.
+			 * Use quadratic peak-finding to find best contrast position.
+			 */
+			ftarget_ = findPeak(scanMaxIndex_);
+			scanState_ = ScanState::Settle;
+		} else
+			ftarget_ -= cfg_.speeds[speed_].stepFine;
+	}
+
+	stepCount_ = (ftarget_ == fsmooth_) ? 0 : cfg_.speeds[speed_].stepFrames;
+}
+
+void Af::doAF(double contrast, double phase, double conf)
+{
+	/* Skip frames at startup and after sensor mode change */
+	if (skipCount_ > 0) {
+		LOG(RPiAf, Debug) << "SKIP";
+		skipCount_--;
+		return;
+	}
+
+	if (scanState_ == ScanState::Pdaf) {
+		/*
+		 * Use PDAF closed-loop control whenever available, in both CAF
+		 * mode and (for a limited number of iterations) when triggered.
+		 * If PDAF fails (due to poor contrast, noise or large defocus),
+		 * fall back to a CDAF-based scan. To avoid "nuisance" scans,
+		 * scan only after a number of frames with low PDAF confidence.
+		 */
+		if (conf > (dropCount_ ? 1.0 : 0.25) * cfg_.confEpsilon) {
+			doPDAF(phase, conf);
+			if (stepCount_ > 0)
+				stepCount_--;
+			else if (mode_ != AfModeContinuous)
+				scanState_ = ScanState::Idle;
+			dropCount_ = 0;
+		} else if (++dropCount_ == cfg_.speeds[speed_].dropoutFrames)
+			startProgrammedScan();
+	} else if (scanState_ >= ScanState::Coarse && fsmooth_ == ftarget_) {
+		/*
+		 * Scanning sequence. This means PDAF has become unavailable.
+		 * Allow a delay between steps for CDAF FoM statistics to be
+		 * updated, and a "settling time" at the end of the sequence.
+		 * [A coarse or fine scan can be abandoned if two PDAF samples
+		 * allow direct interpolation of the zero-phase lens position.]
+		 */
+		if (stepCount_ > 0)
+			stepCount_--;
+		else if (scanState_ == ScanState::Settle) {
+			if (prevContrast_ >= cfg_.speeds[speed_].contrastRatio * scanMaxContrast_ &&
+			    scanMinContrast_ <= cfg_.speeds[speed_].contrastRatio * scanMaxContrast_)
+				reportState_ = AfState::Focused;
+			else
+				reportState_ = AfState::Failed;
+			if (mode_ == AfModeContinuous && !pauseFlag_ &&
+			    cfg_.speeds[speed_].dropoutFrames > 0)
+				scanState_ = ScanState::Pdaf;
+			else
+				scanState_ = ScanState::Idle;
+			scanData_.clear();
+		} else if (conf >= cfg_.confEpsilon && earlyTerminationByPhase(phase)) {
+			scanState_ = ScanState::Settle;
+			stepCount_ = (mode_ == AfModeContinuous) ? 0
+								 : cfg_.speeds[speed_].stepFrames;
+		} else
+			doScan(contrast, phase, conf);
+	}
+}
+
+void Af::updateLensPosition()
+{
+	if (scanState_ >= ScanState::Pdaf) {
+		ftarget_ = std::clamp(ftarget_,
+				      cfg_.ranges[range_].focusMin,
+				      cfg_.ranges[range_].focusMax);
+	}
+
+	if (initted_) {
+		/* from a known lens position: apply slew rate limit */
+		fsmooth_ = std::clamp(ftarget_,
+				      fsmooth_ - cfg_.speeds[speed_].maxSlew,
+				      fsmooth_ + cfg_.speeds[speed_].maxSlew);
+	} else {
+		/* from an unknown position: go straight to target, but add delay */
+		fsmooth_ = ftarget_;
+		initted_ = true;
+		skipCount_ = cfg_.skipFrames;
+	}
+}
+
+void Af::startAF()
+{
+	/* Use PDAF if the tuning file allows it; else CDAF. */
+	if (cfg_.speeds[speed_].dropoutFrames > 0 &&
+	    (mode_ == AfModeContinuous || cfg_.speeds[speed_].pdafFrames > 0)) {
+		if (!initted_) {
+			ftarget_ = cfg_.ranges[range_].focusDefault;
+			updateLensPosition();
+		}
+		stepCount_ = (mode_ == AfModeContinuous) ? 0 : cfg_.speeds[speed_].pdafFrames;
+		scanState_ = ScanState::Pdaf;
+		scanData_.clear();
+		dropCount_ = 0;
+		reportState_ = AfState::Scanning;
+	} else
+		startProgrammedScan();
+}
+
+void Af::startProgrammedScan()
+{
+	ftarget_ = cfg_.ranges[range_].focusMin;
+	updateLensPosition();
+	scanState_ = ScanState::Coarse;
+	scanMaxContrast_ = 0.0;
+	scanMinContrast_ = 1.0e9;
+	scanMaxIndex_ = 0;
+	scanData_.clear();
+	stepCount_ = cfg_.speeds[speed_].stepFrames;
+	reportState_ = AfState::Scanning;
+}
+
+void Af::goIdle()
+{
+	scanState_ = ScanState::Idle;
+	reportState_ = AfState::Idle;
+	scanData_.clear();
+}
+
+/*
+ * PDAF phase data are available in prepare(), but CDAF statistics are not
+ * available until process(). We are gambling on the availability of PDAF.
+ * To expedite feedback control using PDAF, issue the V4L2 lens control from
+ * prepare(). Conversely, during scans, we must allow an extra frame delay
+ * between steps, to retrieve CDAF statistics from the previous process()
+ * so we can terminate the scan early without having to change our minds.
+ */
+
+void Af::prepare(Metadata *imageMetadata)
+{
+	/* Initialize for triggered scan or start of CAF mode */
+	if (scanState_ == ScanState::Trigger)
+		startAF();
+
+	if (initted_) {
+		/* Get PDAF from the embedded metadata, and run AF algorithm core */
+		PdafRegions regions;
+		double phase = 0.0, conf = 0.0;
+		double oldFt = ftarget_;
+		double oldFs = fsmooth_;
+		ScanState oldSs = scanState_;
+		uint32_t oldSt = stepCount_;
+		if (imageMetadata->get("pdaf.regions", regions) == 0)
+			getPhase(regions, phase, conf);
+		doAF(prevContrast_, phase, conf);
+		updateLensPosition();
+		LOG(RPiAf, Debug) << std::fixed << std::setprecision(2)
+				  << static_cast<unsigned int>(reportState_)
+				  << " sst" << static_cast<unsigned int>(oldSs)
+				  << "->" << static_cast<unsigned int>(scanState_)
+				  << " stp" << oldSt << "->" << stepCount_
+				  << " ft" << oldFt << "->" << ftarget_
+				  << " fs" << oldFs << "->" << fsmooth_
+				  << " cont=" << (int)prevContrast_
+				  << " phase=" << (int)phase << " conf=" << (int)conf;
+	}
+
+	/* Report status and produce new lens setting */
+	AfStatus status;
+	if (pauseFlag_)
+		status.pauseState = (scanState_ == ScanState::Idle) ? AfPauseState::Paused
+								    : AfPauseState::Pausing;
+	else
+		status.pauseState = AfPauseState::Running;
+
+	if (mode_ == AfModeAuto && scanState_ != ScanState::Idle)
+		status.state = AfState::Scanning;
+	else
+		status.state = reportState_;
+	status.lensSetting = initted_ ? std::optional<int>(cfg_.map.eval(fsmooth_))
+				      : std::nullopt;
+	imageMetadata->set("af.status", status);
+}
+
+void Af::process(StatisticsPtr &stats, [[maybe_unused]] Metadata *imageMetadata)
+{
+	(void)imageMetadata;
+	prevContrast_ = getContrast(stats->focusRegions);
+}
+
+/* Controls */
+
+void Af::setRange(AfRange r)
+{
+	LOG(RPiAf, Debug) << "setRange: " << (unsigned)r;
+	if (r < AfAlgorithm::AfRangeMax)
+		range_ = r;
+}
+
+void Af::setSpeed(AfSpeed s)
+{
+	LOG(RPiAf, Debug) << "setSpeed: " << (unsigned)s;
+	if (s < AfAlgorithm::AfSpeedMax) {
+		if (scanState_ == ScanState::Pdaf &&
+		    cfg_.speeds[s].pdafFrames > cfg_.speeds[speed_].pdafFrames)
+			stepCount_ += cfg_.speeds[s].pdafFrames - cfg_.speeds[speed_].pdafFrames;
+		speed_ = s;
+	}
+}
+
+void Af::setMetering(bool mode)
+{
+	if (useWindows_ != mode) {
+		useWindows_ = mode;
+		invalidateWeights();
+	}
+}
+
+void Af::setWindows(libcamera::Span<libcamera::Rectangle const> const &wins)
+{
+	windows_.clear();
+	for (auto &w : wins) {
+		LOG(RPiAf, Debug) << "Window: "
+				  << w.x << ", "
+				  << w.y << ", "
+				  << w.width << ", "
+				  << w.height;
+		windows_.push_back(w);
+		if (windows_.size() >= MaxWindows)
+			break;
+	}
+
+	if (useWindows_)
+		invalidateWeights();
+}
+
+bool Af::setLensPosition(double dioptres, int *hwpos)
+{
+	bool changed = false;
+
+	if (mode_ == AfModeManual) {
+		LOG(RPiAf, Debug) << "setLensPosition: " << dioptres;
+		ftarget_ = cfg_.map.domain().clip(dioptres);
+		changed = !(initted_ && fsmooth_ == ftarget_);
+		updateLensPosition();
+	}
+
+	if (hwpos)
+		*hwpos = cfg_.map.eval(fsmooth_);
+
+	return changed;
+}
+
+std::optional<double> Af::getLensPosition() const
+{
+	/*
+	 * \todo We ought to perform some precise timing here to determine
+	 * the current lens position.
+	 */
+	return initted_ ? std::optional<double>(fsmooth_) : std::nullopt;
+}
+
+void Af::cancelScan()
+{
+	LOG(RPiAf, Debug) << "cancelScan";
+	if (mode_ == AfModeAuto)
+		goIdle();
+}
+
+void Af::triggerScan()
+{
+	LOG(RPiAf, Debug) << "triggerScan";
+	if (mode_ == AfModeAuto && scanState_ == ScanState::Idle)
+		scanState_ = ScanState::Trigger;
+}
+
+void Af::setMode(AfAlgorithm::AfMode mode)
+{
+	LOG(RPiAf, Debug) << "setMode: " << (unsigned)mode;
+	if (mode_ != mode) {
+		mode_ = mode;
+		pauseFlag_ = false;
+		if (mode == AfModeContinuous)
+			scanState_ = ScanState::Trigger;
+		else if (mode != AfModeAuto || scanState_ < ScanState::Coarse)
+			goIdle();
+	}
+}
+
+AfAlgorithm::AfMode Af::getMode() const
+{
+	return mode_;
+}
+
+void Af::pause(AfAlgorithm::AfPause pause)
+{
+	LOG(RPiAf, Debug) << "pause: " << (unsigned)pause;
+	if (mode_ == AfModeContinuous) {
+		if (pause == AfPauseResume && pauseFlag_) {
+			pauseFlag_ = false;
+			if (scanState_ < ScanState::Coarse)
+				scanState_ = ScanState::Trigger;
+		} else if (pause != AfPauseResume && !pauseFlag_) {
+			pauseFlag_ = true;
+			if (pause == AfPauseImmediate || scanState_ < ScanState::Coarse)
+				goIdle();
+		}
+	}
+}
+
+// Register algorithm with the system.
+static Algorithm *create(Controller *controller)
+{
+	return (Algorithm *)new Af(controller);
+}
+static RegisterAlgorithm reg(NAME, &create);

src/ipa/rpi/controller/rpi/af.h

@@ -0,0 +1,165 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2022-2023, Raspberry Pi Ltd
+ *
+ * af.h - Autofocus control algorithm
+ */
+#pragma once
+
+#include "../af_algorithm.h"
+#include "../af_status.h"
+#include "../pdaf_data.h"
+#include "../pwl.h"
+
+/*
+ * This algorithm implements a hybrid of CDAF and PDAF, favouring PDAF.
+ *
+ * Whenever PDAF is available, it is used in a continuous feedback loop.
+ * When triggered in auto mode, we simply enable AF for a limited number
+ * of frames (it may terminate early if the delta becomes small enough).
+ *
+ * When PDAF confidence is low (due e.g. to low contrast or extreme defocus)
+ * or PDAF data are absent, fall back to CDAF with a programmed scan pattern.
+ * A coarse and fine scan are performed, using ISP's CDAF focus FoM to
+ * estimate the lens position with peak contrast. This is slower due to
+ * extra latency in the ISP, and requires a settling time between steps.
+ *
+ * Some hysteresis is applied to the switch between PDAF and CDAF, to avoid
+ * "nuisance" scans. During each interval where PDAF is not working, only
+ * ONE scan will be performed; CAF cannot track objects using CDAF alone.
+ *
+ */
+
+namespace RPiController {
+
+class Af : public AfAlgorithm
+{
+public:
+	Af(Controller *controller = NULL);
+	~Af();
+	char const *name() const override;
+	int read(const libcamera::YamlObject &params) override;
+	void initialise() override;
+
+	/* IPA calls */
+	void switchMode(CameraMode const &cameraMode, Metadata *metadata) override;
+	void prepare(Metadata *imageMetadata) override;
+	void process(StatisticsPtr &stats, Metadata *imageMetadata) override;
+
+	/* controls */
+	void setRange(AfRange range) override;
+	void setSpeed(AfSpeed speed) override;
+	void setMetering(bool use_windows) override;
+	void setWindows(libcamera::Span<libcamera::Rectangle const> const &wins) override;
+	void setMode(AfMode mode) override;
+	AfMode getMode() const override;
+	bool setLensPosition(double dioptres, int32_t *hwpos) override;
+	std::optional<double> getLensPosition() const override;
+	void triggerScan() override;
+	void cancelScan() override;
+	void pause(AfPause pause) override;
+
+private:
+	enum class ScanState {
+		Idle = 0,
+		Trigger,
+		Pdaf,
+		Coarse,
+		Fine,
+		Settle
+	};
+
+	struct RangeDependentParams {
+		double focusMin;       		/* lower (far) limit in dipotres */
+		double focusMax;	       	/* upper (near) limit in dioptres */
+		double focusDefault;		/* default setting ("hyperfocal") */
+
+		RangeDependentParams();
+		void read(const libcamera::YamlObject &params);
+	};
+
+	struct SpeedDependentParams {
+		double stepCoarse;		/* used for scans */
+		double stepFine;		/* used for scans */
+		double contrastRatio;		/* used for scan termination and reporting */
+		double pdafGain;		/* coefficient for PDAF feedback loop */
+		double pdafSquelch;		/* PDAF stability parameter (device-specific) */
+		double maxSlew;			/* limit for lens movement per frame */
+		uint32_t pdafFrames;		/* number of iterations when triggered */
+		uint32_t dropoutFrames;		/* number of non-PDAF frames to switch to CDAF */
+		uint32_t stepFrames;		/* frames to skip in between steps of a scan */
+
+		SpeedDependentParams();
+		void read(const libcamera::YamlObject &params);
+	};
+
+	struct CfgParams {
+		RangeDependentParams ranges[AfRangeMax];
+		SpeedDependentParams speeds[AfSpeedMax];
+		uint32_t confEpsilon;	       	/* PDAF hysteresis threshold (sensor-specific) */
+		uint32_t confThresh;	       	/* PDAF confidence cell min (sensor-specific) */
+		uint32_t confClip;	       	/* PDAF confidence cell max (sensor-specific) */
+		uint32_t skipFrames;	       	/* frames to skip at start or modeswitch */
+		Pwl map;		       	/* converts dioptres -> lens driver position */
+
+		CfgParams();
+		int read(const libcamera::YamlObject &params);
+		void initialise();
+	};
+
+	struct ScanRecord {
+		double focus;
+		double contrast;
+		double phase;
+		double conf;
+	};
+
+	struct RegionWeights {
+		unsigned rows;
+		unsigned cols;
+		uint32_t sum;
+		std::vector<uint16_t> w;
+
+		RegionWeights()
+			: rows(0), cols(0), sum(0), w() {}
+	};
+
+	void computeWeights(RegionWeights *wgts, unsigned rows, unsigned cols);
+	void invalidateWeights();
+	bool getPhase(PdafRegions const &regions, double &phase, double &conf);
+	double getContrast(const FocusRegions &focusStats);
+	void doPDAF(double phase, double conf);
+	bool earlyTerminationByPhase(double phase);
+	double findPeak(unsigned index) const;
+	void doScan(double contrast, double phase, double conf);
+	void doAF(double contrast, double phase, double conf);
+	void updateLensPosition();
+	void startAF();
+	void startProgrammedScan();
+	void goIdle();
+
+	/* Configuration and settings */
+	CfgParams cfg_;
+	AfRange range_;
+	AfSpeed speed_;
+	AfMode mode_;
+	bool pauseFlag_;
+	libcamera::Rectangle statsRegion_;
+	std::vector<libcamera::Rectangle> windows_;
+	bool useWindows_;
+	RegionWeights phaseWeights_;
+	RegionWeights contrastWeights_;
+
+	/* Working state. */
+	ScanState scanState_;
+	bool initted_;
+	double ftarget_, fsmooth_;
+	double prevContrast_;
+	unsigned skipCount_, stepCount_, dropCount_;
+	unsigned scanMaxIndex_;
+	double scanMaxContrast_, scanMinContrast_;
+	std::vector<ScanRecord> scanData_;
+	AfState reportState_;
+};
+
+} // namespace RPiController

src/ipa/rpi/controller/rpi/agc.cpp

@@ -0,0 +1,922 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2019, Raspberry Pi Ltd
+ *
+ * agc.cpp - AGC/AEC control algorithm
+ */
+
+#include <algorithm>
+#include <map>
+#include <tuple>
+
+#include <libcamera/base/log.h>
+
+#include "../awb_status.h"
+#include "../device_status.h"
+#include "../histogram.h"
+#include "../lux_status.h"
+#include "../metadata.h"
+
+#include "agc.h"
+
+using namespace RPiController;
+using namespace libcamera;
+using libcamera::utils::Duration;
+using namespace std::literals::chrono_literals;
+
+LOG_DEFINE_CATEGORY(RPiAgc)
+
+#define NAME "rpi.agc"
+
+int AgcMeteringMode::read(const libcamera::YamlObject &params)
+{
+	const YamlObject &yamlWeights = params["weights"];
+
+	for (const auto &p : yamlWeights.asList()) {
+		auto value = p.get<double>();
+		if (!value)
+			return -EINVAL;
+		weights.push_back(*value);
+	}
+
+	return 0;
+}
+
+static std::tuple<int, std::string>
+readMeteringModes(std::map<std::string, AgcMeteringMode> &metering_modes,
+		  const libcamera::YamlObject &params)
+{
+	std::string first;
+	int ret;
+
+	for (const auto &[key, value] : params.asDict()) {
+		AgcMeteringMode meteringMode;
+		ret = meteringMode.read(value);
+		if (ret)
+			return { ret, {} };
+
+		metering_modes[key] = std::move(meteringMode);
+		if (first.empty())
+			first = key;
+	}
+
+	return { 0, first };
+}
+
+int AgcExposureMode::read(const libcamera::YamlObject &params)
+{
+	auto value = params["shutter"].getList<double>();
+	if (!value)
+		return -EINVAL;
+	std::transform(value->begin(), value->end(), std::back_inserter(shutter),
+		       [](double v) { return v * 1us; });
+
+	value = params["gain"].getList<double>();
+	if (!value)
+		return -EINVAL;
+	gain = std::move(*value);
+
+	if (shutter.size() < 2 || gain.size() < 2) {
+		LOG(RPiAgc, Error)
+			<< "AgcExposureMode: must have at least two entries in exposure profile";
+		return -EINVAL;
+	}
+
+	if (shutter.size() != gain.size()) {
+		LOG(RPiAgc, Error)
+			<< "AgcExposureMode: expect same number of exposure and gain entries in exposure profile";
+		return -EINVAL;
+	}
+
+	return 0;
+}
+
+static std::tuple<int, std::string>
+readExposureModes(std::map<std::string, AgcExposureMode> &exposureModes,
+		  const libcamera::YamlObject &params)
+{
+	std::string first;
+	int ret;
+
+	for (const auto &[key, value] : params.asDict()) {
+		AgcExposureMode exposureMode;
+		ret = exposureMode.read(value);
+		if (ret)
+			return { ret, {} };
+
+		exposureModes[key] = std::move(exposureMode);
+		if (first.empty())
+			first = key;
+	}
+
+	return { 0, first };
+}
+
+int AgcConstraint::read(const libcamera::YamlObject &params)
+{
+	std::string boundString = params["bound"].get<std::string>("");
+	transform(boundString.begin(), boundString.end(),
+		  boundString.begin(), ::toupper);
+	if (boundString != "UPPER" && boundString != "LOWER") {
+		LOG(RPiAgc, Error) << "AGC constraint type should be UPPER or LOWER";
+		return -EINVAL;
+	}
+	bound = boundString == "UPPER" ? Bound::UPPER : Bound::LOWER;
+
+	auto value = params["q_lo"].get<double>();
+	if (!value)
+		return -EINVAL;
+	qLo = *value;
+
+	value = params["q_hi"].get<double>();
+	if (!value)
+		return -EINVAL;
+	qHi = *value;
+
+	return yTarget.read(params["y_target"]);
+}
+
+static std::tuple<int, AgcConstraintMode>
+readConstraintMode(const libcamera::YamlObject &params)
+{
+	AgcConstraintMode mode;
+	int ret;
+
+	for (const auto &p : params.asList()) {
+		AgcConstraint constraint;
+		ret = constraint.read(p);
+		if (ret)
+			return { ret, {} };
+
+		mode.push_back(std::move(constraint));
+	}
+
+	return { 0, mode };
+}
+
+static std::tuple<int, std::string>
+readConstraintModes(std::map<std::string, AgcConstraintMode> &constraintModes,
+		    const libcamera::YamlObject &params)
+{
+	std::string first;
+	int ret;
+
+	for (const auto &[key, value] : params.asDict()) {
+		std::tie(ret, constraintModes[key]) = readConstraintMode(value);
+		if (ret)
+			return { ret, {} };
+
+		if (first.empty())
+			first = key;
+	}
+
+	return { 0, first };
+}
+
+int AgcConfig::read(const libcamera::YamlObject &params)
+{
+	LOG(RPiAgc, Debug) << "AgcConfig";
+	int ret;
+
+	std::tie(ret, defaultMeteringMode) =
+		readMeteringModes(meteringModes, params["metering_modes"]);
+	if (ret)
+		return ret;
+	std::tie(ret, defaultExposureMode) =
+		readExposureModes(exposureModes, params["exposure_modes"]);
+	if (ret)
+		return ret;
+	std::tie(ret, defaultConstraintMode) =
+		readConstraintModes(constraintModes, params["constraint_modes"]);
+	if (ret)
+		return ret;
+
+	ret = yTarget.read(params["y_target"]);
+	if (ret)
+		return ret;
+
+	speed = params["speed"].get<double>(0.2);
+	startupFrames = params["startup_frames"].get<uint16_t>(10);
+	convergenceFrames = params["convergence_frames"].get<unsigned int>(6);
+	fastReduceThreshold = params["fast_reduce_threshold"].get<double>(0.4);
+	baseEv = params["base_ev"].get<double>(1.0);
+
+	/* Start with quite a low value as ramping up is easier than ramping down. */
+	defaultExposureTime = params["default_exposure_time"].get<double>(1000) * 1us;
+	defaultAnalogueGain = params["default_analogue_gain"].get<double>(1.0);
+
+	return 0;
+}
+
+Agc::ExposureValues::ExposureValues()
+	: shutter(0s), analogueGain(0),
+	  totalExposure(0s), totalExposureNoDG(0s)
+{
+}
+
+Agc::Agc(Controller *controller)
+	: AgcAlgorithm(controller), meteringMode_(nullptr),
+	  exposureMode_(nullptr), constraintMode_(nullptr),
+	  frameCount_(0), lockCount_(0),
+	  lastTargetExposure_(0s), ev_(1.0), flickerPeriod_(0s),
+	  maxShutter_(0s), fixedShutter_(0s), fixedAnalogueGain_(0.0)
+{
+	memset(&awb_, 0, sizeof(awb_));
+	/*
+	 * Setting status_.totalExposureValue_ to zero initially tells us
+	 * it's not been calculated yet (i.e. Process hasn't yet run).
+	 */
+	memset(&status_, 0, sizeof(status_));
+	status_.ev = ev_;
+}
+
+char const *Agc::name() const
+{
+	return NAME;
+}
+
+int Agc::read(const libcamera::YamlObject &params)
+{
+	LOG(RPiAgc, Debug) << "Agc";
+
+	int ret = config_.read(params);
+	if (ret)
+		return ret;
+
+	const Size &size = getHardwareConfig().agcZoneWeights;
+	for (auto const &modes : config_.meteringModes) {
+		if (modes.second.weights.size() != size.width * size.height) {
+			LOG(RPiAgc, Error) << "AgcMeteringMode: Incorrect number of weights";
+			return -EINVAL;
+		}
+	}
+
+	/*
+	 * Set the config's defaults (which are the first ones it read) as our
+	 * current modes, until someone changes them.  (they're all known to
+	 * exist at this point)
+	 */
+	meteringModeName_ = config_.defaultMeteringMode;
+	meteringMode_ = &config_.meteringModes[meteringModeName_];
+	exposureModeName_ = config_.defaultExposureMode;
+	exposureMode_ = &config_.exposureModes[exposureModeName_];
+	constraintModeName_ = config_.defaultConstraintMode;
+	constraintMode_ = &config_.constraintModes[constraintModeName_];
+	/* Set up the "last shutter/gain" values, in case AGC starts "disabled". */
+	status_.shutterTime = config_.defaultExposureTime;
+	status_.analogueGain = config_.defaultAnalogueGain;
+	return 0;
+}
+
+void Agc::disableAuto()
+{
+	fixedShutter_ = status_.shutterTime;
+	fixedAnalogueGain_ = status_.analogueGain;
+}
+
+void Agc::enableAuto()
+{
+	fixedShutter_ = 0s;
+	fixedAnalogueGain_ = 0;
+}
+
+unsigned int Agc::getConvergenceFrames() const
+{
+	/*
+	 * If shutter and gain have been explicitly set, there is no
+	 * convergence to happen, so no need to drop any frames - return zero.
+	 */
+	if (fixedShutter_ && fixedAnalogueGain_)
+		return 0;
+	else
+		return config_.convergenceFrames;
+}
+
+void Agc::setEv(double ev)
+{
+	ev_ = ev;
+}
+
+void Agc::setFlickerPeriod(Duration flickerPeriod)
+{
+	flickerPeriod_ = flickerPeriod;
+}
+
+void Agc::setMaxShutter(Duration maxShutter)
+{
+	maxShutter_ = maxShutter;
+}
+
+void Agc::setFixedShutter(Duration fixedShutter)
+{
+	fixedShutter_ = fixedShutter;
+	/* Set this in case someone calls disableAuto() straight after. */
+	status_.shutterTime = limitShutter(fixedShutter_);
+}
+
+void Agc::setFixedAnalogueGain(double fixedAnalogueGain)
+{
+	fixedAnalogueGain_ = fixedAnalogueGain;
+	/* Set this in case someone calls disableAuto() straight after. */
+	status_.analogueGain = limitGain(fixedAnalogueGain);
+}
+
+void Agc::setMeteringMode(std::string const &meteringModeName)
+{
+	meteringModeName_ = meteringModeName;
+}
+
+void Agc::setExposureMode(std::string const &exposureModeName)
+{
+	exposureModeName_ = exposureModeName;
+}
+
+void Agc::setConstraintMode(std::string const &constraintModeName)
+{
+	constraintModeName_ = constraintModeName;
+}
+
+void Agc::switchMode(CameraMode const &cameraMode,
+		     Metadata *metadata)
+{
+	/* AGC expects the mode sensitivity always to be non-zero. */
+	ASSERT(cameraMode.sensitivity);
+
+	housekeepConfig();
+
+	/*
+	 * Store the mode in the local state. We must cache the sensitivity of
+	 * of the previous mode for the calculations below.
+	 */
+	double lastSensitivity = mode_.sensitivity;
+	mode_ = cameraMode;
+
+	Duration fixedShutter = limitShutter(fixedShutter_);
+	if (fixedShutter && fixedAnalogueGain_) {
+		/* We're going to reset the algorithm here with these fixed values. */
+
+		fetchAwbStatus(metadata);
+		double minColourGain = std::min({ awb_.gainR, awb_.gainG, awb_.gainB, 1.0 });
+		ASSERT(minColourGain != 0.0);
+
+		/* This is the equivalent of computeTargetExposure and applyDigitalGain. */
+		target_.totalExposureNoDG = fixedShutter_ * fixedAnalogueGain_;
+		target_.totalExposure = target_.totalExposureNoDG / minColourGain;
+
+		/* Equivalent of filterExposure. This resets any "history". */
+		filtered_ = target_;
+
+		/* Equivalent of divideUpExposure. */
+		filtered_.shutter = fixedShutter;
+		filtered_.analogueGain = fixedAnalogueGain_;
+	} else if (status_.totalExposureValue) {
+		/*
+		 * On a mode switch, various things could happen:
+		 * - the exposure profile might change
+		 * - a fixed exposure or gain might be set
+		 * - the new mode's sensitivity might be different
+		 * We cope with the last of these by scaling the target values. After
+		 * that we just need to re-divide the exposure/gain according to the
+		 * current exposure profile, which takes care of everything else.
+		 */
+
+		double ratio = lastSensitivity / cameraMode.sensitivity;
+		target_.totalExposureNoDG *= ratio;
+		target_.totalExposure *= ratio;
+		filtered_.totalExposureNoDG *= ratio;
+		filtered_.totalExposure *= ratio;
+
+		divideUpExposure();
+	} else {
+		/*
+		 * We come through here on startup, when at least one of the shutter
+		 * or gain has not been fixed. We must still write those values out so
+		 * that they will be applied immediately. We supply some arbitrary defaults
+		 * for any that weren't set.
+		 */
+
+		/* Equivalent of divideUpExposure. */
+		filtered_.shutter = fixedShutter ? fixedShutter : config_.defaultExposureTime;
+		filtered_.analogueGain = fixedAnalogueGain_ ? fixedAnalogueGain_ : config_.defaultAnalogueGain;
+	}
+
+	writeAndFinish(metadata, false);
+}
+
+void Agc::prepare(Metadata *imageMetadata)
+{
+	Duration totalExposureValue = status_.totalExposureValue;
+	AgcStatus delayedStatus;
+
+	if (!imageMetadata->get("agc.delayed_status", delayedStatus))
+		totalExposureValue = delayedStatus.totalExposureValue;
+
+	status_.digitalGain = 1.0;
+	fetchAwbStatus(imageMetadata); /* always fetch it so that Process knows it's been done */
+
+	if (status_.totalExposureValue) {
+		/* Process has run, so we have meaningful values. */
+		DeviceStatus deviceStatus;
+		if (imageMetadata->get("device.status", deviceStatus) == 0) {
+			Duration actualExposure = deviceStatus.shutterSpeed *
+						  deviceStatus.analogueGain;
+			if (actualExposure) {
+				status_.digitalGain = totalExposureValue / actualExposure;
+				LOG(RPiAgc, Debug) << "Want total exposure " << totalExposureValue;
+				/*
+				 * Never ask for a gain < 1.0, and also impose
+				 * some upper limit. Make it customisable?
+				 */
+				status_.digitalGain = std::max(1.0, std::min(status_.digitalGain, 4.0));
+				LOG(RPiAgc, Debug) << "Actual exposure " << actualExposure;
+				LOG(RPiAgc, Debug) << "Use digitalGain " << status_.digitalGain;
+				LOG(RPiAgc, Debug) << "Effective exposure "
+						   << actualExposure * status_.digitalGain;
+				/* Decide whether AEC/AGC has converged. */
+				updateLockStatus(deviceStatus);
+			}
+		} else
+			LOG(RPiAgc, Warning) << name() << ": no device metadata";
+		imageMetadata->set("agc.status", status_);
+	}
+}
+
+void Agc::process(StatisticsPtr &stats, Metadata *imageMetadata)
+{
+	frameCount_++;
+	/*
+	 * First a little bit of housekeeping, fetching up-to-date settings and
+	 * configuration, that kind of thing.
+	 */
+	housekeepConfig();
+	/* Get the current exposure values for the frame that's just arrived. */
+	fetchCurrentExposure(imageMetadata);
+	/* Compute the total gain we require relative to the current exposure. */
+	double gain, targetY;
+	computeGain(stats, imageMetadata, gain, targetY);
+	/* Now compute the target (final) exposure which we think we want. */
+	computeTargetExposure(gain);
+	/*
+	 * Some of the exposure has to be applied as digital gain, so work out
+	 * what that is. This function also tells us whether it's decided to
+	 * "desaturate" the image more quickly.
+	 */
+	bool desaturate = applyDigitalGain(gain, targetY);
+	/* The results have to be filtered so as not to change too rapidly. */
+	filterExposure(desaturate);
+	/*
+	 * The last thing is to divide up the exposure value into a shutter time
+	 * and analogue gain, according to the current exposure mode.
+	 */
+	divideUpExposure();
+	/* Finally advertise what we've done. */
+	writeAndFinish(imageMetadata, desaturate);
+}
+
+void Agc::updateLockStatus(DeviceStatus const &deviceStatus)
+{
+	const double errorFactor = 0.10; /* make these customisable? */
+	const int maxLockCount = 5;
+	/* Reset "lock count" when we exceed this multiple of errorFactor */
+	const double resetMargin = 1.5;
+
+	/* Add 200us to the exposure time error to allow for line quantisation. */
+	Duration exposureError = lastDeviceStatus_.shutterSpeed * errorFactor + 200us;
+	double gainError = lastDeviceStatus_.analogueGain * errorFactor;
+	Duration targetError = lastTargetExposure_ * errorFactor;
+
+	/*
+	 * Note that we don't know the exposure/gain limits of the sensor, so
+	 * the values we keep requesting may be unachievable. For this reason
+	 * we only insist that we're close to values in the past few frames.
+	 */
+	if (deviceStatus.shutterSpeed > lastDeviceStatus_.shutterSpeed - exposureError &&
+	    deviceStatus.shutterSpeed < lastDeviceStatus_.shutterSpeed + exposureError &&
+	    deviceStatus.analogueGain > lastDeviceStatus_.analogueGain - gainError &&
+	    deviceStatus.analogueGain < lastDeviceStatus_.analogueGain + gainError &&
+	    status_.targetExposureValue > lastTargetExposure_ - targetError &&
+	    status_.targetExposureValue < lastTargetExposure_ + targetError)
+		lockCount_ = std::min(lockCount_ + 1, maxLockCount);
+	else if (deviceStatus.shutterSpeed < lastDeviceStatus_.shutterSpeed - resetMargin * exposureError ||
+		 deviceStatus.shutterSpeed > lastDeviceStatus_.shutterSpeed + resetMargin * exposureError ||
+		 deviceStatus.analogueGain < lastDeviceStatus_.analogueGain - resetMargin * gainError ||
+		 deviceStatus.analogueGain > lastDeviceStatus_.analogueGain + resetMargin * gainError ||
+		 status_.targetExposureValue < lastTargetExposure_ - resetMargin * targetError ||
+		 status_.targetExposureValue > lastTargetExposure_ + resetMargin * targetError)
+		lockCount_ = 0;
+
+	lastDeviceStatus_ = deviceStatus;
+	lastTargetExposure_ = status_.targetExposureValue;
+
+	LOG(RPiAgc, Debug) << "Lock count updated to " << lockCount_;
+	status_.locked = lockCount_ == maxLockCount;
+}
+
+static void copyString(std::string const &s, char *d, size_t size)
+{
+	size_t length = s.copy(d, size - 1);
+	d[length] = '\0';
+}
+
+void Agc::housekeepConfig()
+{
+	/* First fetch all the up-to-date settings, so no one else has to do it. */
+	status_.ev = ev_;
+	status_.fixedShutter = limitShutter(fixedShutter_);
+	status_.fixedAnalogueGain = fixedAnalogueGain_;
+	status_.flickerPeriod = flickerPeriod_;
+	LOG(RPiAgc, Debug) << "ev " << status_.ev << " fixedShutter "
+			   << status_.fixedShutter << " fixedAnalogueGain "
+			   << status_.fixedAnalogueGain;
+	/*
+	 * Make sure the "mode" pointers point to the up-to-date things, if
+	 * they've changed.
+	 */
+	if (strcmp(meteringModeName_.c_str(), status_.meteringMode)) {
+		auto it = config_.meteringModes.find(meteringModeName_);
+		if (it == config_.meteringModes.end())
+			LOG(RPiAgc, Fatal) << "No metering mode " << meteringModeName_;
+		meteringMode_ = &it->second;
+		copyString(meteringModeName_, status_.meteringMode,
+			   sizeof(status_.meteringMode));
+	}
+	if (strcmp(exposureModeName_.c_str(), status_.exposureMode)) {
+		auto it = config_.exposureModes.find(exposureModeName_);
+		if (it == config_.exposureModes.end())
+			LOG(RPiAgc, Fatal) << "No exposure profile " << exposureModeName_;
+		exposureMode_ = &it->second;
+		copyString(exposureModeName_, status_.exposureMode,
+			   sizeof(status_.exposureMode));
+	}
+	if (strcmp(constraintModeName_.c_str(), status_.constraintMode)) {
+		auto it =
+			config_.constraintModes.find(constraintModeName_);
+		if (it == config_.constraintModes.end())
+			LOG(RPiAgc, Fatal) << "No constraint list " << constraintModeName_;
+		constraintMode_ = &it->second;
+		copyString(constraintModeName_, status_.constraintMode,
+			   sizeof(status_.constraintMode));
+	}
+	LOG(RPiAgc, Debug) << "exposureMode "
+			   << exposureModeName_ << " constraintMode "
+			   << constraintModeName_ << " meteringMode "
+			   << meteringModeName_;
+}
+
+void Agc::fetchCurrentExposure(Metadata *imageMetadata)
+{
+	std::unique_lock<Metadata> lock(*imageMetadata);
+	DeviceStatus *deviceStatus =
+		imageMetadata->getLocked<DeviceStatus>("device.status");
+	if (!deviceStatus)
+		LOG(RPiAgc, Fatal) << "No device metadata";
+	current_.shutter = deviceStatus->shutterSpeed;
+	current_.analogueGain = deviceStatus->analogueGain;
+	AgcStatus *agcStatus =
+		imageMetadata->getLocked<AgcStatus>("agc.status");
+	current_.totalExposure = agcStatus ? agcStatus->totalExposureValue : 0s;
+	current_.totalExposureNoDG = current_.shutter * current_.analogueGain;
+}
+
+void Agc::fetchAwbStatus(Metadata *imageMetadata)
+{
+	awb_.gainR = 1.0; /* in case not found in metadata */
+	awb_.gainG = 1.0;
+	awb_.gainB = 1.0;
+	if (imageMetadata->get("awb.status", awb_) != 0)
+		LOG(RPiAgc, Debug) << "No AWB status found";
+}
+
+static double computeInitialY(StatisticsPtr &stats, AwbStatus const &awb,
+			      std::vector<double> &weights, double gain)
+{
+	constexpr uint64_t maxVal = 1 << Statistics::NormalisationFactorPow2;
+
+	ASSERT(weights.size() == stats->agcRegions.numRegions());
+
+	/*
+	 * Note how the calculation below means that equal weights give you
+	 * "average" metering (i.e. all pixels equally important).
+	 */
+	double rSum = 0, gSum = 0, bSum = 0, pixelSum = 0;
+	for (unsigned int i = 0; i < stats->agcRegions.numRegions(); i++) {
+		auto &region = stats->agcRegions.get(i);
+		double rAcc = std::min<double>(region.val.rSum * gain, (maxVal - 1) * region.counted);
+		double gAcc = std::min<double>(region.val.gSum * gain, (maxVal - 1) * region.counted);
+		double bAcc = std::min<double>(region.val.bSum * gain, (maxVal - 1) * region.counted);
+		rSum += rAcc * weights[i];
+		gSum += gAcc * weights[i];
+		bSum += bAcc * weights[i];
+		pixelSum += region.counted * weights[i];
+	}
+	if (pixelSum == 0.0) {
+		LOG(RPiAgc, Warning) << "computeInitialY: pixelSum is zero";
+		return 0;
+	}
+	double ySum = rSum * awb.gainR * .299 +
+		      gSum * awb.gainG * .587 +
+		      bSum * awb.gainB * .114;
+	return ySum / pixelSum / maxVal;
+}
+
+/*
+ * We handle extra gain through EV by adjusting our Y targets. However, you
+ * simply can't monitor histograms once they get very close to (or beyond!)
+ * saturation, so we clamp the Y targets to this value. It does mean that EV
+ * increases don't necessarily do quite what you might expect in certain
+ * (contrived) cases.
+ */
+
+static constexpr double EvGainYTargetLimit = 0.9;
+
+static double constraintComputeGain(AgcConstraint &c, const Histogram &h, double lux,
+				    double evGain, double &targetY)
+{
+	targetY = c.yTarget.eval(c.yTarget.domain().clip(lux));
+	targetY = std::min(EvGainYTargetLimit, targetY * evGain);
+	double iqm = h.interQuantileMean(c.qLo, c.qHi);
+	return (targetY * h.bins()) / iqm;
+}
+
+void Agc::computeGain(StatisticsPtr &statistics, Metadata *imageMetadata,
+		      double &gain, double &targetY)
+{
+	struct LuxStatus lux = {};
+	lux.lux = 400; /* default lux level to 400 in case no metadata found */
+	if (imageMetadata->get("lux.status", lux) != 0)
+		LOG(RPiAgc, Warning) << "No lux level found";
+	const Histogram &h = statistics->yHist;
+	double evGain = status_.ev * config_.baseEv;
+	/*
+	 * The initial gain and target_Y come from some of the regions. After
+	 * that we consider the histogram constraints.
+	 */
+	targetY = config_.yTarget.eval(config_.yTarget.domain().clip(lux.lux));
+	targetY = std::min(EvGainYTargetLimit, targetY * evGain);
+
+	/*
+	 * Do this calculation a few times as brightness increase can be
+	 * non-linear when there are saturated regions.
+	 */
+	gain = 1.0;
+	for (int i = 0; i < 8; i++) {
+		double initialY = computeInitialY(statistics, awb_, meteringMode_->weights, gain);
+		double extraGain = std::min(10.0, targetY / (initialY + .001));
+		gain *= extraGain;
+		LOG(RPiAgc, Debug) << "Initial Y " << initialY << " target " << targetY
+				   << " gives gain " << gain;
+		if (extraGain < 1.01) /* close enough */
+			break;
+	}
+
+	for (auto &c : *constraintMode_) {
+		double newTargetY;
+		double newGain = constraintComputeGain(c, h, lux.lux, evGain, newTargetY);
+		LOG(RPiAgc, Debug) << "Constraint has target_Y "
+				   << newTargetY << " giving gain " << newGain;
+		if (c.bound == AgcConstraint::Bound::LOWER && newGain > gain) {
+			LOG(RPiAgc, Debug) << "Lower bound constraint adopted";
+			gain = newGain;
+			targetY = newTargetY;
+		} else if (c.bound == AgcConstraint::Bound::UPPER && newGain < gain) {
+			LOG(RPiAgc, Debug) << "Upper bound constraint adopted";
+			gain = newGain;
+			targetY = newTargetY;
+		}
+	}
+	LOG(RPiAgc, Debug) << "Final gain " << gain << " (target_Y " << targetY << " ev "
+			   << status_.ev << " base_ev " << config_.baseEv
+			   << ")";
+}
+
+void Agc::computeTargetExposure(double gain)
+{
+	if (status_.fixedShutter && status_.fixedAnalogueGain) {
+		/*
+		 * When ag and shutter are both fixed, we need to drive the
+		 * total exposure so that we end up with a digital gain of at least
+		 * 1/minColourGain. Otherwise we'd desaturate channels causing
+		 * white to go cyan or magenta.
+		 */
+		double minColourGain = std::min({ awb_.gainR, awb_.gainG, awb_.gainB, 1.0 });
+		ASSERT(minColourGain != 0.0);
+		target_.totalExposure =
+			status_.fixedShutter * status_.fixedAnalogueGain / minColourGain;
+	} else {
+		/*
+		 * The statistics reflect the image without digital gain, so the final
+		 * total exposure we're aiming for is:
+		 */
+		target_.totalExposure = current_.totalExposureNoDG * gain;
+		/* The final target exposure is also limited to what the exposure mode allows. */
+		Duration maxShutter = status_.fixedShutter
+					      ? status_.fixedShutter
+					      : exposureMode_->shutter.back();
+		maxShutter = limitShutter(maxShutter);
+		Duration maxTotalExposure =
+			maxShutter *
+			(status_.fixedAnalogueGain != 0.0
+				 ? status_.fixedAnalogueGain
+				 : exposureMode_->gain.back());
+		target_.totalExposure = std::min(target_.totalExposure, maxTotalExposure);
+	}
+	LOG(RPiAgc, Debug) << "Target totalExposure " << target_.totalExposure;
+}
+
+bool Agc::applyDigitalGain(double gain, double targetY)
+{
+	double minColourGain = std::min({ awb_.gainR, awb_.gainG, awb_.gainB, 1.0 });
+	ASSERT(minColourGain != 0.0);
+	double dg = 1.0 / minColourGain;
+	/*
+	 * I think this pipeline subtracts black level and rescales before we
+	 * get the stats, so no need to worry about it.
+	 */
+	LOG(RPiAgc, Debug) << "after AWB, target dg " << dg << " gain " << gain
+			   << " target_Y " << targetY;
+	/*
+	 * Finally, if we're trying to reduce exposure but the target_Y is
+	 * "close" to 1.0, then the gain computed for that constraint will be
+	 * only slightly less than one, because the measured Y can never be
+	 * larger than 1.0. When this happens, demand a large digital gain so
+	 * that the exposure can be reduced, de-saturating the image much more
+	 * quickly (and we then approach the correct value more quickly from
+	 * below).
+	 */
+	bool desaturate = targetY > config_.fastReduceThreshold &&
+			  gain < sqrt(targetY);
+	if (desaturate)
+		dg /= config_.fastReduceThreshold;
+	LOG(RPiAgc, Debug) << "Digital gain " << dg << " desaturate? " << desaturate;
+	target_.totalExposureNoDG = target_.totalExposure / dg;
+	LOG(RPiAgc, Debug) << "Target totalExposureNoDG " << target_.totalExposureNoDG;
+	return desaturate;
+}
+
+void Agc::filterExposure(bool desaturate)
+{
+	double speed = config_.speed;
+	/*
+	 * AGC adapts instantly if both shutter and gain are directly specified
+	 * or we're in the startup phase.
+	 */
+	if ((status_.fixedShutter && status_.fixedAnalogueGain) ||
+	    frameCount_ <= config_.startupFrames)
+		speed = 1.0;
+	if (!filtered_.totalExposure) {
+		filtered_.totalExposure = target_.totalExposure;
+		filtered_.totalExposureNoDG = target_.totalExposureNoDG;
+	} else {
+		/*
+		 * If close to the result go faster, to save making so many
+		 * micro-adjustments on the way. (Make this customisable?)
+		 */
+		if (filtered_.totalExposure < 1.2 * target_.totalExposure &&
+		    filtered_.totalExposure > 0.8 * target_.totalExposure)
+			speed = sqrt(speed);
+		filtered_.totalExposure = speed * target_.totalExposure +
+					  filtered_.totalExposure * (1.0 - speed);
+		/*
+		 * When desaturing, take a big jump down in totalExposureNoDG,
+		 * which we'll hide with digital gain.
+		 */
+		if (desaturate)
+			filtered_.totalExposureNoDG =
+				target_.totalExposureNoDG;
+		else
+			filtered_.totalExposureNoDG =
+				speed * target_.totalExposureNoDG +
+				filtered_.totalExposureNoDG * (1.0 - speed);
+	}
+	/*
+	 * We can't let the totalExposureNoDG exposure deviate too far below the
+	 * total exposure, as there might not be enough digital gain available
+	 * in the ISP to hide it (which will cause nasty oscillation).
+	 */
+	if (filtered_.totalExposureNoDG <
+	    filtered_.totalExposure * config_.fastReduceThreshold)
+		filtered_.totalExposureNoDG = filtered_.totalExposure * config_.fastReduceThreshold;
+	LOG(RPiAgc, Debug) << "After filtering, totalExposure " << filtered_.totalExposure
+			   << " no dg " << filtered_.totalExposureNoDG;
+}
+
+void Agc::divideUpExposure()
+{
+	/*
+	 * Sending the fixed shutter/gain cases through the same code may seem
+	 * unnecessary, but it will make more sense when extend this to cover
+	 * variable aperture.
+	 */
+	Duration exposureValue = filtered_.totalExposureNoDG;
+	Duration shutterTime;
+	double analogueGain;
+	shutterTime = status_.fixedShutter ? status_.fixedShutter
+					   : exposureMode_->shutter[0];
+	shutterTime = limitShutter(shutterTime);
+	analogueGain = status_.fixedAnalogueGain != 0.0 ? status_.fixedAnalogueGain
+							: exposureMode_->gain[0];
+	analogueGain = limitGain(analogueGain);
+	if (shutterTime * analogueGain < exposureValue) {
+		for (unsigned int stage = 1;
+		     stage < exposureMode_->gain.size(); stage++) {
+			if (!status_.fixedShutter) {
+				Duration stageShutter =
+					limitShutter(exposureMode_->shutter[stage]);
+				if (stageShutter * analogueGain >= exposureValue) {
+					shutterTime = exposureValue / analogueGain;
+					break;
+				}
+				shutterTime = stageShutter;
+			}
+			if (status_.fixedAnalogueGain == 0.0) {
+				if (exposureMode_->gain[stage] * shutterTime >= exposureValue) {
+					analogueGain = exposureValue / shutterTime;
+					break;
+				}
+				analogueGain = exposureMode_->gain[stage];
+				analogueGain = limitGain(analogueGain);
+			}
+		}
+	}
+	LOG(RPiAgc, Debug) << "Divided up shutter and gain are " << shutterTime << " and "
+			   << analogueGain;
+	/*
+	 * Finally adjust shutter time for flicker avoidance (require both
+	 * shutter and gain not to be fixed).
+	 */
+	if (!status_.fixedShutter && !status_.fixedAnalogueGain &&
+	    status_.flickerPeriod) {
+		int flickerPeriods = shutterTime / status_.flickerPeriod;
+		if (flickerPeriods) {
+			Duration newShutterTime = flickerPeriods * status_.flickerPeriod;
+			analogueGain *= shutterTime / newShutterTime;
+			/*
+			 * We should still not allow the ag to go over the
+			 * largest value in the exposure mode. Note that this
+			 * may force more of the total exposure into the digital
+			 * gain as a side-effect.
+			 */
+			analogueGain = std::min(analogueGain, exposureMode_->gain.back());
+			analogueGain = limitGain(analogueGain);
+			shutterTime = newShutterTime;
+		}
+		LOG(RPiAgc, Debug) << "After flicker avoidance, shutter "
+				   << shutterTime << " gain " << analogueGain;
+	}
+	filtered_.shutter = shutterTime;
+	filtered_.analogueGain = analogueGain;
+}
+
+void Agc::writeAndFinish(Metadata *imageMetadata, bool desaturate)
+{
+	status_.totalExposureValue = filtered_.totalExposure;
+	status_.targetExposureValue = desaturate ? 0s : target_.totalExposureNoDG;
+	status_.shutterTime = filtered_.shutter;
+	status_.analogueGain = filtered_.analogueGain;
+	/*
+	 * Write to metadata as well, in case anyone wants to update the camera
+	 * immediately.
+	 */
+	imageMetadata->set("agc.status", status_);
+	LOG(RPiAgc, Debug) << "Output written, total exposure requested is "
+			   << filtered_.totalExposure;
+	LOG(RPiAgc, Debug) << "Camera exposure update: shutter time " << filtered_.shutter
+			   << " analogue gain " << filtered_.analogueGain;
+}
+
+Duration Agc::limitShutter(Duration shutter)
+{
+	/*
+	 * shutter == 0 is a special case for fixed shutter values, and must pass
+	 * through unchanged
+	 */
+	if (!shutter)
+		return shutter;
+
+	shutter = std::clamp(shutter, mode_.minShutter, maxShutter_);
+	return shutter;
+}
+
+double Agc::limitGain(double gain) const
+{
+	/*
+	 * Only limit the lower bounds of the gain value to what the sensor limits.
+	 * The upper bound on analogue gain will be made up with additional digital
+	 * gain applied by the ISP.
+	 *
+	 * gain == 0.0 is a special case for fixed shutter values, and must pass
+	 * through unchanged
+	 */
+	if (!gain)
+		return gain;
+
+	gain = std::max(gain, mode_.minAnalogueGain);
+	return gain;
+}
+
+/* Register algorithm with the system. */
+static Algorithm *create(Controller *controller)
+{
+	return (Algorithm *)new Agc(controller);
+}
+static RegisterAlgorithm reg(NAME, &create);

src/ipa/rpi/controller/rpi/agc.h

@@ -0,0 +1,133 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2019, Raspberry Pi Ltd
+ *
+ * agc.h - AGC/AEC control algorithm
+ */
+#pragma once
+
+#include <vector>
+#include <mutex>
+
+#include <libcamera/base/utils.h>
+
+#include "../agc_algorithm.h"
+#include "../agc_status.h"
+#include "../pwl.h"
+
+/* This is our implementation of AGC. */
+
+namespace RPiController {
+
+struct AgcMeteringMode {
+	std::vector<double> weights;
+	int read(const libcamera::YamlObject &params);
+};
+
+struct AgcExposureMode {
+	std::vector<libcamera::utils::Duration> shutter;
+	std::vector<double> gain;
+	int read(const libcamera::YamlObject &params);
+};
+
+struct AgcConstraint {
+	enum class Bound { LOWER = 0, UPPER = 1 };
+	Bound bound;
+	double qLo;
+	double qHi;
+	Pwl yTarget;
+	int read(const libcamera::YamlObject &params);
+};
+
+typedef std::vector<AgcConstraint> AgcConstraintMode;
+
+struct AgcConfig {
+	int read(const libcamera::YamlObject &params);
+	std::map<std::string, AgcMeteringMode> meteringModes;
+	std::map<std::string, AgcExposureMode> exposureModes;
+	std::map<std::string, AgcConstraintMode> constraintModes;
+	Pwl yTarget;
+	double speed;
+	uint16_t startupFrames;
+	unsigned int convergenceFrames;
+	double maxChange;
+	double minChange;
+	double fastReduceThreshold;
+	double speedUpThreshold;
+	std::string defaultMeteringMode;
+	std::string defaultExposureMode;
+	std::string defaultConstraintMode;
+	double baseEv;
+	libcamera::utils::Duration defaultExposureTime;
+	double defaultAnalogueGain;
+};
+
+class Agc : public AgcAlgorithm
+{
+public:
+	Agc(Controller *controller);
+	char const *name() const override;
+	int read(const libcamera::YamlObject &params) override;
+	unsigned int getConvergenceFrames() const override;
+	void setEv(double ev) override;
+	void setFlickerPeriod(libcamera::utils::Duration flickerPeriod) override;
+	void setMaxShutter(libcamera::utils::Duration maxShutter) override;
+	void setFixedShutter(libcamera::utils::Duration fixedShutter) override;
+	void setFixedAnalogueGain(double fixedAnalogueGain) override;
+	void setMeteringMode(std::string const &meteringModeName) override;
+	void setExposureMode(std::string const &exposureModeName) override;
+	void setConstraintMode(std::string const &contraintModeName) override;
+	void enableAuto() override;
+	void disableAuto() override;
+	void switchMode(CameraMode const &cameraMode, Metadata *metadata) override;
+	void prepare(Metadata *imageMetadata) override;
+	void process(StatisticsPtr &stats, Metadata *imageMetadata) override;
+
+private:
+	void updateLockStatus(DeviceStatus const &deviceStatus);
+	AgcConfig config_;
+	void housekeepConfig();
+	void fetchCurrentExposure(Metadata *imageMetadata);
+	void fetchAwbStatus(Metadata *imageMetadata);
+	void computeGain(StatisticsPtr &statistics, Metadata *imageMetadata,
+			 double &gain, double &targetY);
+	void computeTargetExposure(double gain);
+	bool applyDigitalGain(double gain, double targetY);
+	void filterExposure(bool desaturate);
+	void divideUpExposure();
+	void writeAndFinish(Metadata *imageMetadata, bool desaturate);
+	libcamera::utils::Duration limitShutter(libcamera::utils::Duration shutter);
+	double limitGain(double gain) const;
+	AgcMeteringMode *meteringMode_;
+	AgcExposureMode *exposureMode_;
+	AgcConstraintMode *constraintMode_;
+	CameraMode mode_;
+	uint64_t frameCount_;
+	AwbStatus awb_;
+	struct ExposureValues {
+		ExposureValues();
+
+		libcamera::utils::Duration shutter;
+		double analogueGain;
+		libcamera::utils::Duration totalExposure;
+		libcamera::utils::Duration totalExposureNoDG; /* without digital gain */
+	};
+	ExposureValues current_;  /* values for the current frame */
+	ExposureValues target_;   /* calculate the values we want here */
+	ExposureValues filtered_; /* these values are filtered towards target */
+	AgcStatus status_;
+	int lockCount_;
+	DeviceStatus lastDeviceStatus_;
+	libcamera::utils::Duration lastTargetExposure_;
+	/* Below here the "settings" that applications can change. */
+	std::string meteringModeName_;
+	std::string exposureModeName_;
+	std::string constraintModeName_;
+	double ev_;
+	libcamera::utils::Duration flickerPeriod_;
+	libcamera::utils::Duration maxShutter_;
+	libcamera::utils::Duration fixedShutter_;
+	double fixedAnalogueGain_;
+};
+
+} /* namespace RPiController */

src/ipa/rpi/controller/rpi/alsc.cpp

@@ -0,0 +1,865 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2019, Raspberry Pi Ltd
+ *
+ * alsc.cpp - ALSC (auto lens shading correction) control algorithm
+ */
+
+#include <algorithm>
+#include <functional>
+#include <math.h>
+#include <numeric>
+
+#include <libcamera/base/log.h>
+#include <libcamera/base/span.h>
+
+#include "../awb_status.h"
+#include "alsc.h"
+
+/* Raspberry Pi ALSC (Auto Lens Shading Correction) algorithm. */
+
+using namespace RPiController;
+using namespace libcamera;
+
+LOG_DEFINE_CATEGORY(RPiAlsc)
+
+#define NAME "rpi.alsc"
+
+static const double InsufficientData = -1.0;
+
+Alsc::Alsc(Controller *controller)
+	: Algorithm(controller)
+{
+	asyncAbort_ = asyncStart_ = asyncStarted_ = asyncFinished_ = false;
+	asyncThread_ = std::thread(std::bind(&Alsc::asyncFunc, this));
+}
+
+Alsc::~Alsc()
+{
+	{
+		std::lock_guard<std::mutex> lock(mutex_);
+		asyncAbort_ = true;
+	}
+	asyncSignal_.notify_one();
+	asyncThread_.join();
+}
+
+char const *Alsc::name() const
+{
+	return NAME;
+}
+
+static int generateLut(Array2D<double> &lut, const libcamera::YamlObject &params)
+{
+	/* These must be signed ints for the co-ordinate calculations below. */
+	int X = lut.dimensions().width, Y = lut.dimensions().height;
+	double cstrength = params["corner_strength"].get<double>(2.0);
+	if (cstrength <= 1.0) {
+		LOG(RPiAlsc, Error) << "corner_strength must be > 1.0";
+		return -EINVAL;
+	}
+
+	double asymmetry = params["asymmetry"].get<double>(1.0);
+	if (asymmetry < 0) {
+		LOG(RPiAlsc, Error) << "asymmetry must be >= 0";
+		return -EINVAL;
+	}
+
+	double f1 = cstrength - 1, f2 = 1 + sqrt(cstrength);
+	double R2 = X * Y / 4 * (1 + asymmetry * asymmetry);
+	int num = 0;
+	for (int y = 0; y < Y; y++) {
+		for (int x = 0; x < X; x++) {
+			double dy = y - Y / 2 + 0.5,
+			       dx = (x - X / 2 + 0.5) * asymmetry;
+			double r2 = (dx * dx + dy * dy) / R2;
+			lut[num++] =
+				(f1 * r2 + f2) * (f1 * r2 + f2) /
+				(f2 * f2); /* this reproduces the cos^4 rule */
+		}
+	}
+	return 0;
+}
+
+static int readLut(Array2D<double> &lut, const libcamera::YamlObject &params)
+{
+	if (params.size() != lut.size()) {
+		LOG(RPiAlsc, Error) << "Invalid number of entries in LSC table";
+		return -EINVAL;
+	}
+
+	int num = 0;
+	for (const auto &p : params.asList()) {
+		auto value = p.get<double>();
+		if (!value)
+			return -EINVAL;
+		lut[num++] = *value;
+	}
+
+	return 0;
+}
+
+static int readCalibrations(std::vector<AlscCalibration> &calibrations,
+			    const libcamera::YamlObject &params,
+			    std::string const &name, const Size &size)
+{
+	if (params.contains(name)) {
+		double lastCt = 0;
+		for (const auto &p : params[name].asList()) {
+			auto value = p["ct"].get<double>();
+			if (!value)
+				return -EINVAL;
+			double ct = *value;
+			if (ct <= lastCt) {
+				LOG(RPiAlsc, Error)
+					<< "Entries in " << name << " must be in increasing ct order";
+				return -EINVAL;
+			}
+			AlscCalibration calibration;
+			calibration.ct = lastCt = ct;
+
+			const libcamera::YamlObject &table = p["table"];
+			if (table.size() != size.width * size.height) {
+				LOG(RPiAlsc, Error)
+					<< "Incorrect number of values for ct "
+					<< ct << " in " << name;
+				return -EINVAL;
+			}
+
+			int num = 0;
+			calibration.table.resize(size);
+			for (const auto &elem : table.asList()) {
+				value = elem.get<double>();
+				if (!value)
+					return -EINVAL;
+				calibration.table[num++] = *value;
+			}
+
+			calibrations.push_back(std::move(calibration));
+			LOG(RPiAlsc, Debug)
+				<< "Read " << name << " calibration for ct " << ct;
+		}
+	}
+	return 0;
+}
+
+int Alsc::read(const libcamera::YamlObject &params)
+{
+	config_.tableSize = getHardwareConfig().awbRegions;
+	config_.framePeriod = params["frame_period"].get<uint16_t>(12);
+	config_.startupFrames = params["startup_frames"].get<uint16_t>(10);
+	config_.speed = params["speed"].get<double>(0.05);
+	double sigma = params["sigma"].get<double>(0.01);
+	config_.sigmaCr = params["sigma_Cr"].get<double>(sigma);
+	config_.sigmaCb = params["sigma_Cb"].get<double>(sigma);
+	config_.minCount = params["min_count"].get<double>(10.0);
+	config_.minG = params["min_G"].get<uint16_t>(50);
+	config_.omega = params["omega"].get<double>(1.3);
+	config_.nIter = params["n_iter"].get<uint32_t>(config_.tableSize.width + config_.tableSize.height);
+	config_.luminanceStrength =
+		params["luminance_strength"].get<double>(1.0);
+
+	config_.luminanceLut.resize(config_.tableSize, 1.0);
+	int ret = 0;
+
+	if (params.contains("corner_strength"))
+		ret = generateLut(config_.luminanceLut, params);
+	else if (params.contains("luminance_lut"))
+		ret = readLut(config_.luminanceLut, params["luminance_lut"]);
+	else
+		LOG(RPiAlsc, Warning)
+			<< "no luminance table - assume unity everywhere";
+	if (ret)
+		return ret;
+
+	ret = readCalibrations(config_.calibrationsCr, params, "calibrations_Cr",
+			       config_.tableSize);
+	if (ret)
+		return ret;
+	ret = readCalibrations(config_.calibrationsCb, params, "calibrations_Cb",
+			       config_.tableSize);
+	if (ret)
+		return ret;
+
+	config_.defaultCt = params["default_ct"].get<double>(4500.0);
+	config_.threshold = params["threshold"].get<double>(1e-3);
+	config_.lambdaBound = params["lambda_bound"].get<double>(0.05);
+
+	return 0;
+}
+
+static double getCt(Metadata *metadata, double defaultCt);
+static void getCalTable(double ct, std::vector<AlscCalibration> const &calibrations,
+			Array2D<double> &calTable);
+static void resampleCalTable(const Array2D<double> &calTableIn, CameraMode const &cameraMode,
+			     Array2D<double> &calTableOut);
+static void compensateLambdasForCal(const Array2D<double> &calTable,
+				    const Array2D<double> &oldLambdas,
+				    Array2D<double> &newLambdas);
+static void addLuminanceToTables(std::array<Array2D<double>, 3> &results,
+				 const Array2D<double> &lambdaR, double lambdaG,
+				 const Array2D<double> &lambdaB,
+				 const Array2D<double> &luminanceLut,
+				 double luminanceStrength);
+
+void Alsc::initialise()
+{
+	frameCount2_ = frameCount_ = framePhase_ = 0;
+	firstTime_ = true;
+	ct_ = config_.defaultCt;
+
+	const size_t XY = config_.tableSize.width * config_.tableSize.height;
+
+	for (auto &r : syncResults_)
+		r.resize(config_.tableSize);
+	for (auto &r : prevSyncResults_)
+		r.resize(config_.tableSize);
+	for (auto &r : asyncResults_)
+		r.resize(config_.tableSize);
+
+	luminanceTable_.resize(config_.tableSize);
+	asyncLambdaR_.resize(config_.tableSize);
+	asyncLambdaB_.resize(config_.tableSize);
+	/* The lambdas are initialised in the SwitchMode. */
+	lambdaR_.resize(config_.tableSize);
+	lambdaB_.resize(config_.tableSize);
+
+	/* Temporaries for the computations, but sensible to allocate this up-front! */
+	for (auto &c : tmpC_)
+		c.resize(config_.tableSize);
+	for (auto &m : tmpM_)
+		m.resize(XY);
+}
+
+void Alsc::waitForAysncThread()
+{
+	if (asyncStarted_) {
+		asyncStarted_ = false;
+		std::unique_lock<std::mutex> lock(mutex_);
+		syncSignal_.wait(lock, [&] {
+			return asyncFinished_;
+		});
+		asyncFinished_ = false;
+	}
+}
+
+static bool compareModes(CameraMode const &cm0, CameraMode const &cm1)
+{
+	/*
+	 * Return true if the modes crop from the sensor significantly differently,
+	 * or if the user transform has changed.
+	 */
+	if (cm0.transform != cm1.transform)
+		return true;
+	int leftDiff = abs(cm0.cropX - cm1.cropX);
+	int topDiff = abs(cm0.cropY - cm1.cropY);
+	int rightDiff = fabs(cm0.cropX + cm0.scaleX * cm0.width -
+			     cm1.cropX - cm1.scaleX * cm1.width);
+	int bottomDiff = fabs(cm0.cropY + cm0.scaleY * cm0.height -
+			      cm1.cropY - cm1.scaleY * cm1.height);
+	/*
+	 * These thresholds are a rather arbitrary amount chosen to trigger
+	 * when carrying on with the previously calculated tables might be
+	 * worse than regenerating them (but without the adaptive algorithm).
+	 */
+	int thresholdX = cm0.sensorWidth >> 4;
+	int thresholdY = cm0.sensorHeight >> 4;
+	return leftDiff > thresholdX || rightDiff > thresholdX ||
+	       topDiff > thresholdY || bottomDiff > thresholdY;
+}
+
+void Alsc::switchMode(CameraMode const &cameraMode,
+		      [[maybe_unused]] Metadata *metadata)
+{
+	/*
+	 * We're going to start over with the tables if there's any "significant"
+	 * change.
+	 */
+	bool resetTables = firstTime_ || compareModes(cameraMode_, cameraMode);
+
+	/* Believe the colour temperature from the AWB, if there is one. */
+	ct_ = getCt(metadata, ct_);
+
+	/* Ensure the other thread isn't running while we do this. */
+	waitForAysncThread();
+
+	cameraMode_ = cameraMode;
+
+	/*
+	 * We must resample the luminance table like we do the others, but it's
+	 * fixed so we can simply do it up front here.
+	 */
+	resampleCalTable(config_.luminanceLut, cameraMode_, luminanceTable_);
+
+	if (resetTables) {
+		/*
+		 * Upon every "table reset", arrange for something sensible to be
+		 * generated. Construct the tables for the previous recorded colour
+		 * temperature. In order to start over from scratch we initialise
+		 * the lambdas, but the rest of this code then echoes the code in
+		 * doAlsc, without the adaptive algorithm.
+		 */
+		std::fill(lambdaR_.begin(), lambdaR_.end(), 1.0);
+		std::fill(lambdaB_.begin(), lambdaB_.end(), 1.0);
+		Array2D<double> &calTableR = tmpC_[0], &calTableB = tmpC_[1], &calTableTmp = tmpC_[2];
+		getCalTable(ct_, config_.calibrationsCr, calTableTmp);
+		resampleCalTable(calTableTmp, cameraMode_, calTableR);
+		getCalTable(ct_, config_.calibrationsCb, calTableTmp);
+		resampleCalTable(calTableTmp, cameraMode_, calTableB);
+		compensateLambdasForCal(calTableR, lambdaR_, asyncLambdaR_);
+		compensateLambdasForCal(calTableB, lambdaB_, asyncLambdaB_);
+		addLuminanceToTables(syncResults_, asyncLambdaR_, 1.0, asyncLambdaB_,
+				     luminanceTable_, config_.luminanceStrength);
+		prevSyncResults_ = syncResults_;
+		framePhase_ = config_.framePeriod; /* run the algo again asap */
+		firstTime_ = false;
+	}
+}
+
+void Alsc::fetchAsyncResults()
+{
+	LOG(RPiAlsc, Debug) << "Fetch ALSC results";
+	asyncFinished_ = false;
+	asyncStarted_ = false;
+	syncResults_ = asyncResults_;
+}
+
+double getCt(Metadata *metadata, double defaultCt)
+{
+	AwbStatus awbStatus;
+	awbStatus.temperatureK = defaultCt; /* in case nothing found */
+	if (metadata->get("awb.status", awbStatus) != 0)
+		LOG(RPiAlsc, Debug) << "no AWB results found, using "
+				    << awbStatus.temperatureK;
+	else
+		LOG(RPiAlsc, Debug) << "AWB results found, using "
+				    << awbStatus.temperatureK;
+	return awbStatus.temperatureK;
+}
+
+static void copyStats(RgbyRegions &regions, StatisticsPtr &stats,
+		      AlscStatus const &status)
+{
+	if (!regions.numRegions())
+		regions.init(stats->awbRegions.size());
+
+	const std::vector<double> &rTable = status.r;
+	const std::vector<double> &gTable = status.g;
+	const std::vector<double> &bTable = status.b;
+	for (unsigned int i = 0; i < stats->awbRegions.numRegions(); i++) {
+		auto r = stats->awbRegions.get(i);
+		r.val.rSum = static_cast<uint64_t>(r.val.rSum / rTable[i]);
+		r.val.gSum = static_cast<uint64_t>(r.val.gSum / gTable[i]);
+		r.val.bSum = static_cast<uint64_t>(r.val.bSum / bTable[i]);
+		regions.set(i, r);
+	}
+}
+
+void Alsc::restartAsync(StatisticsPtr &stats, Metadata *imageMetadata)
+{
+	LOG(RPiAlsc, Debug) << "Starting ALSC calculation";
+	/*
+	 * Get the current colour temperature. It's all we need from the
+	 * metadata. Default to the last CT value (which could be the default).
+	 */
+	ct_ = getCt(imageMetadata, ct_);
+	/*
+	 * We have to copy the statistics here, dividing out our best guess of
+	 * the LSC table that the pipeline applied to them.
+	 */
+	AlscStatus alscStatus;
+	if (imageMetadata->get("alsc.status", alscStatus) != 0) {
+		LOG(RPiAlsc, Warning)
+			<< "No ALSC status found for applied gains!";
+		alscStatus.r.resize(config_.tableSize.width * config_.tableSize.height, 1.0);
+		alscStatus.g.resize(config_.tableSize.width * config_.tableSize.height, 1.0);
+		alscStatus.b.resize(config_.tableSize.width * config_.tableSize.height, 1.0);
+	}
+	copyStats(statistics_, stats, alscStatus);
+	framePhase_ = 0;
+	asyncStarted_ = true;
+	{
+		std::lock_guard<std::mutex> lock(mutex_);
+		asyncStart_ = true;
+	}
+	asyncSignal_.notify_one();
+}
+
+void Alsc::prepare(Metadata *imageMetadata)
+{
+	/*
+	 * Count frames since we started, and since we last poked the async
+	 * thread.
+	 */
+	if (frameCount_ < (int)config_.startupFrames)
+		frameCount_++;
+	double speed = frameCount_ < (int)config_.startupFrames
+			       ? 1.0
+			       : config_.speed;
+	LOG(RPiAlsc, Debug)
+		<< "frame count " << frameCount_ << " speed " << speed;
+	{
+		std::unique_lock<std::mutex> lock(mutex_);
+		if (asyncStarted_ && asyncFinished_)
+			fetchAsyncResults();
+	}
+	/* Apply IIR filter to results and program into the pipeline. */
+	for (unsigned int j = 0; j < syncResults_.size(); j++) {
+		for (unsigned int i = 0; i < syncResults_[j].size(); i++)
+			prevSyncResults_[j][i] = speed * syncResults_[j][i] + (1.0 - speed) * prevSyncResults_[j][i];
+	}
+	/* Put output values into status metadata. */
+	AlscStatus status;
+	status.r = prevSyncResults_[0].data();
+	status.g = prevSyncResults_[1].data();
+	status.b = prevSyncResults_[2].data();
+	imageMetadata->set("alsc.status", status);
+}
+
+void Alsc::process(StatisticsPtr &stats, Metadata *imageMetadata)
+{
+	/*
+	 * Count frames since we started, and since we last poked the async
+	 * thread.
+	 */
+	if (framePhase_ < (int)config_.framePeriod)
+		framePhase_++;
+	if (frameCount2_ < (int)config_.startupFrames)
+		frameCount2_++;
+	LOG(RPiAlsc, Debug) << "frame_phase " << framePhase_;
+	if (framePhase_ >= (int)config_.framePeriod ||
+	    frameCount2_ < (int)config_.startupFrames) {
+		if (asyncStarted_ == false)
+			restartAsync(stats, imageMetadata);
+	}
+}
+
+void Alsc::asyncFunc()
+{
+	while (true) {
+		{
+			std::unique_lock<std::mutex> lock(mutex_);
+			asyncSignal_.wait(lock, [&] {
+				return asyncStart_ || asyncAbort_;
+			});
+			asyncStart_ = false;
+			if (asyncAbort_)
+				break;
+		}
+		doAlsc();
+		{
+			std::lock_guard<std::mutex> lock(mutex_);
+			asyncFinished_ = true;
+		}
+		syncSignal_.notify_one();
+	}
+}
+
+void getCalTable(double ct, std::vector<AlscCalibration> const &calibrations,
+		 Array2D<double> &calTable)
+{
+	if (calibrations.empty()) {
+		std::fill(calTable.begin(), calTable.end(), 1.0);
+		LOG(RPiAlsc, Debug) << "no calibrations found";
+	} else if (ct <= calibrations.front().ct) {
+		calTable = calibrations.front().table;
+		LOG(RPiAlsc, Debug) << "using calibration for "
+				    << calibrations.front().ct;
+	} else if (ct >= calibrations.back().ct) {
+		calTable = calibrations.back().table;
+		LOG(RPiAlsc, Debug) << "using calibration for "
+				    << calibrations.back().ct;
+	} else {
+		int idx = 0;
+		while (ct > calibrations[idx + 1].ct)
+			idx++;
+		double ct0 = calibrations[idx].ct, ct1 = calibrations[idx + 1].ct;
+		LOG(RPiAlsc, Debug)
+			<< "ct is " << ct << ", interpolating between "
+			<< ct0 << " and " << ct1;
+		for (unsigned int i = 0; i < calTable.size(); i++)
+			calTable[i] =
+				(calibrations[idx].table[i] * (ct1 - ct) +
+				 calibrations[idx + 1].table[i] * (ct - ct0)) /
+				(ct1 - ct0);
+	}
+}
+
+void resampleCalTable(const Array2D<double> &calTableIn,
+		      CameraMode const &cameraMode,
+		      Array2D<double> &calTableOut)
+{
+	int X = calTableIn.dimensions().width;
+	int Y = calTableIn.dimensions().height;
+
+	/*
+	 * Precalculate and cache the x sampling locations and phases to save
+	 * recomputing them on every row.
+	 */
+	int xLo[X], xHi[X];
+	double xf[X];
+	double scaleX = cameraMode.sensorWidth /
+			(cameraMode.width * cameraMode.scaleX);
+	double xOff = cameraMode.cropX / (double)cameraMode.sensorWidth;
+	double x = .5 / scaleX + xOff * X - .5;
+	double xInc = 1 / scaleX;
+	for (int i = 0; i < X; i++, x += xInc) {
+		xLo[i] = floor(x);
+		xf[i] = x - xLo[i];
+		xHi[i] = std::min(xLo[i] + 1, X - 1);
+		xLo[i] = std::max(xLo[i], 0);
+		if (!!(cameraMode.transform & libcamera::Transform::HFlip)) {
+			xLo[i] = X - 1 - xLo[i];
+			xHi[i] = X - 1 - xHi[i];
+		}
+	}
+	/* Now march over the output table generating the new values. */
+	double scaleY = cameraMode.sensorHeight /
+			(cameraMode.height * cameraMode.scaleY);
+	double yOff = cameraMode.cropY / (double)cameraMode.sensorHeight;
+	double y = .5 / scaleY + yOff * Y - .5;
+	double yInc = 1 / scaleY;
+	for (int j = 0; j < Y; j++, y += yInc) {
+		int yLo = floor(y);
+		double yf = y - yLo;
+		int yHi = std::min(yLo + 1, Y - 1);
+		yLo = std::max(yLo, 0);
+		if (!!(cameraMode.transform & libcamera::Transform::VFlip)) {
+			yLo = Y - 1 - yLo;
+			yHi = Y - 1 - yHi;
+		}
+		double const *rowAbove = calTableIn.ptr() + X * yLo;
+		double const *rowBelow = calTableIn.ptr() + X * yHi;
+		double *out = calTableOut.ptr() + X * j;
+		for (int i = 0; i < X; i++) {
+			double above = rowAbove[xLo[i]] * (1 - xf[i]) +
+				       rowAbove[xHi[i]] * xf[i];
+			double below = rowBelow[xLo[i]] * (1 - xf[i]) +
+				       rowBelow[xHi[i]] * xf[i];
+			*(out++) = above * (1 - yf) + below * yf;
+		}
+	}
+}
+
+/* Calculate chrominance statistics (R/G and B/G) for each region. */
+static void calculateCrCb(const RgbyRegions &awbRegion, Array2D<double> &cr,
+			  Array2D<double> &cb, uint32_t minCount, uint16_t minG)
+{
+	for (unsigned int i = 0; i < cr.size(); i++) {
+		auto s = awbRegion.get(i);
+
+		if (s.counted <= minCount || s.val.gSum / s.counted <= minG) {
+			cr[i] = cb[i] = InsufficientData;
+			continue;
+		}
+
+		cr[i] = s.val.rSum / (double)s.val.gSum;
+		cb[i] = s.val.bSum / (double)s.val.gSum;
+	}
+}
+
+static void applyCalTable(const Array2D<double> &calTable, Array2D<double> &C)
+{
+	for (unsigned int i = 0; i < C.size(); i++)
+		if (C[i] != InsufficientData)
+			C[i] *= calTable[i];
+}
+
+void compensateLambdasForCal(const Array2D<double> &calTable,
+			     const Array2D<double> &oldLambdas,
+			     Array2D<double> &newLambdas)
+{
+	double minNewLambda = std::numeric_limits<double>::max();
+	for (unsigned int i = 0; i < newLambdas.size(); i++) {
+		newLambdas[i] = oldLambdas[i] * calTable[i];
+		minNewLambda = std::min(minNewLambda, newLambdas[i]);
+	}
+	for (unsigned int i = 0; i < newLambdas.size(); i++)
+		newLambdas[i] /= minNewLambda;
+}
+
+[[maybe_unused]] static void printCalTable(const Array2D<double> &C)
+{
+	const Size &size = C.dimensions();
+	printf("table: [\n");
+	for (unsigned int j = 0; j < size.height; j++) {
+		for (unsigned int i = 0; i < size.width; i++) {
+			printf("%5.3f", 1.0 / C[j * size.width + i]);
+			if (i != size.width - 1 || j != size.height - 1)
+				printf(",");
+		}
+		printf("\n");
+	}
+	printf("]\n");
+}
+
+/*
+ * Compute weight out of 1.0 which reflects how similar we wish to make the
+ * colours of these two regions.
+ */
+static double computeWeight(double Ci, double Cj, double sigma)
+{
+	if (Ci == InsufficientData || Cj == InsufficientData)
+		return 0;
+	double diff = (Ci - Cj) / sigma;
+	return exp(-diff * diff / 2);
+}
+
+/* Compute all weights. */
+static void computeW(const Array2D<double> &C, double sigma,
+		     SparseArray<double> &W)
+{
+	size_t XY = C.size();
+	size_t X = C.dimensions().width;
+
+	for (unsigned int i = 0; i < XY; i++) {
+		/* Start with neighbour above and go clockwise. */
+		W[i][0] = i >= X ? computeWeight(C[i], C[i - X], sigma) : 0;
+		W[i][1] = i % X < X - 1 ? computeWeight(C[i], C[i + 1], sigma) : 0;
+		W[i][2] = i < XY - X ? computeWeight(C[i], C[i + X], sigma) : 0;
+		W[i][3] = i % X ? computeWeight(C[i], C[i - 1], sigma) : 0;
+	}
+}
+
+/* Compute M, the large but sparse matrix such that M * lambdas = 0. */
+static void constructM(const Array2D<double> &C,
+		       const SparseArray<double> &W,
+		       SparseArray<double> &M)
+{
+	size_t XY = C.size();
+	size_t X = C.dimensions().width;
+
+	double epsilon = 0.001;
+	for (unsigned int i = 0; i < XY; i++) {
+		/*
+		 * Note how, if C[i] == INSUFFICIENT_DATA, the weights will all
+		 * be zero so the equation is still set up correctly.
+		 */
+		int m = !!(i >= X) + !!(i % X < X - 1) + !!(i < XY - X) +
+			!!(i % X); /* total number of neighbours */
+		/* we'll divide the diagonal out straight away */
+		double diagonal = (epsilon + W[i][0] + W[i][1] + W[i][2] + W[i][3]) * C[i];
+		M[i][0] = i >= X ? (W[i][0] * C[i - X] + epsilon / m * C[i]) / diagonal : 0;
+		M[i][1] = i % X < X - 1 ? (W[i][1] * C[i + 1] + epsilon / m * C[i]) / diagonal : 0;
+		M[i][2] = i < XY - X ? (W[i][2] * C[i + X] + epsilon / m * C[i]) / diagonal : 0;
+		M[i][3] = i % X ? (W[i][3] * C[i - 1] + epsilon / m * C[i]) / diagonal : 0;
+	}
+}
+
+/*
+ * In the compute_lambda_ functions, note that the matrix coefficients for the
+ * left/right neighbours are zero down the left/right edges, so we don't need
+ * need to test the i value to exclude them.
+ */
+static double computeLambdaBottom(int i, const SparseArray<double> &M,
+				  Array2D<double> &lambda)
+{
+	return M[i][1] * lambda[i + 1] + M[i][2] * lambda[i + lambda.dimensions().width] +
+	       M[i][3] * lambda[i - 1];
+}
+static double computeLambdaBottomStart(int i, const SparseArray<double> &M,
+				       Array2D<double> &lambda)
+{
+	return M[i][1] * lambda[i + 1] + M[i][2] * lambda[i + lambda.dimensions().width];
+}
+static double computeLambdaInterior(int i, const SparseArray<double> &M,
+				    Array2D<double> &lambda)
+{
+	return M[i][0] * lambda[i - lambda.dimensions().width] + M[i][1] * lambda[i + 1] +
+	       M[i][2] * lambda[i + lambda.dimensions().width] + M[i][3] * lambda[i - 1];
+}
+static double computeLambdaTop(int i, const SparseArray<double> &M,
+			       Array2D<double> &lambda)
+{
+	return M[i][0] * lambda[i - lambda.dimensions().width] + M[i][1] * lambda[i + 1] +
+	       M[i][3] * lambda[i - 1];
+}
+static double computeLambdaTopEnd(int i, const SparseArray<double> &M,
+				  Array2D<double> &lambda)
+{
+	return M[i][0] * lambda[i - lambda.dimensions().width] + M[i][3] * lambda[i - 1];
+}
+
+/* Gauss-Seidel iteration with over-relaxation. */
+static double gaussSeidel2Sor(const SparseArray<double> &M, double omega,
+			      Array2D<double> &lambda, double lambdaBound)
+{
+	int XY = lambda.size();
+	int X = lambda.dimensions().width;
+	const double min = 1 - lambdaBound, max = 1 + lambdaBound;
+	Array2D<double> oldLambda = lambda;
+	int i;
+	lambda[0] = computeLambdaBottomStart(0, M, lambda);
+	lambda[0] = std::clamp(lambda[0], min, max);
+	for (i = 1; i < X; i++) {
+		lambda[i] = computeLambdaBottom(i, M, lambda);
+		lambda[i] = std::clamp(lambda[i], min, max);
+	}
+	for (; i < XY - X; i++) {
+		lambda[i] = computeLambdaInterior(i, M, lambda);
+		lambda[i] = std::clamp(lambda[i], min, max);
+	}
+	for (; i < XY - 1; i++) {
+		lambda[i] = computeLambdaTop(i, M, lambda);
+		lambda[i] = std::clamp(lambda[i], min, max);
+	}
+	lambda[i] = computeLambdaTopEnd(i, M, lambda);
+	lambda[i] = std::clamp(lambda[i], min, max);
+	/*
+	 * Also solve the system from bottom to top, to help spread the updates
+	 * better.
+	 */
+	lambda[i] = computeLambdaTopEnd(i, M, lambda);
+	lambda[i] = std::clamp(lambda[i], min, max);
+	for (i = XY - 2; i >= XY - X; i--) {
+		lambda[i] = computeLambdaTop(i, M, lambda);
+		lambda[i] = std::clamp(lambda[i], min, max);
+	}
+	for (; i >= X; i--) {
+		lambda[i] = computeLambdaInterior(i, M, lambda);
+		lambda[i] = std::clamp(lambda[i], min, max);
+	}
+	for (; i >= 1; i--) {
+		lambda[i] = computeLambdaBottom(i, M, lambda);
+		lambda[i] = std::clamp(lambda[i], min, max);
+	}
+	lambda[0] = computeLambdaBottomStart(0, M, lambda);
+	lambda[0] = std::clamp(lambda[0], min, max);
+	double maxDiff = 0;
+	for (i = 0; i < XY; i++) {
+		lambda[i] = oldLambda[i] + (lambda[i] - oldLambda[i]) * omega;
+		if (fabs(lambda[i] - oldLambda[i]) > fabs(maxDiff))
+			maxDiff = lambda[i] - oldLambda[i];
+	}
+	return maxDiff;
+}
+
+/* Normalise the values so that the smallest value is 1. */
+static void normalise(Array2D<double> &results)
+{
+	double minval = *std::min_element(results.begin(), results.end());
+	std::for_each(results.begin(), results.end(),
+		      [minval](double val) { return val / minval; });
+}
+
+/* Rescale the values so that the average value is 1. */
+static void reaverage(Array2D<double> &data)
+{
+	double sum = std::accumulate(data.begin(), data.end(), 0.0);
+	double ratio = 1 / (sum / data.size());
+	std::for_each(data.begin(), data.end(),
+		      [ratio](double val) { return val * ratio; });
+}
+
+static void runMatrixIterations(const Array2D<double> &C,
+				Array2D<double> &lambda,
+				const SparseArray<double> &W,
+				SparseArray<double> &M, double omega,
+				unsigned int nIter, double threshold, double lambdaBound)
+{
+	constructM(C, W, M);
+	double lastMaxDiff = std::numeric_limits<double>::max();
+	for (unsigned int i = 0; i < nIter; i++) {
+		double maxDiff = fabs(gaussSeidel2Sor(M, omega, lambda, lambdaBound));
+		if (maxDiff < threshold) {
+			LOG(RPiAlsc, Debug)
+				<< "Stop after " << i + 1 << " iterations";
+			break;
+		}
+		/*
+		 * this happens very occasionally (so make a note), though
+		 * doesn't seem to matter
+		 */
+		if (maxDiff > lastMaxDiff)
+			LOG(RPiAlsc, Debug)
+				<< "Iteration " << i << ": maxDiff gone up "
+				<< lastMaxDiff << " to " << maxDiff;
+		lastMaxDiff = maxDiff;
+	}
+	/* We're going to normalise the lambdas so the total average is 1. */
+	reaverage(lambda);
+}
+
+static void addLuminanceRb(Array2D<double> &result, const Array2D<double> &lambda,
+			   const Array2D<double> &luminanceLut,
+			   double luminanceStrength)
+{
+	for (unsigned int i = 0; i < result.size(); i++)
+		result[i] = lambda[i] * ((luminanceLut[i] - 1) * luminanceStrength + 1);
+}
+
+static void addLuminanceG(Array2D<double> &result, double lambda,
+			  const Array2D<double> &luminanceLut,
+			  double luminanceStrength)
+{
+	for (unsigned int i = 0; i < result.size(); i++)
+		result[i] = lambda * ((luminanceLut[i] - 1) * luminanceStrength + 1);
+}
+
+void addLuminanceToTables(std::array<Array2D<double>, 3> &results,
+			  const Array2D<double> &lambdaR,
+			  double lambdaG, const Array2D<double> &lambdaB,
+			  const Array2D<double> &luminanceLut,
+			  double luminanceStrength)
+{
+	addLuminanceRb(results[0], lambdaR, luminanceLut, luminanceStrength);
+	addLuminanceG(results[1], lambdaG, luminanceLut, luminanceStrength);
+	addLuminanceRb(results[2], lambdaB, luminanceLut, luminanceStrength);
+	for (auto &r : results)
+		normalise(r);
+}
+
+void Alsc::doAlsc()
+{
+	Array2D<double> &cr = tmpC_[0], &cb = tmpC_[1], &calTableR = tmpC_[2],
+			&calTableB = tmpC_[3], &calTableTmp = tmpC_[4];
+	SparseArray<double> &wr = tmpM_[0], &wb = tmpM_[1], &M = tmpM_[2];
+
+	/*
+	 * Calculate our R/B ("Cr"/"Cb") colour statistics, and assess which are
+	 * usable.
+	 */
+	calculateCrCb(statistics_, cr, cb, config_.minCount, config_.minG);
+	/*
+	 * Fetch the new calibrations (if any) for this CT. Resample them in
+	 * case the camera mode is not full-frame.
+	 */
+	getCalTable(ct_, config_.calibrationsCr, calTableTmp);
+	resampleCalTable(calTableTmp, cameraMode_, calTableR);
+	getCalTable(ct_, config_.calibrationsCb, calTableTmp);
+	resampleCalTable(calTableTmp, cameraMode_, calTableB);
+	/*
+	 * You could print out the cal tables for this image here, if you're
+	 * tuning the algorithm...
+	 * Apply any calibration to the statistics, so the adaptive algorithm
+	 * makes only the extra adjustments.
+	 */
+	applyCalTable(calTableR, cr);
+	applyCalTable(calTableB, cb);
+	/* Compute weights between zones. */
+	computeW(cr, config_.sigmaCr, wr);
+	computeW(cb, config_.sigmaCb, wb);
+	/* Run Gauss-Seidel iterations over the resulting matrix, for R and B. */
+	runMatrixIterations(cr, lambdaR_, wr, M, config_.omega, config_.nIter,
+			    config_.threshold, config_.lambdaBound);
+	runMatrixIterations(cb, lambdaB_, wb, M, config_.omega, config_.nIter,
+			    config_.threshold, config_.lambdaBound);
+	/*
+	 * Fold the calibrated gains into our final lambda values. (Note that on
+	 * the next run, we re-start with the lambda values that don't have the
+	 * calibration gains included.)
+	 */
+	compensateLambdasForCal(calTableR, lambdaR_, asyncLambdaR_);
+	compensateLambdasForCal(calTableB, lambdaB_, asyncLambdaB_);
+	/* Fold in the luminance table at the appropriate strength. */
+	addLuminanceToTables(asyncResults_, asyncLambdaR_, 1.0,
+			     asyncLambdaB_, luminanceTable_,
+			     config_.luminanceStrength);
+}
+
+/* Register algorithm with the system. */
+static Algorithm *create(Controller *controller)
+{
+	return (Algorithm *)new Alsc(controller);
+}
+static RegisterAlgorithm reg(NAME, &create);

src/ipa/rpi/controller/rpi/alsc.h

@@ -0,0 +1,174 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2019, Raspberry Pi Ltd
+ *
+ * alsc.h - ALSC (auto lens shading correction) control algorithm
+ */
+#pragma once
+
+#include <array>
+#include <mutex>
+#include <condition_variable>
+#include <thread>
+#include <vector>
+
+#include <libcamera/geometry.h>
+
+#include "../algorithm.h"
+#include "../alsc_status.h"
+#include "../statistics.h"
+
+namespace RPiController {
+
+/* Algorithm to generate automagic LSC (Lens Shading Correction) tables. */
+
+/*
+ * The Array2D class is a very thin wrapper round std::vector so that it can
+ * be used in exactly the same way in the code but carries its correct width
+ * and height ("dimensions") with it.
+ */
+
+template<typename T>
+class Array2D
+{
+public:
+	using Size = libcamera::Size;
+
+	const Size &dimensions() const { return dimensions_; }
+
+	size_t size() const { return data_.size(); }
+
+	const std::vector<T> &data() const { return data_; }
+
+	void resize(const Size &dims)
+	{
+		dimensions_ = dims;
+		data_.resize(dims.width * dims.height);
+	}
+
+	void resize(const Size &dims, const T &value)
+	{
+		resize(dims);
+		std::fill(data_.begin(), data_.end(), value);
+	}
+
+	T &operator[](int index) { return data_[index]; }
+
+	const T &operator[](int index) const { return data_[index]; }
+
+	T *ptr() { return data_.data(); }
+
+	const T *ptr() const { return data_.data(); }
+
+	auto begin() { return data_.begin(); }
+	auto end() { return data_.end(); }
+
+private:
+	Size dimensions_;
+	std::vector<T> data_;
+};
+
+/*
+ * We'll use the term SparseArray for the large sparse matrices that are
+ * XY tall but have only 4 non-zero elements on each row.
+ */
+
+template<typename T>
+using SparseArray = std::vector<std::array<T, 4>>;
+
+struct AlscCalibration {
+	double ct;
+	Array2D<double> table;
+};
+
+struct AlscConfig {
+	/* Only repeat the ALSC calculation every "this many" frames */
+	uint16_t framePeriod;
+	/* number of initial frames for which speed taken as 1.0 (maximum) */
+	uint16_t startupFrames;
+	/* IIR filter speed applied to algorithm results */
+	double speed;
+	double sigmaCr;
+	double sigmaCb;
+	double minCount;
+	uint16_t minG;
+	double omega;
+	uint32_t nIter;
+	Array2D<double> luminanceLut;
+	double luminanceStrength;
+	std::vector<AlscCalibration> calibrationsCr;
+	std::vector<AlscCalibration> calibrationsCb;
+	double defaultCt; /* colour temperature if no metadata found */
+	double threshold; /* iteration termination threshold */
+	double lambdaBound; /* upper/lower bound for lambda from a value of 1 */
+	libcamera::Size tableSize;
+};
+
+class Alsc : public Algorithm
+{
+public:
+	Alsc(Controller *controller = NULL);
+	~Alsc();
+	char const *name() const override;
+	void initialise() override;
+	void switchMode(CameraMode const &cameraMode, Metadata *metadata) override;
+	int read(const libcamera::YamlObject &params) override;
+	void prepare(Metadata *imageMetadata) override;
+	void process(StatisticsPtr &stats, Metadata *imageMetadata) override;
+
+private:
+	/* configuration is read-only, and available to both threads */
+	AlscConfig config_;
+	bool firstTime_;
+	CameraMode cameraMode_;
+	Array2D<double> luminanceTable_;
+	std::thread asyncThread_;
+	void asyncFunc(); /* asynchronous thread function */
+	std::mutex mutex_;
+	/* condvar for async thread to wait on */
+	std::condition_variable asyncSignal_;
+	/* condvar for synchronous thread to wait on */
+	std::condition_variable syncSignal_;
+	/* for sync thread to check  if async thread finished (requires mutex) */
+	bool asyncFinished_;
+	/* for async thread to check if it's been told to run (requires mutex) */
+	bool asyncStart_;
+	/* for async thread to check if it's been told to quit (requires mutex) */
+	bool asyncAbort_;
+
+	/*
+	 * The following are only for the synchronous thread to use:
+	 * for sync thread to note its has asked async thread to run
+	 */
+	bool asyncStarted_;
+	/* counts up to framePeriod before restarting the async thread */
+	int framePhase_;
+	/* counts up to startupFrames */
+	int frameCount_;
+	/* counts up to startupFrames for Process function */
+	int frameCount2_;
+	std::array<Array2D<double>, 3> syncResults_;
+	std::array<Array2D<double>, 3> prevSyncResults_;
+	void waitForAysncThread();
+	/*
+	 * The following are for the asynchronous thread to use, though the main
+	 * thread can set/reset them if the async thread is known to be idle:
+	 */
+	void restartAsync(StatisticsPtr &stats, Metadata *imageMetadata);
+	/* copy out the results from the async thread so that it can be restarted */
+	void fetchAsyncResults();
+	double ct_;
+	RgbyRegions statistics_;
+	std::array<Array2D<double>, 3> asyncResults_;
+	Array2D<double> asyncLambdaR_;
+	Array2D<double> asyncLambdaB_;
+	void doAlsc();
+	Array2D<double> lambdaR_;
+	Array2D<double> lambdaB_;
+
+	/* Temporaries for the computations */
+	std::array<Array2D<double>, 5> tmpC_;
+	std::array<SparseArray<double>, 3> tmpM_;
+};
+
+} /* namespace RPiController */

src/ipa/rpi/controller/rpi/awb.cpp

@@ -0,0 +1,734 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2019, Raspberry Pi Ltd
+ *
+ * awb.cpp - AWB control algorithm
+ */
+
+#include <assert.h>
+#include <functional>
+
+#include <libcamera/base/log.h>
+
+#include "../lux_status.h"
+
+#include "awb.h"
+
+using namespace RPiController;
+using namespace libcamera;
+
+LOG_DEFINE_CATEGORY(RPiAwb)
+
+#define NAME "rpi.awb"
+
+/*
+ * todo - the locking in this algorithm needs some tidying up as has been done
+ * elsewhere (ALSC and AGC).
+ */
+
+int AwbMode::read(const libcamera::YamlObject &params)
+{
+	auto value = params["lo"].get<double>();
+	if (!value)
+		return -EINVAL;
+	ctLo = *value;
+
+	value = params["hi"].get<double>();
+	if (!value)
+		return -EINVAL;
+	ctHi = *value;
+
+	return 0;
+}
+
+int AwbPrior::read(const libcamera::YamlObject &params)
+{
+	auto value = params["lux"].get<double>();
+	if (!value)
+		return -EINVAL;
+	lux = *value;
+
+	return prior.read(params["prior"]);
+}
+
+static int readCtCurve(Pwl &ctR, Pwl &ctB, const libcamera::YamlObject &params)
+{
+	if (params.size() % 3) {
+		LOG(RPiAwb, Error) << "AwbConfig: incomplete CT curve entry";
+		return -EINVAL;
+	}
+
+	if (params.size() < 6) {
+		LOG(RPiAwb, Error) << "AwbConfig: insufficient points in CT curve";
+		return -EINVAL;
+	}
+
+	const auto &list = params.asList();
+
+	for (auto it = list.begin(); it != list.end(); it++) {
+		auto value = it->get<double>();
+		if (!value)
+			return -EINVAL;
+		double ct = *value;
+
+		assert(it == list.begin() || ct != ctR.domain().end);
+
+		value = (++it)->get<double>();
+		if (!value)
+			return -EINVAL;
+		ctR.append(ct, *value);
+
+		value = (++it)->get<double>();
+		if (!value)
+			return -EINVAL;
+		ctB.append(ct, *value);
+	}
+
+	return 0;
+}
+
+int AwbConfig::read(const libcamera::YamlObject &params)
+{
+	int ret;
+
+	bayes = params["bayes"].get<int>(1);
+	framePeriod = params["frame_period"].get<uint16_t>(10);
+	startupFrames = params["startup_frames"].get<uint16_t>(10);
+	convergenceFrames = params["convergence_frames"].get<unsigned int>(3);
+	speed = params["speed"].get<double>(0.05);
+
+	if (params.contains("ct_curve")) {
+		ret = readCtCurve(ctR, ctB, params["ct_curve"]);
+		if (ret)
+			return ret;
+		/* We will want the inverse functions of these too. */
+		ctRInverse = ctR.inverse();
+		ctBInverse = ctB.inverse();
+	}
+
+	if (params.contains("priors")) {
+		for (const auto &p : params["priors"].asList()) {
+			AwbPrior prior;
+			ret = prior.read(p);
+			if (ret)
+				return ret;
+			if (!priors.empty() && prior.lux <= priors.back().lux) {
+				LOG(RPiAwb, Error) << "AwbConfig: Prior must be ordered in increasing lux value";
+				return -EINVAL;
+			}
+			priors.push_back(prior);
+		}
+		if (priors.empty()) {
+			LOG(RPiAwb, Error) << "AwbConfig: no AWB priors configured";
+			return ret;
+		}
+	}
+	if (params.contains("modes")) {
+		for (const auto &[key, value] : params["modes"].asDict()) {
+			ret = modes[key].read(value);
+			if (ret)
+				return ret;
+			if (defaultMode == nullptr)
+				defaultMode = &modes[key];
+		}
+		if (defaultMode == nullptr) {
+			LOG(RPiAwb, Error) << "AwbConfig: no AWB modes configured";
+			return -EINVAL;
+		}
+	}
+
+	minPixels = params["min_pixels"].get<double>(16.0);
+	minG = params["min_G"].get<uint16_t>(32);
+	minRegions = params["min_regions"].get<uint32_t>(10);
+	deltaLimit = params["delta_limit"].get<double>(0.2);
+	coarseStep = params["coarse_step"].get<double>(0.2);
+	transversePos = params["transverse_pos"].get<double>(0.01);
+	transverseNeg = params["transverse_neg"].get<double>(0.01);
+	if (transversePos <= 0 || transverseNeg <= 0) {
+		LOG(RPiAwb, Error) << "AwbConfig: transverse_pos/neg must be > 0";
+		return -EINVAL;
+	}
+
+	sensitivityR = params["sensitivity_r"].get<double>(1.0);
+	sensitivityB = params["sensitivity_b"].get<double>(1.0);
+
+	if (bayes) {
+		if (ctR.empty() || ctB.empty() || priors.empty() ||
+		    defaultMode == nullptr) {
+			LOG(RPiAwb, Warning)
+				<< "Bayesian AWB mis-configured - switch to Grey method";
+			bayes = false;
+		}
+	}
+	fast = params[fast].get<int>(bayes); /* default to fast for Bayesian, otherwise slow */
+	whitepointR = params["whitepoint_r"].get<double>(0.0);
+	whitepointB = params["whitepoint_b"].get<double>(0.0);
+	if (bayes == false)
+		sensitivityR = sensitivityB = 1.0; /* nor do sensitivities make any sense */
+	return 0;
+}
+
+Awb::Awb(Controller *controller)
+	: AwbAlgorithm(controller)
+{
+	asyncAbort_ = asyncStart_ = asyncStarted_ = asyncFinished_ = false;
+	mode_ = nullptr;
+	manualR_ = manualB_ = 0.0;
+	asyncThread_ = std::thread(std::bind(&Awb::asyncFunc, this));
+}
+
+Awb::~Awb()
+{
+	{
+		std::lock_guard<std::mutex> lock(mutex_);
+		asyncAbort_ = true;
+	}
+	asyncSignal_.notify_one();
+	asyncThread_.join();
+}
+
+char const *Awb::name() const
+{
+	return NAME;
+}
+
+int Awb::read(const libcamera::YamlObject &params)
+{
+	return config_.read(params);
+}
+
+void Awb::initialise()
+{
+	frameCount_ = framePhase_ = 0;
+	/*
+	 * Put something sane into the status that we are filtering towards,
+	 * just in case the first few frames don't have anything meaningful in
+	 * them.
+	 */
+	if (!config_.ctR.empty() && !config_.ctB.empty()) {
+		syncResults_.temperatureK = config_.ctR.domain().clip(4000);
+		syncResults_.gainR = 1.0 / config_.ctR.eval(syncResults_.temperatureK);
+		syncResults_.gainG = 1.0;
+		syncResults_.gainB = 1.0 / config_.ctB.eval(syncResults_.temperatureK);
+	} else {
+		/* random values just to stop the world blowing up */
+		syncResults_.temperatureK = 4500;
+		syncResults_.gainR = syncResults_.gainG = syncResults_.gainB = 1.0;
+	}
+	prevSyncResults_ = syncResults_;
+	asyncResults_ = syncResults_;
+}
+
+void Awb::disableAuto()
+{
+	/* Freeze the most recent values, and treat them as manual gains */
+	manualR_ = syncResults_.gainR = prevSyncResults_.gainR;
+	manualB_ = syncResults_.gainB = prevSyncResults_.gainB;
+	syncResults_.gainG = prevSyncResults_.gainG;
+	syncResults_.temperatureK = prevSyncResults_.temperatureK;
+}
+
+void Awb::enableAuto()
+{
+	manualR_ = 0.0;
+	manualB_ = 0.0;
+}
+
+unsigned int Awb::getConvergenceFrames() const
+{
+	/*
+	 * If not in auto mode, there is no convergence
+	 * to happen, so no need to drop any frames - return zero.
+	 */
+	if (!isAutoEnabled())
+		return 0;
+	else
+		return config_.convergenceFrames;
+}
+
+void Awb::setMode(std::string const &modeName)
+{
+	modeName_ = modeName;
+}
+
+void Awb::setManualGains(double manualR, double manualB)
+{
+	/* If any of these are 0.0, we swich back to auto. */
+	manualR_ = manualR;
+	manualB_ = manualB;
+	/*
+	 * If not in auto mode, set these values into the syncResults which
+	 * means that Prepare() will adopt them immediately.
+	 */
+	if (!isAutoEnabled()) {
+		syncResults_.gainR = prevSyncResults_.gainR = manualR_;
+		syncResults_.gainG = prevSyncResults_.gainG = 1.0;
+		syncResults_.gainB = prevSyncResults_.gainB = manualB_;
+		if (config_.bayes) {
+			/* Also estimate the best corresponding colour temperature from the curves. */
+			double ctR = config_.ctRInverse.eval(config_.ctRInverse.domain().clip(1 / manualR_));
+			double ctB = config_.ctBInverse.eval(config_.ctBInverse.domain().clip(1 / manualB_));
+			prevSyncResults_.temperatureK = (ctR + ctB) / 2;
+			syncResults_.temperatureK = prevSyncResults_.temperatureK;
+		}
+	}
+}
+
+void Awb::switchMode([[maybe_unused]] CameraMode const &cameraMode,
+		     Metadata *metadata)
+{
+	/* Let other algorithms know the current white balance values. */
+	metadata->set("awb.status", prevSyncResults_);
+}
+
+bool Awb::isAutoEnabled() const
+{
+	return manualR_ == 0.0 || manualB_ == 0.0;
+}
+
+void Awb::fetchAsyncResults()
+{
+	LOG(RPiAwb, Debug) << "Fetch AWB results";
+	asyncFinished_ = false;
+	asyncStarted_ = false;
+	/*
+	 * It's possible manual gains could be set even while the async
+	 * thread was running, so only copy the results if still in auto mode.
+	 */
+	if (isAutoEnabled())
+		syncResults_ = asyncResults_;
+}
+
+void Awb::restartAsync(StatisticsPtr &stats, double lux)
+{
+	LOG(RPiAwb, Debug) << "Starting AWB calculation";
+	/* this makes a new reference which belongs to the asynchronous thread */
+	statistics_ = stats;
+	/* store the mode as it could technically change */
+	auto m = config_.modes.find(modeName_);
+	mode_ = m != config_.modes.end()
+			? &m->second
+			: (mode_ == nullptr ? config_.defaultMode : mode_);
+	lux_ = lux;
+	framePhase_ = 0;
+	asyncStarted_ = true;
+	size_t len = modeName_.copy(asyncResults_.mode,
+				    sizeof(asyncResults_.mode) - 1);
+	asyncResults_.mode[len] = '\0';
+	{
+		std::lock_guard<std::mutex> lock(mutex_);
+		asyncStart_ = true;
+	}
+	asyncSignal_.notify_one();
+}
+
+void Awb::prepare(Metadata *imageMetadata)
+{
+	if (frameCount_ < (int)config_.startupFrames)
+		frameCount_++;
+	double speed = frameCount_ < (int)config_.startupFrames
+			       ? 1.0
+			       : config_.speed;
+	LOG(RPiAwb, Debug)
+		<< "frame_count " << frameCount_ << " speed " << speed;
+	{
+		std::unique_lock<std::mutex> lock(mutex_);
+		if (asyncStarted_ && asyncFinished_)
+			fetchAsyncResults();
+	}
+	/* Finally apply IIR filter to results and put into metadata. */
+	memcpy(prevSyncResults_.mode, syncResults_.mode,
+	       sizeof(prevSyncResults_.mode));
+	prevSyncResults_.temperatureK = speed * syncResults_.temperatureK +
+					(1.0 - speed) * prevSyncResults_.temperatureK;
+	prevSyncResults_.gainR = speed * syncResults_.gainR +
+				 (1.0 - speed) * prevSyncResults_.gainR;
+	prevSyncResults_.gainG = speed * syncResults_.gainG +
+				 (1.0 - speed) * prevSyncResults_.gainG;
+	prevSyncResults_.gainB = speed * syncResults_.gainB +
+				 (1.0 - speed) * prevSyncResults_.gainB;
+	imageMetadata->set("awb.status", prevSyncResults_);
+	LOG(RPiAwb, Debug)
+		<< "Using AWB gains r " << prevSyncResults_.gainR << " g "
+		<< prevSyncResults_.gainG << " b "
+		<< prevSyncResults_.gainB;
+}
+
+void Awb::process(StatisticsPtr &stats, Metadata *imageMetadata)
+{
+	/* Count frames since we last poked the async thread. */
+	if (framePhase_ < (int)config_.framePeriod)
+		framePhase_++;
+	LOG(RPiAwb, Debug) << "frame_phase " << framePhase_;
+	/* We do not restart the async thread if we're not in auto mode. */
+	if (isAutoEnabled() &&
+	    (framePhase_ >= (int)config_.framePeriod ||
+	     frameCount_ < (int)config_.startupFrames)) {
+		/* Update any settings and any image metadata that we need. */
+		struct LuxStatus luxStatus = {};
+		luxStatus.lux = 400; /* in case no metadata */
+		if (imageMetadata->get("lux.status", luxStatus) != 0)
+			LOG(RPiAwb, Debug) << "No lux metadata found";
+		LOG(RPiAwb, Debug) << "Awb lux value is " << luxStatus.lux;
+
+		if (asyncStarted_ == false)
+			restartAsync(stats, luxStatus.lux);
+	}
+}
+
+void Awb::asyncFunc()
+{
+	while (true) {
+		{
+			std::unique_lock<std::mutex> lock(mutex_);
+			asyncSignal_.wait(lock, [&] {
+				return asyncStart_ || asyncAbort_;
+			});
+			asyncStart_ = false;
+			if (asyncAbort_)
+				break;
+		}
+		doAwb();
+		{
+			std::lock_guard<std::mutex> lock(mutex_);
+			asyncFinished_ = true;
+		}
+		syncSignal_.notify_one();
+	}
+}
+
+static void generateStats(std::vector<Awb::RGB> &zones,
+			  RgbyRegions &stats, double minPixels,
+			  double minG)
+{
+	for (auto const &region : stats) {
+		Awb::RGB zone;
+		if (region.counted >= minPixels) {
+			zone.G = region.val.gSum / region.counted;
+			if (zone.G >= minG) {
+				zone.R = region.val.rSum / region.counted;
+				zone.B = region.val.bSum / region.counted;
+				zones.push_back(zone);
+			}
+		}
+	}
+}
+
+void Awb::prepareStats()
+{
+	zones_.clear();
+	/*
+	 * LSC has already been applied to the stats in this pipeline, so stop
+	 * any LSC compensation.  We also ignore config_.fast in this version.
+	 */
+	generateStats(zones_, statistics_->awbRegions, config_.minPixels,
+		      config_.minG);
+	/*
+	 * apply sensitivities, so values appear to come from our "canonical"
+	 * sensor.
+	 */
+	for (auto &zone : zones_) {
+		zone.R *= config_.sensitivityR;
+		zone.B *= config_.sensitivityB;
+	}
+}
+
+double Awb::computeDelta2Sum(double gainR, double gainB)
+{
+	/*
+	 * Compute the sum of the squared colour error (non-greyness) as it
+	 * appears in the log likelihood equation.
+	 */
+	double delta2Sum = 0;
+	for (auto &z : zones_) {
+		double deltaR = gainR * z.R - 1 - config_.whitepointR;
+		double deltaB = gainB * z.B - 1 - config_.whitepointB;
+		double delta2 = deltaR * deltaR + deltaB * deltaB;
+		/* LOG(RPiAwb, Debug) << "deltaR " << deltaR << " deltaB " << deltaB << " delta2 " << delta2; */
+		delta2 = std::min(delta2, config_.deltaLimit);
+		delta2Sum += delta2;
+	}
+	return delta2Sum;
+}
+
+Pwl Awb::interpolatePrior()
+{
+	/*
+	 * Interpolate the prior log likelihood function for our current lux
+	 * value.
+	 */
+	if (lux_ <= config_.priors.front().lux)
+		return config_.priors.front().prior;
+	else if (lux_ >= config_.priors.back().lux)
+		return config_.priors.back().prior;
+	else {
+		int idx = 0;
+		/* find which two we lie between */
+		while (config_.priors[idx + 1].lux < lux_)
+			idx++;
+		double lux0 = config_.priors[idx].lux,
+		       lux1 = config_.priors[idx + 1].lux;
+		return Pwl::combine(config_.priors[idx].prior,
+				    config_.priors[idx + 1].prior,
+				    [&](double /*x*/, double y0, double y1) {
+					    return y0 + (y1 - y0) *
+							(lux_ - lux0) / (lux1 - lux0);
+				    });
+	}
+}
+
+static double interpolateQuadatric(Pwl::Point const &a, Pwl::Point const &b,
+				   Pwl::Point const &c)
+{
+	/*
+	 * Given 3 points on a curve, find the extremum of the function in that
+	 * interval by fitting a quadratic.
+	 */
+	const double eps = 1e-3;
+	Pwl::Point ca = c - a, ba = b - a;
+	double denominator = 2 * (ba.y * ca.x - ca.y * ba.x);
+	if (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);
+}
+
+double Awb::coarseSearch(Pwl const &prior)
+{
+	points_.clear(); /* assume doesn't deallocate memory */
+	size_t bestPoint = 0;
+	double t = mode_->ctLo;
+	int spanR = 0, spanB = 0;
+	/* Step down the CT curve evaluating log likelihood. */
+	while (true) {
+		double r = config_.ctR.eval(t, &spanR);
+		double b = config_.ctB.eval(t, &spanB);
+		double gainR = 1 / r, gainB = 1 / b;
+		double delta2Sum = computeDelta2Sum(gainR, gainB);
+		double priorLogLikelihood = prior.eval(prior.domain().clip(t));
+		double finalLogLikelihood = delta2Sum - priorLogLikelihood;
+		LOG(RPiAwb, Debug)
+			<< "t: " << t << " gain R " << gainR << " gain B "
+			<< gainB << " delta2_sum " << delta2Sum
+			<< " prior " << priorLogLikelihood << " final "
+			<< finalLogLikelihood;
+		points_.push_back(Pwl::Point(t, finalLogLikelihood));
+		if (points_.back().y < points_[bestPoint].y)
+			bestPoint = points_.size() - 1;
+		if (t == mode_->ctHi)
+			break;
+		/* for even steps along the r/b curve scale them by the current t */
+		t = std::min(t + t / 10 * config_.coarseStep, mode_->ctHi);
+	}
+	t = points_[bestPoint].x;
+	LOG(RPiAwb, Debug) << "Coarse search found CT " << t;
+	/*
+	 * We have the best point of the search, but refine it with a quadratic
+	 * interpolation around its neighbours.
+	 */
+	if (points_.size() > 2) {
+		unsigned long bp = std::min(bestPoint, points_.size() - 2);
+		bestPoint = std::max(1UL, bp);
+		t = interpolateQuadatric(points_[bestPoint - 1],
+					 points_[bestPoint],
+					 points_[bestPoint + 1]);
+		LOG(RPiAwb, Debug)
+			<< "After quadratic refinement, coarse search has CT "
+			<< t;
+	}
+	return t;
+}
+
+void Awb::fineSearch(double &t, double &r, double &b, Pwl const &prior)
+{
+	int spanR = -1, spanB = -1;
+	config_.ctR.eval(t, &spanR);
+	config_.ctB.eval(t, &spanB);
+	double step = t / 10 * config_.coarseStep * 0.1;
+	int nsteps = 5;
+	double rDiff = config_.ctR.eval(t + nsteps * step, &spanR) -
+		       config_.ctR.eval(t - nsteps * step, &spanR);
+	double bDiff = config_.ctB.eval(t + nsteps * step, &spanB) -
+		       config_.ctB.eval(t - nsteps * step, &spanB);
+	Pwl::Point transverse(bDiff, -rDiff);
+	if (transverse.len2() < 1e-6)
+		return;
+	/*
+	 * unit vector orthogonal to the b vs. r function (pointing outwards
+	 * with r and b increasing)
+	 */
+	transverse = transverse / transverse.len();
+	double bestLogLikelihood = 0, bestT = 0, bestR = 0, bestB = 0;
+	double transverseRange = config_.transverseNeg + config_.transversePos;
+	const int maxNumDeltas = 12;
+	/* a transverse step approximately every 0.01 r/b units */
+	int numDeltas = floor(transverseRange * 100 + 0.5) + 1;
+	numDeltas = numDeltas < 3 ? 3 : (numDeltas > maxNumDeltas ? maxNumDeltas : numDeltas);
+	/*
+	 * 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 =
+			prior.eval(prior.domain().clip(tTest));
+		double rCurve = config_.ctR.eval(tTest, &spanR);
+		double bCurve = config_.ctB.eval(tTest, &spanB);
+		/* x will be distance off the curve, y the log likelihood there */
+		Pwl::Point points[maxNumDeltas];
+		int bestPoint = 0;
+		/* Take some measurements transversely *off* the CT curve. */
+		for (int j = 0; j < numDeltas; j++) {
+			points[j].x = -config_.transverseNeg +
+				      (transverseRange * j) / (numDeltas - 1);
+			Pwl::Point rbTest = Pwl::Point(rCurve, bCurve) +
+					    transverse * points[j].x;
+			double rTest = rbTest.x, bTest = rbTest.y;
+			double gainR = 1 / rTest, gainB = 1 / bTest;
+			double delta2Sum = computeDelta2Sum(gainR, gainB);
+			points[j].y = delta2Sum - priorLogLikelihood;
+			LOG(RPiAwb, Debug)
+				<< "At t " << tTest << " r " << rTest << " b "
+				<< bTest << ": " << points[j].y;
+			if (points[j].y < points[bestPoint].y)
+				bestPoint = j;
+		}
+		/*
+		 * We have NUM_DELTAS points transversely across the CT curve,
+		 * now let's do a quadratic interpolation for the best result.
+		 */
+		bestPoint = std::max(1, std::min(bestPoint, numDeltas - 2));
+		Pwl::Point rbTest = Pwl::Point(rCurve, bCurve) +
+					transverse * interpolateQuadatric(points[bestPoint - 1],
+									points[bestPoint],
+									points[bestPoint + 1]);
+		double rTest = rbTest.x, bTest = rbTest.y;
+		double gainR = 1 / rTest, gainB = 1 / bTest;
+		double delta2Sum = computeDelta2Sum(gainR, gainB);
+		double finalLogLikelihood = delta2Sum - priorLogLikelihood;
+		LOG(RPiAwb, Debug)
+			<< "Finally "
+			<< tTest << " r " << rTest << " b " << bTest << ": "
+			<< finalLogLikelihood
+			<< (finalLogLikelihood < bestLogLikelihood ? " BEST" : "");
+		if (bestT == 0 || finalLogLikelihood < bestLogLikelihood)
+			bestLogLikelihood = finalLogLikelihood,
+			bestT = tTest, bestR = rTest, bestB = bTest;
+	}
+	t = bestT, r = bestR, b = bestB;
+	LOG(RPiAwb, Debug)
+		<< "Fine search found t " << t << " r " << r << " b " << b;
+}
+
+void Awb::awbBayes()
+{
+	/*
+	 * May as well divide out G to save computeDelta2Sum from doing it over
+	 * and over.
+	 */
+	for (auto &z : zones_)
+		z.R = z.R / (z.G + 1), z.B = z.B / (z.G + 1);
+	/*
+	 * Get the current prior, and scale according to how many zones are
+	 * valid... not entirely sure about this.
+	 */
+	Pwl prior = interpolatePrior();
+	prior *= zones_.size() / (double)(statistics_->awbRegions.numRegions());
+	prior.map([](double x, double y) {
+		LOG(RPiAwb, Debug) << "(" << x << "," << y << ")";
+	});
+	double t = coarseSearch(prior);
+	double r = config_.ctR.eval(t);
+	double b = config_.ctB.eval(t);
+	LOG(RPiAwb, Debug)
+		<< "After coarse search: r " << r << " b " << b << " (gains r "
+		<< 1 / r << " b " << 1 / b << ")";
+	/*
+	 * 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 transverely 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);
+	LOG(RPiAwb, Debug)
+		<< "After fine search: r " << r << " b " << b << " (gains r "
+		<< 1 / r << " b " << 1 / b << ")";
+	/*
+	 * Write results out for the main thread to pick up. Remember to adjust
+	 * the gains from the ones that the "canonical sensor" would require to
+	 * the ones needed by *this* sensor.
+	 */
+	asyncResults_.temperatureK = t;
+	asyncResults_.gainR = 1.0 / r * config_.sensitivityR;
+	asyncResults_.gainG = 1.0;
+	asyncResults_.gainB = 1.0 / b * config_.sensitivityB;
+}
+
+void Awb::awbGrey()
+{
+	LOG(RPiAwb, Debug) << "Grey world AWB";
+	/*
+	 * Make a separate list of the derivatives for each of red and blue, so
+	 * that we can sort them to exclude the extreme gains.  We could
+	 * consider some variations, such as normalising all the zones first, or
+	 * doing an L2 average etc.
+	 */
+	std::vector<RGB> &derivsR(zones_);
+	std::vector<RGB> derivsB(derivsR);
+	std::sort(derivsR.begin(), derivsR.end(),
+		  [](RGB const &a, RGB const &b) {
+			  return a.G * b.R < b.G * a.R;
+		  });
+	std::sort(derivsB.begin(), derivsB.end(),
+		  [](RGB const &a, RGB const &b) {
+			  return a.G * b.B < b.G * a.B;
+		  });
+	/* Average the middle half of the values. */
+	int discard = derivsR.size() / 4;
+	RGB sumR(0, 0, 0), sumB(0, 0, 0);
+	for (auto ri = derivsR.begin() + discard,
+		  bi = derivsB.begin() + discard;
+	     ri != derivsR.end() - discard; ri++, bi++)
+		sumR += *ri, sumB += *bi;
+	double gainR = sumR.G / (sumR.R + 1),
+	       gainB = sumB.G / (sumB.B + 1);
+	asyncResults_.temperatureK = 4500; /* don't know what it is */
+	asyncResults_.gainR = gainR;
+	asyncResults_.gainG = 1.0;
+	asyncResults_.gainB = gainB;
+}
+
+void Awb::doAwb()
+{
+	prepareStats();
+	LOG(RPiAwb, Debug) << "Valid zones: " << zones_.size();
+	if (zones_.size() > config_.minRegions) {
+		if (config_.bayes)
+			awbBayes();
+		else
+			awbGrey();
+		LOG(RPiAwb, Debug)
+			<< "CT found is "
+			<< asyncResults_.temperatureK
+			<< " with gains r " << asyncResults_.gainR
+			<< " and b " << asyncResults_.gainB;
+	}
+	/*
+	 * we're done with these; we may as well relinquish our hold on the
+	 * pointer.
+	 */
+	statistics_.reset();
+}
+
+/* Register algorithm with the system. */
+static Algorithm *create(Controller *controller)
+{
+	return (Algorithm *)new Awb(controller);
+}
+static RegisterAlgorithm reg(NAME, &create);

src/ipa/rpi/controller/rpi/awb.h

@@ -0,0 +1,191 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2019, Raspberry Pi Ltd
+ *
+ * awb.h - AWB control algorithm
+ */
+#pragma once
+
+#include <mutex>
+#include <condition_variable>
+#include <thread>
+
+#include "../awb_algorithm.h"
+#include "../pwl.h"
+#include "../awb_status.h"
+#include "../statistics.h"
+
+namespace RPiController {
+
+/* Control algorithm to perform AWB calculations. */
+
+struct AwbMode {
+	int read(const libcamera::YamlObject &params);
+	double ctLo; /* low CT value for search */
+	double ctHi; /* high CT value for search */
+};
+
+struct AwbPrior {
+	int read(const libcamera::YamlObject &params);
+	double lux; /* lux level */
+	Pwl prior; /* maps CT to prior log likelihood for this lux level */
+};
+
+struct AwbConfig {
+	AwbConfig() : defaultMode(nullptr) {}
+	int read(const libcamera::YamlObject &params);
+	/* Only repeat the AWB calculation every "this many" frames */
+	uint16_t framePeriod;
+	/* number of initial frames for which speed taken as 1.0 (maximum) */
+	uint16_t startupFrames;
+	unsigned int convergenceFrames; /* approx number of frames to converge */
+	double speed; /* IIR filter speed applied to algorithm results */
+	bool fast; /* "fast" mode uses a 16x16 rather than 32x32 grid */
+	Pwl ctR; /* function maps CT to r (= R/G) */
+	Pwl ctB; /* function maps CT to b (= B/G) */
+	Pwl ctRInverse; /* inverse of ctR */
+	Pwl ctBInverse; /* inverse of ctB */
+	/* table of illuminant priors at different lux levels */
+	std::vector<AwbPrior> priors;
+	/* AWB "modes" (determines the search range) */
+	std::map<std::string, AwbMode> modes;
+	AwbMode *defaultMode; /* mode used if no mode selected */
+	/*
+	 * minimum proportion of pixels counted within AWB region for it to be
+	 * "useful"
+	 */
+	double minPixels;
+	/* minimum G value of those pixels, to be regarded a "useful" */
+	uint16_t minG;
+	/*
+	 * number of AWB regions that must be "useful" in order to do the AWB
+	 * calculation
+	 */
+	uint32_t minRegions;
+	/* clamp on colour error term (so as not to penalise non-grey excessively) */
+	double deltaLimit;
+	/* step size control in coarse search */
+	double coarseStep;
+	/* how far to wander off CT curve towards "more purple" */
+	double transversePos;
+	/* how far to wander off CT curve towards "more green" */
+	double transverseNeg;
+	/*
+	 * red sensitivity ratio (set to canonical sensor's R/G divided by this
+	 * sensor's R/G)
+	 */
+	double sensitivityR;
+	/*
+	 * blue sensitivity ratio (set to canonical sensor's B/G divided by this
+	 * sensor's B/G)
+	 */
+	double sensitivityB;
+	/* The whitepoint (which we normally "aim" for) can be moved. */
+	double whitepointR;
+	double whitepointB;
+	bool bayes; /* use Bayesian algorithm */
+};
+
+class Awb : public AwbAlgorithm
+{
+public:
+	Awb(Controller *controller = NULL);
+	~Awb();
+	char const *name() const override;
+	void initialise() override;
+	int read(const libcamera::YamlObject &params) override;
+	unsigned int getConvergenceFrames() const override;
+	void setMode(std::string const &name) override;
+	void setManualGains(double manualR, double manualB) override;
+	void enableAuto() override;
+	void disableAuto() override;
+	void switchMode(CameraMode const &cameraMode, Metadata *metadata) override;
+	void prepare(Metadata *imageMetadata) override;
+	void process(StatisticsPtr &stats, Metadata *imageMetadata) override;
+	struct RGB {
+		RGB(double r = 0, double g = 0, double b = 0)
+			: R(r), G(g), B(b)
+		{
+		}
+		double R, G, B;
+		RGB &operator+=(RGB const &other)
+		{
+			R += other.R, G += other.G, B += other.B;
+			return *this;
+		}
+	};
+
+private:
+	bool isAutoEnabled() const;
+	/* configuration is read-only, and available to both threads */
+	AwbConfig config_;
+	std::thread asyncThread_;
+	void asyncFunc(); /* asynchronous thread function */
+	std::mutex mutex_;
+	/* condvar for async thread to wait on */
+	std::condition_variable asyncSignal_;
+	/* condvar for synchronous thread to wait on */
+	std::condition_variable syncSignal_;
+	/* for sync thread to check  if async thread finished (requires mutex) */
+	bool asyncFinished_;
+	/* for async thread to check if it's been told to run (requires mutex) */
+	bool asyncStart_;
+	/* for async thread to check if it's been told to quit (requires mutex) */
+	bool asyncAbort_;
+
+	/*
+	 * The following are only for the synchronous thread to use:
+	 * for sync thread to note its has asked async thread to run
+	 */
+	bool asyncStarted_;
+	/* counts up to framePeriod before restarting the async thread */
+	int framePhase_;
+	int frameCount_; /* counts up to startup_frames */
+	AwbStatus syncResults_;
+	AwbStatus prevSyncResults_;
+	std::string modeName_;
+	/*
+	 * The following are for the asynchronous thread to use, though the main
+	 * thread can set/reset them if the async thread is known to be idle:
+	 */
+	void restartAsync(StatisticsPtr &stats, double lux);
+	/* copy out the results from the async thread so that it can be restarted */
+	void fetchAsyncResults();
+	StatisticsPtr statistics_;
+	AwbMode *mode_;
+	double lux_;
+	AwbStatus asyncResults_;
+	void doAwb();
+	void awbBayes();
+	void awbGrey();
+	void prepareStats();
+	double computeDelta2Sum(double gainR, double gainB);
+	Pwl interpolatePrior();
+	double coarseSearch(Pwl const &prior);
+	void fineSearch(double &t, double &r, double &b, Pwl const &prior);
+	std::vector<RGB> zones_;
+	std::vector<Pwl::Point> points_;
+	/* manual r setting */
+	double manualR_;
+	/* manual b setting */
+	double manualB_;
+};
+
+static inline Awb::RGB operator+(Awb::RGB const &a, Awb::RGB const &b)
+{
+	return Awb::RGB(a.R + b.R, a.G + b.G, a.B + b.B);
+}
+static inline Awb::RGB operator-(Awb::RGB const &a, Awb::RGB const &b)
+{
+	return Awb::RGB(a.R - b.R, a.G - b.G, a.B - b.B);
+}
+static inline Awb::RGB operator*(double d, Awb::RGB const &rgb)
+{
+	return Awb::RGB(d * rgb.R, d * rgb.G, d * rgb.B);
+}
+static inline Awb::RGB operator*(Awb::RGB const &rgb, double d)
+{
+	return d * rgb;
+}
+
+} /* namespace RPiController */

src/ipa/rpi/controller/rpi/black_level.cpp

@@ -0,0 +1,66 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2019, Raspberry Pi Ltd
+ *
+ * black_level.cpp - black level control algorithm
+ */
+
+#include <math.h>
+#include <stdint.h>
+
+#include <libcamera/base/log.h>
+
+#include "../black_level_status.h"
+
+#include "black_level.h"
+
+using namespace RPiController;
+using namespace libcamera;
+
+LOG_DEFINE_CATEGORY(RPiBlackLevel)
+
+#define NAME "rpi.black_level"
+
+BlackLevel::BlackLevel(Controller *controller)
+	: Algorithm(controller)
+{
+}
+
+char const *BlackLevel::name() const
+{
+	return NAME;
+}
+
+int BlackLevel::read(const libcamera::YamlObject &params)
+{
+	/* 64 in 10 bits scaled to 16 bits */
+	uint16_t blackLevel = params["black_level"].get<uint16_t>(4096);
+	blackLevelR_ = params["black_level_r"].get<uint16_t>(blackLevel);
+	blackLevelG_ = params["black_level_g"].get<uint16_t>(blackLevel);
+	blackLevelB_ = params["black_level_b"].get<uint16_t>(blackLevel);
+	LOG(RPiBlackLevel, Debug)
+		<< " Read black levels red " << blackLevelR_
+		<< " green " << blackLevelG_
+		<< " blue " << blackLevelB_;
+	return 0;
+}
+
+void BlackLevel::prepare(Metadata *imageMetadata)
+{
+	/*
+	 * Possibly we should think about doing this in a switchMode or
+	 * something?
+	 */
+	struct BlackLevelStatus status;
+	status.blackLevelR = blackLevelR_;
+	status.blackLevelG = blackLevelG_;
+	status.blackLevelB = blackLevelB_;
+	imageMetadata->set("black_level.status", status);
+}
+
+/* Register algorithm with the system. */
+static Algorithm *create(Controller *controller)
+{
+	return new BlackLevel(controller);
+}
+static RegisterAlgorithm reg(NAME, &create);

src/ipa/rpi/controller/rpi/black_level.h

@@ -0,0 +1,30 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2019, Raspberry Pi Ltd
+ *
+ * black_level.h - black level control algorithm
+ */
+#pragma once
+
+#include "../algorithm.h"
+#include "../black_level_status.h"
+
+/* This is our implementation of the "black level algorithm". */
+
+namespace RPiController {
+
+class BlackLevel : public Algorithm
+{
+public:
+	BlackLevel(Controller *controller);
+	char const *name() const override;
+	int read(const libcamera::YamlObject &params) override;
+	void prepare(Metadata *imageMetadata) override;
+
+private:
+	double blackLevelR_;
+	double blackLevelG_;
+	double blackLevelB_;
+};
+
+} /* namespace RPiController */

src/ipa/rpi/controller/rpi/ccm.cpp

@@ -0,0 +1,199 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2019, Raspberry Pi Ltd
+ *
+ * ccm.cpp - CCM (colour correction matrix) control algorithm
+ */
+
+#include <libcamera/base/log.h>
+
+#include "../awb_status.h"
+#include "../ccm_status.h"
+#include "../lux_status.h"
+#include "../metadata.h"
+
+#include "ccm.h"
+
+using namespace RPiController;
+using namespace libcamera;
+
+LOG_DEFINE_CATEGORY(RPiCcm)
+
+/*
+ * This algorithm selects a CCM (Colour Correction Matrix) according to the
+ * colour temperature estimated by AWB (interpolating between known matricies as
+ * necessary). Additionally the amount of colour saturation can be controlled
+ * both according to the current estimated lux level and according to a
+ * saturation setting that is exposed to applications.
+ */
+
+#define NAME "rpi.ccm"
+
+Matrix::Matrix()
+{
+	memset(m, 0, sizeof(m));
+}
+Matrix::Matrix(double m0, double m1, double m2, double m3, double m4, double m5,
+	       double m6, double m7, double m8)
+{
+	m[0][0] = m0, m[0][1] = m1, m[0][2] = m2, m[1][0] = m3, m[1][1] = m4,
+	m[1][2] = m5, m[2][0] = m6, m[2][1] = m7, m[2][2] = m8;
+}
+int Matrix::read(const libcamera::YamlObject &params)
+{
+	double *ptr = (double *)m;
+
+	if (params.size() != 9) {
+		LOG(RPiCcm, Error) << "Wrong number of values in CCM";
+		return -EINVAL;
+	}
+
+	for (const auto &param : params.asList()) {
+		auto value = param.get<double>();
+		if (!value)
+			return -EINVAL;
+		*ptr++ = *value;
+	}
+
+	return 0;
+}
+
+Ccm::Ccm(Controller *controller)
+	: CcmAlgorithm(controller), saturation_(1.0) {}
+
+char const *Ccm::name() const
+{
+	return NAME;
+}
+
+int Ccm::read(const libcamera::YamlObject &params)
+{
+	int ret;
+
+	if (params.contains("saturation")) {
+		ret = config_.saturation.read(params["saturation"]);
+		if (ret)
+			return ret;
+	}
+
+	for (auto &p : params["ccms"].asList()) {
+		auto value = p["ct"].get<double>();
+		if (!value)
+			return -EINVAL;
+
+		CtCcm ctCcm;
+		ctCcm.ct = *value;
+		ret = ctCcm.ccm.read(p["ccm"]);
+		if (ret)
+			return ret;
+
+		if (!config_.ccms.empty() && ctCcm.ct <= config_.ccms.back().ct) {
+			LOG(RPiCcm, Error)
+				<< "CCM not in increasing colour temperature order";
+			return -EINVAL;
+		}
+
+		config_.ccms.push_back(std::move(ctCcm));
+	}
+
+	if (config_.ccms.empty()) {
+		LOG(RPiCcm, Error) << "No CCMs specified";
+		return -EINVAL;
+	}
+
+	return 0;
+}
+
+void Ccm::setSaturation(double saturation)
+{
+	saturation_ = saturation;
+}
+
+void Ccm::initialise()
+{
+}
+
+template<typename T>
+static bool getLocked(Metadata *metadata, std::string const &tag, T &value)
+{
+	T *ptr = metadata->getLocked<T>(tag);
+	if (ptr == nullptr)
+		return false;
+	value = *ptr;
+	return true;
+}
+
+Matrix calculateCcm(std::vector<CtCcm> const &ccms, double ct)
+{
+	if (ct <= ccms.front().ct)
+		return ccms.front().ccm;
+	else if (ct >= ccms.back().ct)
+		return ccms.back().ccm;
+	else {
+		int i = 0;
+		for (; ct > ccms[i].ct; i++)
+			;
+		double lambda =
+			(ct - ccms[i - 1].ct) / (ccms[i].ct - ccms[i - 1].ct);
+		return lambda * ccms[i].ccm + (1.0 - lambda) * ccms[i - 1].ccm;
+	}
+}
+
+Matrix applySaturation(Matrix const &ccm, double saturation)
+{
+	Matrix RGB2Y(0.299, 0.587, 0.114, -0.169, -0.331, 0.500, 0.500, -0.419,
+		     -0.081);
+	Matrix Y2RGB(1.000, 0.000, 1.402, 1.000, -0.345, -0.714, 1.000, 1.771,
+		     0.000);
+	Matrix S(1, 0, 0, 0, saturation, 0, 0, 0, saturation);
+	return Y2RGB * S * RGB2Y * ccm;
+}
+
+void Ccm::prepare(Metadata *imageMetadata)
+{
+	bool awbOk = false, luxOk = false;
+	struct AwbStatus awb = {};
+	awb.temperatureK = 4000; /* in case no metadata */
+	struct LuxStatus lux = {};
+	lux.lux = 400; /* in case no metadata */
+	{
+		/* grab mutex just once to get everything */
+		std::lock_guard<Metadata> lock(*imageMetadata);
+		awbOk = getLocked(imageMetadata, "awb.status", awb);
+		luxOk = getLocked(imageMetadata, "lux.status", lux);
+	}
+	if (!awbOk)
+		LOG(RPiCcm, Warning) << "no colour temperature found";
+	if (!luxOk)
+		LOG(RPiCcm, Warning) << "no lux value found";
+	Matrix ccm = calculateCcm(config_.ccms, awb.temperatureK);
+	double saturation = saturation_;
+	struct CcmStatus ccmStatus;
+	ccmStatus.saturation = saturation;
+	if (!config_.saturation.empty())
+		saturation *= config_.saturation.eval(
+			config_.saturation.domain().clip(lux.lux));
+	ccm = applySaturation(ccm, saturation);
+	for (int j = 0; j < 3; j++)
+		for (int i = 0; i < 3; i++)
+			ccmStatus.matrix[j * 3 + i] =
+				std::max(-8.0, std::min(7.9999, ccm.m[j][i]));
+	LOG(RPiCcm, Debug)
+		<< "colour temperature " << awb.temperatureK << "K";
+	LOG(RPiCcm, Debug)
+		<< "CCM: " << ccmStatus.matrix[0] << " " << ccmStatus.matrix[1]
+		<< " " << ccmStatus.matrix[2] << "     "
+		<< ccmStatus.matrix[3] << " " << ccmStatus.matrix[4]
+		<< " " << ccmStatus.matrix[5] << "     "
+		<< ccmStatus.matrix[6] << " " << ccmStatus.matrix[7]
+		<< " " << ccmStatus.matrix[8];
+	imageMetadata->set("ccm.status", ccmStatus);
+}
+
+/* Register algorithm with the system. */
+static Algorithm *create(Controller *controller)
+{
+	return (Algorithm *)new Ccm(controller);
+	;
+}
+static RegisterAlgorithm reg(NAME, &create);

src/ipa/rpi/controller/rpi/ccm.h

@@ -0,0 +1,75 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2019, Raspberry Pi Ltd
+ *
+ * ccm.h - CCM (colour correction matrix) control algorithm
+ */
+#pragma once
+
+#include <vector>
+
+#include "../ccm_algorithm.h"
+#include "../pwl.h"
+
+namespace RPiController {
+
+/* Algorithm to calculate colour matrix. Should be placed after AWB. */
+
+struct Matrix {
+	Matrix(double m0, double m1, double m2, double m3, double m4, double m5,
+	       double m6, double m7, double m8);
+	Matrix();
+	double m[3][3];
+	int read(const libcamera::YamlObject &params);
+};
+static inline Matrix operator*(double d, Matrix const &m)
+{
+	return Matrix(m.m[0][0] * d, m.m[0][1] * d, m.m[0][2] * d,
+		      m.m[1][0] * d, m.m[1][1] * d, m.m[1][2] * d,
+		      m.m[2][0] * d, m.m[2][1] * d, m.m[2][2] * d);
+}
+static inline Matrix operator*(Matrix const &m1, Matrix const &m2)
+{
+	Matrix m;
+	for (int i = 0; i < 3; i++)
+		for (int j = 0; j < 3; j++)
+			m.m[i][j] = m1.m[i][0] * m2.m[0][j] +
+				    m1.m[i][1] * m2.m[1][j] +
+				    m1.m[i][2] * m2.m[2][j];
+	return m;
+}
+static inline Matrix operator+(Matrix const &m1, Matrix const &m2)
+{
+	Matrix m;
+	for (int i = 0; i < 3; i++)
+		for (int j = 0; j < 3; j++)
+			m.m[i][j] = m1.m[i][j] + m2.m[i][j];
+	return m;
+}
+
+struct CtCcm {
+	double ct;
+	Matrix ccm;
+};
+
+struct CcmConfig {
+	std::vector<CtCcm> ccms;
+	Pwl saturation;
+};
+
+class Ccm : public CcmAlgorithm
+{
+public:
+	Ccm(Controller *controller = NULL);
+	char const *name() const override;
+	int read(const libcamera::YamlObject &params) override;
+	void setSaturation(double saturation) override;
+	void initialise() override;
+	void prepare(Metadata *imageMetadata) override;
+
+private:
+	CcmConfig config_;
+	double saturation_;
+};
+
+} /* namespace RPiController */

src/ipa/rpi/controller/rpi/contrast.cpp

@@ -0,0 +1,181 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2019, Raspberry Pi Ltd
+ *
+ * contrast.cpp - contrast (gamma) control algorithm
+ */
+#include <stdint.h>
+
+#include <libcamera/base/log.h>
+
+#include "../contrast_status.h"
+#include "../histogram.h"
+
+#include "contrast.h"
+
+using namespace RPiController;
+using namespace libcamera;
+
+LOG_DEFINE_CATEGORY(RPiContrast)
+
+/*
+ * This is a very simple control algorithm which simply retrieves the results of
+ * AGC and AWB via their "status" metadata, and applies digital gain to the
+ * colour channels in accordance with those instructions. We take care never to
+ * apply less than unity gains, as that would cause fully saturated pixels to go
+ * off-white.
+ */
+
+#define NAME "rpi.contrast"
+
+Contrast::Contrast(Controller *controller)
+	: ContrastAlgorithm(controller), brightness_(0.0), contrast_(1.0)
+{
+}
+
+char const *Contrast::name() const
+{
+	return NAME;
+}
+
+int Contrast::read(const libcamera::YamlObject &params)
+{
+	// enable adaptive enhancement by default
+	config_.ceEnable = params["ce_enable"].get<int>(1);
+	// the point near the bottom of the histogram to move
+	config_.loHistogram = params["lo_histogram"].get<double>(0.01);
+	// where in the range to try and move it to
+	config_.loLevel = params["lo_level"].get<double>(0.015);
+	// but don't move by more than this
+	config_.loMax = params["lo_max"].get<double>(500);
+	// equivalent values for the top of the histogram...
+	config_.hiHistogram = params["hi_histogram"].get<double>(0.95);
+	config_.hiLevel = params["hi_level"].get<double>(0.95);
+	config_.hiMax = params["hi_max"].get<double>(2000);
+	return config_.gammaCurve.read(params["gamma_curve"]);
+}
+
+void Contrast::setBrightness(double brightness)
+{
+	brightness_ = brightness;
+}
+
+void Contrast::setContrast(double contrast)
+{
+	contrast_ = contrast;
+}
+
+void Contrast::initialise()
+{
+	/*
+	 * Fill in some default values as Prepare will run before Process gets
+	 * called.
+	 */
+	status_.brightness = brightness_;
+	status_.contrast = contrast_;
+	status_.gammaCurve = config_.gammaCurve;
+}
+
+void Contrast::prepare(Metadata *imageMetadata)
+{
+	imageMetadata->set("contrast.status", status_);
+}
+
+Pwl computeStretchCurve(Histogram const &histogram,
+			ContrastConfig const &config)
+{
+	Pwl enhance;
+	enhance.append(0, 0);
+	/*
+	 * If the start of the histogram is rather empty, try to pull it down a
+	 * bit.
+	 */
+	double histLo = histogram.quantile(config.loHistogram) *
+			(65536 / histogram.bins());
+	double levelLo = config.loLevel * 65536;
+	LOG(RPiContrast, Debug)
+		<< "Move histogram point " << histLo << " to " << levelLo;
+	histLo = std::max(levelLo,
+			  std::min(65535.0, std::min(histLo, levelLo + config.loMax)));
+	LOG(RPiContrast, Debug)
+		<< "Final values " << histLo << " -> " << levelLo;
+	enhance.append(histLo, levelLo);
+	/*
+	 * Keep the mid-point (median) in the same place, though, to limit the
+	 * apparent amount of global brightness shift.
+	 */
+	double mid = histogram.quantile(0.5) * (65536 / histogram.bins());
+	enhance.append(mid, mid);
+
+	/*
+	 * If the top to the histogram is empty, try to pull the pixel values
+	 * there up.
+	 */
+	double histHi = histogram.quantile(config.hiHistogram) *
+			(65536 / histogram.bins());
+	double levelHi = config.hiLevel * 65536;
+	LOG(RPiContrast, Debug)
+		<< "Move histogram point " << histHi << " to " << levelHi;
+	histHi = std::min(levelHi,
+			  std::max(0.0, std::max(histHi, levelHi - config.hiMax)));
+	LOG(RPiContrast, Debug)
+		<< "Final values " << histHi << " -> " << levelHi;
+	enhance.append(histHi, levelHi);
+	enhance.append(65535, 65535);
+	return enhance;
+}
+
+Pwl applyManualContrast(Pwl const &gammaCurve, double brightness,
+			double contrast)
+{
+	Pwl newGammaCurve;
+	LOG(RPiContrast, Debug)
+		<< "Manual brightness " << brightness << " contrast " << contrast;
+	gammaCurve.map([&](double x, double y) {
+		newGammaCurve.append(
+			x, std::max(0.0, std::min(65535.0,
+						  (y - 32768) * contrast +
+							  32768 + brightness)));
+	});
+	return newGammaCurve;
+}
+
+void Contrast::process(StatisticsPtr &stats,
+		       [[maybe_unused]] Metadata *imageMetadata)
+{
+	Histogram &histogram = stats->yHist;
+	/*
+	 * We look at the histogram and adjust the gamma curve in the following
+	 * ways: 1. Adjust the gamma curve so as to pull the start of the
+	 * histogram down, and possibly push the end up.
+	 */
+	Pwl gammaCurve = config_.gammaCurve;
+	if (config_.ceEnable) {
+		if (config_.loMax != 0 || config_.hiMax != 0)
+			gammaCurve = computeStretchCurve(histogram, config_).compose(gammaCurve);
+		/*
+		 * We could apply other adjustments (e.g. partial equalisation)
+		 * based on the histogram...?
+		 */
+	}
+	/*
+	 * 2. Finally apply any manually selected brightness/contrast
+	 * adjustment.
+	 */
+	if (brightness_ != 0 || contrast_ != 1.0)
+		gammaCurve = applyManualContrast(gammaCurve, brightness_, contrast_);
+	/*
+	 * And fill in the status for output. Use more points towards the bottom
+	 * of the curve.
+	 */
+	status_.brightness = brightness_;
+	status_.contrast = contrast_;
+	status_.gammaCurve = std::move(gammaCurve);
+}
+
+/* Register algorithm with the system. */
+static Algorithm *create(Controller *controller)
+{
+	return (Algorithm *)new Contrast(controller);
+}
+static RegisterAlgorithm reg(NAME, &create);

src/ipa/rpi/controller/rpi/contrast.h

@@ -0,0 +1,51 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2019, Raspberry Pi Ltd
+ *
+ * contrast.h - contrast (gamma) control algorithm
+ */
+#pragma once
+
+#include <mutex>
+
+#include "../contrast_algorithm.h"
+#include "../pwl.h"
+
+namespace RPiController {
+
+/*
+ * Back End algorithm to appaly correct digital gain. Should be placed after
+ * Back End AWB.
+ */
+
+struct ContrastConfig {
+	bool ceEnable;
+	double loHistogram;
+	double loLevel;
+	double loMax;
+	double hiHistogram;
+	double hiLevel;
+	double hiMax;
+	Pwl gammaCurve;
+};
+
+class Contrast : public ContrastAlgorithm
+{
+public:
+	Contrast(Controller *controller = NULL);
+	char const *name() const override;
+	int read(const libcamera::YamlObject &params) override;
+	void setBrightness(double brightness) override;
+	void setContrast(double contrast) override;
+	void initialise() override;
+	void prepare(Metadata *imageMetadata) override;
+	void process(StatisticsPtr &stats, Metadata *imageMetadata) override;
+
+private:
+	ContrastConfig config_;
+	double brightness_;
+	double contrast_;
+	ContrastStatus status_;
+};
+
+} /* namespace RPiController */

src/ipa/rpi/controller/rpi/dpc.cpp

@@ -0,0 +1,59 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2019, Raspberry Pi Ltd
+ *
+ * dpc.cpp - DPC (defective pixel correction) control algorithm
+ */
+
+#include <libcamera/base/log.h>
+
+#include "dpc.h"
+
+using namespace RPiController;
+using namespace libcamera;
+
+LOG_DEFINE_CATEGORY(RPiDpc)
+
+/*
+ * We use the lux status so that we can apply stronger settings in darkness (if
+ * necessary).
+ */
+
+#define NAME "rpi.dpc"
+
+Dpc::Dpc(Controller *controller)
+	: Algorithm(controller)
+{
+}
+
+char const *Dpc::name() const
+{
+	return NAME;
+}
+
+int Dpc::read(const libcamera::YamlObject &params)
+{
+	config_.strength = params["strength"].get<int>(1);
+	if (config_.strength < 0 || config_.strength > 2) {
+		LOG(RPiDpc, Error) << "Bad strength value";
+		return -EINVAL;
+	}
+
+	return 0;
+}
+
+void Dpc::prepare(Metadata *imageMetadata)
+{
+	DpcStatus dpcStatus = {};
+	/* Should we vary this with lux level or analogue gain? TBD. */
+	dpcStatus.strength = config_.strength;
+	LOG(RPiDpc, Debug) << "strength " << dpcStatus.strength;
+	imageMetadata->set("dpc.status", dpcStatus);
+}
+
+/* Register algorithm with the system. */
+static Algorithm *create(Controller *controller)
+{
+	return (Algorithm *)new Dpc(controller);
+}
+static RegisterAlgorithm reg(NAME, &create);

src/ipa/rpi/controller/rpi/dpc.h

@@ -0,0 +1,32 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2019, Raspberry Pi Ltd
+ *
+ * dpc.h - DPC (defective pixel correction) control algorithm
+ */
+#pragma once
+
+#include "../algorithm.h"
+#include "../dpc_status.h"
+
+namespace RPiController {
+
+/* Back End algorithm to apply appropriate GEQ settings. */
+
+struct DpcConfig {
+	int strength;
+};
+
+class Dpc : public Algorithm
+{
+public:
+	Dpc(Controller *controller);
+	char const *name() const override;
+	int read(const libcamera::YamlObject &params) override;
+	void prepare(Metadata *imageMetadata) override;
+
+private:
+	DpcConfig config_;
+};
+
+} /* namespace RPiController */

src/ipa/rpi/controller/rpi/focus.h

@@ -0,0 +1,28 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2020, Raspberry Pi Ltd
+ *
+ * focus.h - focus algorithm
+ */
+#pragma once
+
+#include "../algorithm.h"
+#include "../metadata.h"
+
+/*
+ * The "focus" algorithm. All it does it print out a version of the
+ * focus contrast measure; there is no actual auto-focus mechanism to
+ * control.
+ */
+
+namespace RPiController {
+
+class Focus : public Algorithm
+{
+public:
+	Focus(Controller *controller);
+	char const *name() const override;
+	void process(StatisticsPtr &stats, Metadata *imageMetadata) override;
+};
+
+} /* namespace RPiController */

src/ipa/rpi/controller/rpi/geq.cpp

@@ -0,0 +1,89 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2019, Raspberry Pi Ltd
+ *
+ * geq.cpp - GEQ (green equalisation) control algorithm
+ */
+
+#include <libcamera/base/log.h>
+
+#include "../device_status.h"
+#include "../lux_status.h"
+#include "../pwl.h"
+
+#include "geq.h"
+
+using namespace RPiController;
+using namespace libcamera;
+
+LOG_DEFINE_CATEGORY(RPiGeq)
+
+/*
+ * We use the lux status so that we can apply stronger settings in darkness (if
+ * necessary).
+ */
+
+#define NAME "rpi.geq"
+
+Geq::Geq(Controller *controller)
+	: Algorithm(controller)
+{
+}
+
+char const *Geq::name() const
+{
+	return NAME;
+}
+
+int Geq::read(const libcamera::YamlObject &params)
+{
+	config_.offset = params["offset"].get<uint16_t>(0);
+	config_.slope = params["slope"].get<double>(0.0);
+	if (config_.slope < 0.0 || config_.slope >= 1.0) {
+		LOG(RPiGeq, Error) << "Bad slope value";
+		return -EINVAL;
+	}
+
+	if (params.contains("strength")) {
+		int ret = config_.strength.read(params["strength"]);
+		if (ret)
+			return ret;
+	}
+
+	return 0;
+}
+
+void Geq::prepare(Metadata *imageMetadata)
+{
+	LuxStatus luxStatus = {};
+	luxStatus.lux = 400;
+	if (imageMetadata->get("lux.status", luxStatus))
+		LOG(RPiGeq, Warning) << "no lux data found";
+	DeviceStatus deviceStatus;
+	deviceStatus.analogueGain = 1.0; /* in case not found */
+	if (imageMetadata->get("device.status", deviceStatus))
+		LOG(RPiGeq, Warning)
+			<< "no device metadata - use analogue gain of 1x";
+	GeqStatus geqStatus = {};
+	double strength = config_.strength.empty()
+			? 1.0
+			: config_.strength.eval(config_.strength.domain().clip(luxStatus.lux));
+	strength *= deviceStatus.analogueGain;
+	double offset = config_.offset * strength;
+	double slope = config_.slope * strength;
+	geqStatus.offset = std::min(65535.0, std::max(0.0, offset));
+	geqStatus.slope = std::min(.99999, std::max(0.0, slope));
+	LOG(RPiGeq, Debug)
+		<< "offset " << geqStatus.offset << " slope "
+		<< geqStatus.slope << " (analogue gain "
+		<< deviceStatus.analogueGain << " lux "
+		<< luxStatus.lux << ")";
+	imageMetadata->set("geq.status", geqStatus);
+}
+
+/* Register algorithm with the system. */
+static Algorithm *create(Controller *controller)
+{
+	return (Algorithm *)new Geq(controller);
+}
+static RegisterAlgorithm reg(NAME, &create);

src/ipa/rpi/controller/rpi/geq.h

@@ -0,0 +1,34 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2019, Raspberry Pi Ltd
+ *
+ * geq.h - GEQ (green equalisation) control algorithm
+ */
+#pragma once
+
+#include "../algorithm.h"
+#include "../geq_status.h"
+
+namespace RPiController {
+
+/* Back End algorithm to apply appropriate GEQ settings. */
+
+struct GeqConfig {
+	uint16_t offset;
+	double slope;
+	Pwl strength; /* lux to strength factor */
+};
+
+class Geq : public Algorithm
+{
+public:
+	Geq(Controller *controller);
+	char const *name() const override;
+	int read(const libcamera::YamlObject &params) override;
+	void prepare(Metadata *imageMetadata) override;
+
+private:
+	GeqConfig config_;
+};
+
+} /* namespace RPiController */

src/ipa/rpi/controller/rpi/lux.cpp

@@ -0,0 +1,115 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2019, Raspberry Pi Ltd
+ *
+ * lux.cpp - Lux control algorithm
+ */
+#include <math.h>
+
+#include <libcamera/base/log.h>
+
+#include "../device_status.h"
+
+#include "lux.h"
+
+using namespace RPiController;
+using namespace libcamera;
+using namespace std::literals::chrono_literals;
+
+LOG_DEFINE_CATEGORY(RPiLux)
+
+#define NAME "rpi.lux"
+
+Lux::Lux(Controller *controller)
+	: Algorithm(controller)
+{
+	/*
+	 * Put in some defaults as there will be no meaningful values until
+	 * Process has run.
+	 */
+	status_.aperture = 1.0;
+	status_.lux = 400;
+}
+
+char const *Lux::name() const
+{
+	return NAME;
+}
+
+int Lux::read(const libcamera::YamlObject &params)
+{
+	auto value = params["reference_shutter_speed"].get<double>();
+	if (!value)
+		return -EINVAL;
+	referenceShutterSpeed_ = *value * 1.0us;
+
+	value = params["reference_gain"].get<double>();
+	if (!value)
+		return -EINVAL;
+	referenceGain_ = *value;
+
+	referenceAperture_ = params["reference_aperture"].get<double>(1.0);
+
+	value = params["reference_Y"].get<double>();
+	if (!value)
+		return -EINVAL;
+	referenceY_ = *value;
+
+	value = params["reference_lux"].get<double>();
+	if (!value)
+		return -EINVAL;
+	referenceLux_ = *value;
+
+	currentAperture_ = referenceAperture_;
+	return 0;
+}
+
+void Lux::setCurrentAperture(double aperture)
+{
+	currentAperture_ = aperture;
+}
+
+void Lux::prepare(Metadata *imageMetadata)
+{
+	std::unique_lock<std::mutex> lock(mutex_);
+	imageMetadata->set("lux.status", status_);
+}
+
+void Lux::process(StatisticsPtr &stats, Metadata *imageMetadata)
+{
+	DeviceStatus deviceStatus;
+	if (imageMetadata->get("device.status", deviceStatus) == 0) {
+		double currentGain = deviceStatus.analogueGain;
+		double currentAperture = deviceStatus.aperture.value_or(currentAperture_);
+		double currentY = stats->yHist.interQuantileMean(0, 1);
+		double gainRatio = referenceGain_ / currentGain;
+		double shutterSpeedRatio =
+			referenceShutterSpeed_ / deviceStatus.shutterSpeed;
+		double apertureRatio = referenceAperture_ / currentAperture;
+		double yRatio = currentY * (65536 / stats->yHist.bins()) / referenceY_;
+		double estimatedLux = shutterSpeedRatio * gainRatio *
+				      apertureRatio * apertureRatio *
+				      yRatio * referenceLux_;
+		LuxStatus status;
+		status.lux = estimatedLux;
+		status.aperture = currentAperture;
+		LOG(RPiLux, Debug) << ": estimated lux " << estimatedLux;
+		{
+			std::unique_lock<std::mutex> lock(mutex_);
+			status_ = status;
+		}
+		/*
+		 * Overwrite the metadata here as well, so that downstream
+		 * algorithms get the latest value.
+		 */
+		imageMetadata->set("lux.status", status);
+	} else
+		LOG(RPiLux, Warning) << ": no device metadata";
+}
+
+/* Register algorithm with the system. */
+static Algorithm *create(Controller *controller)
+{
+	return (Algorithm *)new Lux(controller);
+}
+static RegisterAlgorithm reg(NAME, &create);

src/ipa/rpi/controller/rpi/lux.h

@@ -0,0 +1,45 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2019, Raspberry Pi Ltd
+ *
+ * lux.h - Lux control algorithm
+ */
+#pragma once
+
+#include <mutex>
+
+#include <libcamera/base/utils.h>
+
+#include "../lux_status.h"
+#include "../algorithm.h"
+
+/* This is our implementation of the "lux control algorithm". */
+
+namespace RPiController {
+
+class Lux : public Algorithm
+{
+public:
+	Lux(Controller *controller);
+	char const *name() const override;
+	int read(const libcamera::YamlObject &params) override;
+	void prepare(Metadata *imageMetadata) override;
+	void process(StatisticsPtr &stats, Metadata *imageMetadata) override;
+	void setCurrentAperture(double aperture);
+
+private:
+	/*
+	 * These values define the conditions of the reference image, against
+	 * which we compare the new image.
+	 */
+	libcamera::utils::Duration referenceShutterSpeed_;
+	double referenceGain_;
+	double referenceAperture_; /* units of 1/f */
+	double referenceY_; /* out of 65536 */
+	double referenceLux_;
+	double currentAperture_;
+	LuxStatus status_;
+	std::mutex mutex_;
+};
+
+} /* namespace RPiController */

src/ipa/rpi/controller/rpi/noise.cpp

@@ -0,0 +1,89 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2019, Raspberry Pi Ltd
+ *
+ * noise.cpp - Noise control algorithm
+ */
+
+#include <math.h>
+
+#include <libcamera/base/log.h>
+
+#include "../device_status.h"
+#include "../noise_status.h"
+
+#include "noise.h"
+
+using namespace RPiController;
+using namespace libcamera;
+
+LOG_DEFINE_CATEGORY(RPiNoise)
+
+#define NAME "rpi.noise"
+
+Noise::Noise(Controller *controller)
+	: Algorithm(controller), modeFactor_(1.0)
+{
+}
+
+char const *Noise::name() const
+{
+	return NAME;
+}
+
+void Noise::switchMode(CameraMode const &cameraMode,
+		       [[maybe_unused]] Metadata *metadata)
+{
+	/*
+	 * For example, we would expect a 2x2 binned mode to have a "noise
+	 * factor" of sqrt(2x2) = 2. (can't be less than one, right?)
+	 */
+	modeFactor_ = std::max(1.0, cameraMode.noiseFactor);
+}
+
+int Noise::read(const libcamera::YamlObject &params)
+{
+	auto value = params["reference_constant"].get<double>();
+	if (!value)
+		return -EINVAL;
+	referenceConstant_ = *value;
+
+	value = params["reference_slope"].get<double>();
+	if (!value)
+		return -EINVAL;
+	referenceSlope_ = *value;
+
+	return 0;
+}
+
+void Noise::prepare(Metadata *imageMetadata)
+{
+	struct DeviceStatus deviceStatus;
+	deviceStatus.analogueGain = 1.0; /* keep compiler calm */
+	if (imageMetadata->get("device.status", deviceStatus) == 0) {
+		/*
+		 * There is a slight question as to exactly how the noise
+		 * profile, specifically the constant part of it, scales. For
+		 * now we assume it all scales the same, and we'll revisit this
+		 * if it proves substantially wrong.  NOTE: we may also want to
+		 * make some adjustments based on the camera mode (such as
+		 * binning), if we knew how to discover it...
+		 */
+		double factor = sqrt(deviceStatus.analogueGain) / modeFactor_;
+		struct NoiseStatus status;
+		status.noiseConstant = referenceConstant_ * factor;
+		status.noiseSlope = referenceSlope_ * factor;
+		imageMetadata->set("noise.status", status);
+		LOG(RPiNoise, Debug)
+			<< "constant " << status.noiseConstant
+			<< " slope " << status.noiseSlope;
+	} else
+		LOG(RPiNoise, Warning) << " no metadata";
+}
+
+/* Register algorithm with the system. */
+static Algorithm *create(Controller *controller)
+{
+	return new Noise(controller);
+}
+static RegisterAlgorithm reg(NAME, &create);

src/ipa/rpi/controller/rpi/noise.h

@@ -0,0 +1,32 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2019, Raspberry Pi Ltd
+ *
+ * noise.h - Noise control algorithm
+ */
+#pragma once
+
+#include "../algorithm.h"
+#include "../noise_status.h"
+
+/* This is our implementation of the "noise algorithm". */
+
+namespace RPiController {
+
+class Noise : public Algorithm
+{
+public:
+	Noise(Controller *controller);
+	char const *name() const override;
+	void switchMode(CameraMode const &cameraMode, Metadata *metadata) override;
+	int read(const libcamera::YamlObject &params) override;
+	void prepare(Metadata *imageMetadata) override;
+
+private:
+	/* the noise profile for analogue gain of 1.0 */
+	double referenceConstant_;
+	double referenceSlope_;
+	double modeFactor_;
+};
+
+} /* namespace RPiController */

src/ipa/rpi/controller/rpi/sdn.cpp

@@ -0,0 +1,80 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2019-2021, Raspberry Pi Ltd
+ *
+ * sdn.cpp - SDN (spatial denoise) control algorithm
+ */
+
+#include <libcamera/base/log.h>
+
+#include "../denoise_status.h"
+#include "../noise_status.h"
+
+#include "sdn.h"
+
+using namespace RPiController;
+using namespace libcamera;
+
+LOG_DEFINE_CATEGORY(RPiSdn)
+
+/*
+ * Calculate settings for the spatial denoise block using the noise profile in
+ * the image metadata.
+ */
+
+#define NAME "rpi.sdn"
+
+Sdn::Sdn(Controller *controller)
+	: DenoiseAlgorithm(controller), mode_(DenoiseMode::ColourOff)
+{
+}
+
+char const *Sdn::name() const
+{
+	return NAME;
+}
+
+int Sdn::read(const libcamera::YamlObject &params)
+{
+	deviation_ = params["deviation"].get<double>(3.2);
+	strength_ = params["strength"].get<double>(0.75);
+	return 0;
+}
+
+void Sdn::initialise()
+{
+}
+
+void Sdn::prepare(Metadata *imageMetadata)
+{
+	struct NoiseStatus noiseStatus = {};
+	noiseStatus.noiseSlope = 3.0; /* in case no metadata */
+	if (imageMetadata->get("noise.status", noiseStatus) != 0)
+		LOG(RPiSdn, Warning) << "no noise profile found";
+	LOG(RPiSdn, Debug)
+		<< "Noise profile: constant " << noiseStatus.noiseConstant
+		<< " slope " << noiseStatus.noiseSlope;
+	struct DenoiseStatus status;
+	status.noiseConstant = noiseStatus.noiseConstant * deviation_;
+	status.noiseSlope = noiseStatus.noiseSlope * deviation_;
+	status.strength = strength_;
+	status.mode = static_cast<std::underlying_type_t<DenoiseMode>>(mode_);
+	imageMetadata->set("denoise.status", status);
+	LOG(RPiSdn, Debug)
+		<< "programmed constant " << status.noiseConstant
+		<< " slope " << status.noiseSlope
+		<< " strength " << status.strength;
+}
+
+void Sdn::setMode(DenoiseMode mode)
+{
+	/* We only distinguish between off and all other modes. */
+	mode_ = mode;
+}
+
+/* Register algorithm with the system. */
+static Algorithm *create(Controller *controller)
+{
+	return (Algorithm *)new Sdn(controller);
+}
+static RegisterAlgorithm reg(NAME, &create);

src/ipa/rpi/controller/rpi/sdn.h

@@ -0,0 +1,32 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2019, Raspberry Pi Ltd
+ *
+ * sdn.h - SDN (spatial denoise) control algorithm
+ */
+#pragma once
+
+#include "../algorithm.h"
+#include "../denoise_algorithm.h"
+
+namespace RPiController {
+
+/* Algorithm to calculate correct spatial denoise (SDN) settings. */
+
+class Sdn : public DenoiseAlgorithm
+{
+public:
+	Sdn(Controller *controller = NULL);
+	char const *name() const override;
+	int read(const libcamera::YamlObject &params) override;
+	void initialise() override;
+	void prepare(Metadata *imageMetadata) override;
+	void setMode(DenoiseMode mode) override;
+
+private:
+	double deviation_;
+	double strength_;
+	DenoiseMode mode_;
+};
+
+} /* namespace RPiController */

src/ipa/rpi/controller/rpi/sharpen.cpp

@@ -0,0 +1,92 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2019, Raspberry Pi Ltd
+ *
+ * sharpen.cpp - sharpening control algorithm
+ */
+
+#include <math.h>
+
+#include <libcamera/base/log.h>
+
+#include "../sharpen_status.h"
+
+#include "sharpen.h"
+
+using namespace RPiController;
+using namespace libcamera;
+
+LOG_DEFINE_CATEGORY(RPiSharpen)
+
+#define NAME "rpi.sharpen"
+
+Sharpen::Sharpen(Controller *controller)
+	: SharpenAlgorithm(controller), userStrength_(1.0)
+{
+}
+
+char const *Sharpen::name() const
+{
+	return NAME;
+}
+
+void Sharpen::switchMode(CameraMode const &cameraMode,
+			 [[maybe_unused]] Metadata *metadata)
+{
+	/* can't be less than one, right? */
+	modeFactor_ = std::max(1.0, cameraMode.noiseFactor);
+}
+
+int Sharpen::read(const libcamera::YamlObject &params)
+{
+	threshold_ = params["threshold"].get<double>(1.0);
+	strength_ = params["strength"].get<double>(1.0);
+	limit_ = params["limit"].get<double>(1.0);
+	LOG(RPiSharpen, Debug)
+		<< "Read threshold " << threshold_
+		<< " strength " << strength_
+		<< " limit " << limit_;
+	return 0;
+}
+
+void Sharpen::setStrength(double strength)
+{
+	/*
+	 * Note that this function is how an application sets the overall
+	 * sharpening "strength". We call this the "user strength" field
+	 * as there already is a strength_ field - being an internal gain
+	 * parameter that gets passed to the ISP control code. Negative
+	 * values are not allowed - coerce them to zero (no sharpening).
+	 */
+	userStrength_ = std::max(0.0, strength);
+}
+
+void Sharpen::prepare(Metadata *imageMetadata)
+{
+	/*
+	 * The userStrength_ affects the algorithm's internal gain directly, but
+	 * we adjust the limit and threshold less aggressively. Using a sqrt
+	 * function is an arbitrary but gentle way of accomplishing this.
+	 */
+	double userStrengthSqrt = sqrt(userStrength_);
+	struct SharpenStatus status;
+	/*
+	 * Binned modes seem to need the sharpening toned down with this
+	 * pipeline, thus we use the modeFactor_ here. Also avoid
+	 * divide-by-zero with the userStrengthSqrt.
+	 */
+	status.threshold = threshold_ * modeFactor_ /
+			   std::max(0.01, userStrengthSqrt);
+	status.strength = strength_ / modeFactor_ * userStrength_;
+	status.limit = limit_ / modeFactor_ * userStrengthSqrt;
+	/* Finally, report any application-supplied parameters that were used. */
+	status.userStrength = userStrength_;
+	imageMetadata->set("sharpen.status", status);
+}
+
+/* Register algorithm with the system. */
+static Algorithm *create(Controller *controller)
+{
+	return new Sharpen(controller);
+}
+static RegisterAlgorithm reg(NAME, &create);

src/ipa/rpi/controller/rpi/sharpen.h

@@ -0,0 +1,34 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2019, Raspberry Pi Ltd
+ *
+ * sharpen.h - sharpening control algorithm
+ */
+#pragma once
+
+#include "../sharpen_algorithm.h"
+#include "../sharpen_status.h"
+
+/* This is our implementation of the "sharpen algorithm". */
+
+namespace RPiController {
+
+class Sharpen : public SharpenAlgorithm
+{
+public:
+	Sharpen(Controller *controller);
+	char const *name() const override;
+	void switchMode(CameraMode const &cameraMode, Metadata *metadata) override;
+	int read(const libcamera::YamlObject &params) override;
+	void setStrength(double strength) override;
+	void prepare(Metadata *imageMetadata) override;
+
+private:
+	double threshold_;
+	double strength_;
+	double limit_;
+	double modeFactor_;
+	double userStrength_;
+};
+
+} /* namespace RPiController */

src/ipa/rpi/controller/sharpen_algorithm.h

@@ -0,0 +1,21 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2020, Raspberry Pi Ltd
+ *
+ * sharpen_algorithm.h - sharpness control algorithm interface
+ */
+#pragma once
+
+#include "algorithm.h"
+
+namespace RPiController {
+
+class SharpenAlgorithm : public Algorithm
+{
+public:
+	SharpenAlgorithm(Controller *controller) : Algorithm(controller) {}
+	/* A sharpness control algorithm must provide the following: */
+	virtual void setStrength(double strength) = 0;
+};
+
+} /* namespace RPiController */

src/ipa/rpi/controller/sharpen_status.h

@@ -0,0 +1,20 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2019, Raspberry Pi Ltd
+ *
+ * sharpen_status.h - Sharpen control algorithm status
+ */
+#pragma once
+
+/* The "sharpen" algorithm stores the strength to use. */
+
+struct SharpenStatus {
+	/* controls the smallest level of detail (or noise!) that sharpening will pick up */
+	double threshold;
+	/* the rate at which the sharpening response ramps once above the threshold */
+	double strength;
+	/* upper limit of the allowed sharpening response */
+	double limit;
+	/* The sharpening strength requested by the user or application. */
+	double userStrength;
+};

src/ipa/rpi/controller/statistics.h

@@ -0,0 +1,78 @@
+/* SPDX-License-Identifier: BSD-2-Clause */
+/*
+ * Copyright (C) 2022, Raspberry Pi Ltd
+ *
+ * statistics.h - Raspberry Pi generic statistics structure
+ */
+#pragma once
+
+#include <memory>
+#include <stdint.h>
+#include <vector>
+
+#include "histogram.h"
+#include "region_stats.h"
+
+namespace RPiController {
+
+struct RgbySums {
+	RgbySums(uint64_t _rSum = 0, uint64_t _gSum = 0, uint64_t _bSum = 0, uint64_t _ySum = 0)
+		: rSum(_rSum), gSum(_gSum), bSum(_bSum), ySum(_ySum)
+	{
+	}
+	uint64_t rSum;
+	uint64_t gSum;
+	uint64_t bSum;
+	uint64_t ySum;
+};
+
+using RgbyRegions = RegionStats<RgbySums>;
+using FocusRegions = RegionStats<uint64_t>;
+
+struct Statistics {
+	/*
+	 * All region based statistics are normalised to 16-bits, giving a
+	 * maximum value of (1 << NormalisationFactorPow2) - 1.
+	 */
+	static constexpr unsigned int NormalisationFactorPow2 = 16;
+
+	/*
+	 * Positioning of the AGC statistics gathering in the pipeline:
+	 * Pre-WB correction or post-WB correction.
+	 * Assume this is post-LSC.
+	 */
+	enum class AgcStatsPos { PreWb, PostWb };
+	const AgcStatsPos agcStatsPos;
+
+	/*
+	 * Positioning of the AWB/ALSC statistics gathering in the pipeline:
+	 * Pre-LSC or post-LSC.
+	 */
+	enum class ColourStatsPos { PreLsc, PostLsc };
+	const ColourStatsPos colourStatsPos;
+
+	Statistics(AgcStatsPos a, ColourStatsPos c)
+		: agcStatsPos(a), colourStatsPos(c)
+	{
+	}
+
+	/* Histogram statistics. Not all histograms may be populated! */
+	Histogram rHist;
+	Histogram gHist;
+	Histogram bHist;
+	Histogram yHist;
+
+	/* Row sums for flicker avoidance. */
+	std::vector<RgbySums> rowSums;
+
+	/* Region based colour sums. */
+	RgbyRegions agcRegions;
+	RgbyRegions awbRegions;
+
+	/* Region based focus FoM. */
+	FocusRegions focusRegions;
+};
+
+using StatisticsPtr = std::shared_ptr<Statistics>;
+
+} /* namespace RPiController */