summaryrefslogtreecommitdiff
path: root/test/mapped-buffer.cpp
blob: 97571945cbca99a544912c4f1d9421e1d34d305f (plain)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
/* SPDX-License-Identifier: GPL-2.0-or-later */
/*
 * Copyright (C) 2020, Google Inc.
 *
 * libcamera internal MappedBuffer tests
 */

#include <iostream>

#include <libcamera/framebuffer_allocator.h>

#include "libcamera/internal/mapped_framebuffer.h"

#include "camera_test.h"
#include "test.h"

using namespace std;

namespace {

class MappedBufferTest : public CameraTest, public Test
{
public:
	MappedBufferTest()
		: CameraTest("platform/vimc.0 Sensor B")
	{
	}

protected:
	int init() override
	{
		if (status_ != TestPass)
			return status_;

		config_ = camera_->generateConfiguration({ StreamRole::VideoRecording });
		if (!config_ || config_->size() != 1) {
			cout << "Failed to generate default configuration" << endl;
			return TestFail;
		}

		allocator_ = new FrameBufferAllocator(camera_);

		StreamConfiguration &cfg = config_->at(0);

		if (camera_->acquire()) {
			cout << "Failed to acquire the camera" << endl;
			return TestFail;
		}

		if (camera_->configure(config_.get())) {
			cout << "Failed to set default configuration" << endl;
			return TestFail;
		}

		stream_ = cfg.stream();

		int ret = allocator_->allocate(stream_);
		if (ret < 0)
			return TestFail;

		return TestPass;
	}

	void cleanup() override
	{
		delete allocator_;
	}

	int run() override
	{
		const std::unique_ptr<FrameBuffer> &buffer = allocator_->buffers(stream_).front();
		std::vector<MappedBuffer> maps;

		MappedFrameBuffer map(buffer.get(), MappedFrameBuffer::MapFlag::Read);
		if (!map.isValid()) {
			cout << "Failed to successfully map buffer" << endl;
			return TestFail;
		}

		/* Make sure we can move it. */
		maps.emplace_back(std::move(map));

		/* But copying is prevented, it would cause double-unmap. */
		// MappedFrameBuffer map_copy = map;

		/* Local map should be invalid (after move). */
		if (map.isValid()) {
			cout << "Post-move map should not be valid" << endl;
			return TestFail;
		}

		/* Test for multiple successful maps on the same buffer. */
		MappedFrameBuffer write_map(buffer.get(), MappedFrameBuffer::MapFlag::Write);
		if (!write_map.isValid()) {
			cout << "Failed to map write buffer" << endl;
			return TestFail;
		}

		MappedFrameBuffer rw_map(buffer.get(), MappedFrameBuffer::MapFlag::ReadWrite);
		if (!rw_map.isValid()) {
			cout << "Failed to map RW buffer" << endl;
			return TestFail;
		}

		return TestPass;
	}

private:
	std::unique_ptr<CameraConfiguration> config_;
	FrameBufferAllocator *allocator_;
	Stream *stream_;
};

} /* namespace */

TEST_REGISTER(MappedBufferTest)
n406' href='#n406'>406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604 605 606 607 608 609 610 611 612 613 614 615 616 617 618 619 620 621 622 623 624 625 626 627 628 629 630 631 632 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648 649 650 651 652 653 654 655 656 657 658 659 660 661 662 663 664 665 666 667 668 669 670 671 672 673 674 675 676 677 678 679 680 681 682 683 684 685 686 687 688 689 690 691 692
/* SPDX-License-Identifier: LGPL-2.1-or-later */
/*
 * Copyright (C) 2020, Google Inc.
 *
 * IPU3 Image Processing Algorithms
 */

#include <algorithm>
#include <array>
#include <cmath>
#include <limits>
#include <map>
#include <memory>
#include <stdint.h>
#include <utility>
#include <vector>

#include <linux/intel-ipu3.h>
#include <linux/v4l2-controls.h>

#include <libcamera/base/file.h>
#include <libcamera/base/log.h>
#include <libcamera/base/utils.h>

#include <libcamera/control_ids.h>
#include <libcamera/controls.h>
#include <libcamera/framebuffer.h>
#include <libcamera/geometry.h>
#include <libcamera/request.h>

#include <libcamera/ipa/ipa_interface.h>
#include <libcamera/ipa/ipa_module_info.h>
#include <libcamera/ipa/ipu3_ipa_interface.h>

#include "libcamera/internal/mapped_framebuffer.h"
#include "libcamera/internal/yaml_parser.h"

#include "libipa/camera_sensor_helper.h"

#include "ipa_context.h"
#include "module.h"

/* Minimum grid width, expressed as a number of cells */
static constexpr uint32_t kMinGridWidth = 16;
/* Maximum grid width, expressed as a number of cells */
static constexpr uint32_t kMaxGridWidth = 80;
/* Minimum grid height, expressed as a number of cells */
static constexpr uint32_t kMinGridHeight = 16;
/* Maximum grid height, expressed as a number of cells */
static constexpr uint32_t kMaxGridHeight = 60;
/* log2 of the minimum grid cell width and height, in pixels */
static constexpr uint32_t kMinCellSizeLog2 = 3;
/* log2 of the maximum grid cell width and height, in pixels */
static constexpr uint32_t kMaxCellSizeLog2 = 6;

/* Maximum number of frame contexts to be held */
static constexpr uint32_t kMaxFrameContexts = 16;

namespace libcamera {

LOG_DEFINE_CATEGORY(IPAIPU3)

using namespace std::literals::chrono_literals;

namespace ipa::ipu3 {

/**
 * \brief The IPU3 IPA implementation
 *
 * The IPU3 Pipeline defines an IPU3-specific interface for communication
 * between the PipelineHandler and the IPA module.
 *
 * We extend the IPAIPU3Interface to implement our algorithms and handle
 * calls from the IPU3 PipelineHandler to satisfy requests from the
 * application.
 *
 * At initialisation time, a CameraSensorHelper is instantiated to support
 * camera-specific calculations, while the default controls are computed, and
 * the algorithms are instantiated from the tuning data file.
 *
 * The IPU3 ImgU operates with a grid layout to divide the overall frame into
 * rectangular cells of pixels. When the IPA is configured, we determine the
 * best grid for the statistics based on the pipeline handler Bayer Down Scaler
 * output size.
 *
 * Two main events are then handled to operate the IPU3 ImgU by populating its
 * parameter buffer, and adapting the settings of the sensor attached to the
 * IPU3 CIO2 through sensor-specific V4L2 controls.
 *
 * In fillParamsBuffer(), we populate the ImgU parameter buffer with
 * settings to configure the device in preparation for handling the frame
 * queued in the Request.
 *
 * When the frame has completed processing, the ImgU will generate a statistics
 * buffer which is given to the IPA with processStatsBuffer(). In this we run the
 * algorithms to parse the statistics and cache any results for the next
 * fillParamsBuffer() call.
 *
 * The individual algorithms are split into modular components that are called
 * iteratively to allow them to process statistics from the ImgU in the order
 * defined in the tuning data file.
 *
 * The current implementation supports five core algorithms:
 *
 * - Auto focus (AF)
 * - Automatic gain and exposure control (AGC)
 * - Automatic white balance (AWB)
 * - Black level correction (BLC)
 * - Tone mapping (Gamma)
 *
 * AWB is implemented using a Greyworld algorithm, and calculates the red and
 * blue gains to apply to generate a neutral grey frame overall.
 *
 * AGC is handled by calculating a histogram of the green channel to estimate an
 * analogue gain and shutter time which will provide a well exposed frame. A
 * low-pass IIR filter is used to smooth the changes to the sensor to reduce
 * perceivable steps.
 *
 * The tone mapping algorithm provides a gamma correction table to improve the
 * contrast of the scene.
 *
 * The black level compensation algorithm subtracts a hardcoded black level from
 * all pixels.
 *
 * The IPU3 ImgU has further processing blocks to support image quality
 * improvements through bayer and temporal noise reductions, however those are
 * not supported in the current implementation, and will use default settings as
 * provided by the kernel driver.
 *
 * Demosaicing is operating with the default parameters and could be further
 * optimised to provide improved sharpening coefficients, checker artifact
 * removal, and false color correction.
 *
 * Additional image enhancements can be made by providing lens and
 * sensor-specific tuning to adapt for Black Level compensation (BLC), Lens
 * shading correction (SHD) and Color correction (CCM).
 */
class IPAIPU3 : public IPAIPU3Interface, public Module
{
public:
	IPAIPU3();

	int init(const IPASettings &settings,
		 const IPACameraSensorInfo &sensorInfo,
		 const ControlInfoMap &sensorControls,
		 ControlInfoMap *ipaControls) override;

	int start() override;
	void stop() override;

	int configure(const IPAConfigInfo &configInfo,
		      ControlInfoMap *ipaControls) override;

	void mapBuffers(const std::vector<IPABuffer> &buffers) override;
	void unmapBuffers(const std::vector<unsigned int> &ids) override;

	void queueRequest(const uint32_t frame, const ControlList &controls) override;
	void fillParamsBuffer(const uint32_t frame, const uint32_t bufferId) override;
	void processStatsBuffer(const uint32_t frame, const int64_t frameTimestamp,
				const uint32_t bufferId,
				const ControlList &sensorControls) override;

protected:
	std::string logPrefix() const override;

private:
	void updateControls(const IPACameraSensorInfo &sensorInfo,
			    const ControlInfoMap &sensorControls,
			    ControlInfoMap *ipaControls);
	void updateSessionConfiguration(const ControlInfoMap &sensorControls);

	void setControls(unsigned int frame);
	void calculateBdsGrid(const Size &bdsOutputSize);

	std::map<unsigned int, MappedFrameBuffer> buffers_;

	ControlInfoMap sensorCtrls_;
	ControlInfoMap lensCtrls_;

	IPACameraSensorInfo sensorInfo_;

	/* Interface to the Camera Helper */
	std::unique_ptr<CameraSensorHelper> camHelper_;

	/* Local parameter storage */
	struct IPAContext context_;
};

IPAIPU3::IPAIPU3()
	: context_({ {}, {}, { kMaxFrameContexts }, {} })
{
}

std::string IPAIPU3::logPrefix() const
{
	return "ipu3";
}

/**
 * \brief Compute IPASessionConfiguration using the sensor information and the
 * sensor V4L2 controls
 */
void IPAIPU3::updateSessionConfiguration(const ControlInfoMap &sensorControls)
{
	const ControlInfo vBlank = sensorControls.find(V4L2_CID_VBLANK)->second;
	context_.configuration.sensor.defVBlank = vBlank.def().get<int32_t>();

	const ControlInfo &v4l2Exposure = sensorControls.find(V4L2_CID_EXPOSURE)->second;
	int32_t minExposure = v4l2Exposure.min().get<int32_t>();
	int32_t maxExposure = v4l2Exposure.max().get<int32_t>();

	const ControlInfo &v4l2Gain = sensorControls.find(V4L2_CID_ANALOGUE_GAIN)->second;
	int32_t minGain = v4l2Gain.min().get<int32_t>();
	int32_t maxGain = v4l2Gain.max().get<int32_t>();

	/*
	 * When the AGC computes the new exposure values for a frame, it needs
	 * to know the limits for shutter speed and analogue gain.
	 * As it depends on the sensor, update it with the controls.
	 *
	 * \todo take VBLANK into account for maximum shutter speed
	 */
	context_.configuration.agc.minShutterSpeed = minExposure * context_.configuration.sensor.lineDuration;
	context_.configuration.agc.maxShutterSpeed = maxExposure * context_.configuration.sensor.lineDuration;
	context_.configuration.agc.minAnalogueGain = camHelper_->gain(minGain);
	context_.configuration.agc.maxAnalogueGain = camHelper_->gain(maxGain);
}

/**
 * \brief Compute camera controls using the sensor information and the sensor
 * V4L2 controls
 *
 * Some of the camera controls are computed by the pipeline handler, some others
 * by the IPA module which is in charge of handling, for example, the exposure
 * time and the frame duration.
 *
 * This function computes:
 * - controls::ExposureTime
 * - controls::FrameDurationLimits
 */
void IPAIPU3::updateControls(const IPACameraSensorInfo &sensorInfo,
			     const ControlInfoMap &sensorControls,
			     ControlInfoMap *ipaControls)
{
	ControlInfoMap::Map controls{};
	double lineDuration = context_.configuration.sensor.lineDuration.get<std::micro>();

	/*
	 * Compute exposure time limits by using line length and pixel rate
	 * converted to microseconds. Use the V4L2_CID_EXPOSURE control to get
	 * exposure min, max and default and convert it from lines to
	 * microseconds.
	 */
	const ControlInfo &v4l2Exposure = sensorControls.find(V4L2_CID_EXPOSURE)->second;
	int32_t minExposure = v4l2Exposure.min().get<int32_t>() * lineDuration;
	int32_t maxExposure = v4l2Exposure.max().get<int32_t>() * lineDuration;
	int32_t defExposure = v4l2Exposure.def().get<int32_t>() * lineDuration;
	controls[&controls::ExposureTime] = ControlInfo(minExposure, maxExposure,
							defExposure);

	/*
	 * Compute the frame duration limits.
	 *
	 * The frame length is computed assuming a fixed line length combined
	 * with the vertical frame sizes.
	 */
	const ControlInfo &v4l2HBlank = sensorControls.find(V4L2_CID_HBLANK)->second;
	uint32_t hblank = v4l2HBlank.def().get<int32_t>();
	uint32_t lineLength = sensorInfo.outputSize.width + hblank;

	const ControlInfo &v4l2VBlank = sensorControls.find(V4L2_CID_VBLANK)->second;
	std::array<uint32_t, 3> frameHeights{
		v4l2VBlank.min().get<int32_t>() + sensorInfo.outputSize.height,
		v4l2VBlank.max().get<int32_t>() + sensorInfo.outputSize.height,
		v4l2VBlank.def().get<int32_t>() + sensorInfo.outputSize.height,
	};

	std::array<int64_t, 3> frameDurations;
	for (unsigned int i = 0; i < frameHeights.size(); ++i) {
		uint64_t frameSize = lineLength * frameHeights[i];
		frameDurations[i] = frameSize / (sensorInfo.pixelRate / 1000000U);
	}

	controls[&controls::FrameDurationLimits] = ControlInfo(frameDurations[0],
							       frameDurations[1],
							       frameDurations[2]);

	controls.merge(context_.ctrlMap);
	*ipaControls = ControlInfoMap(std::move(controls), controls::controls);
}

/**
 * \brief Initialize the IPA module and its controls
 *
 * This function receives the camera sensor information from the pipeline
 * handler, computes the limits of the controls it handles and returns
 * them in the \a ipaControls output parameter.
 */
int IPAIPU3::init(const IPASettings &settings,
		  const IPACameraSensorInfo &sensorInfo,
		  const ControlInfoMap &sensorControls,
		  ControlInfoMap *ipaControls)
{
	camHelper_ = CameraSensorHelperFactoryBase::create(settings.sensorModel);
	if (camHelper_ == nullptr) {
		LOG(IPAIPU3, Error)
			<< "Failed to create camera sensor helper for "
			<< settings.sensorModel;
		return -ENODEV;
	}

	/* Clean context */
	context_.configuration = {};
	context_.configuration.sensor.lineDuration =
		sensorInfo.minLineLength * 1.0s / sensorInfo.pixelRate;

	/* Load the tuning data file. */
	File file(settings.configurationFile);
	if (!file.open(File::OpenModeFlag::ReadOnly)) {
		int ret = file.error();
		LOG(IPAIPU3, Error)
			<< "Failed to open configuration file "
			<< settings.configurationFile << ": " << strerror(-ret);
		return ret;
	}

	std::unique_ptr<libcamera::YamlObject> data = YamlParser::parse(file);
	if (!data)
		return -EINVAL;

	unsigned int version = (*data)["version"].get<uint32_t>(0);
	if (version != 1) {
		LOG(IPAIPU3, Error)
			<< "Invalid tuning file version " << version;
		return -EINVAL;
	}

	if (!data->contains("algorithms")) {
		LOG(IPAIPU3, Error)
			<< "Tuning file doesn't contain any algorithm";
		return -EINVAL;
	}

	int ret = createAlgorithms(context_, (*data)["algorithms"]);
	if (ret)
		return ret;

	/* Initialize controls. */
	updateControls(sensorInfo, sensorControls, ipaControls);

	return 0;
}

/**
 * \brief Perform any processing required before the first frame
 */
int IPAIPU3::start()
{
	/*
	 * Set the sensors V4L2 controls before the first frame to ensure that
	 * we have an expected and known configuration from the start.
	 */
	setControls(0);

	return 0;
}

/**
 * \brief Ensure that all processing has completed
 */
void IPAIPU3::stop()
{
	context_.frameContexts.clear();
}

/**
 * \brief Calculate a grid for the AWB statistics
 *
 * This function calculates a grid for the AWB algorithm in the IPU3 firmware.
 * Its input is the BDS output size calculated in the ImgU.
 * It is limited for now to the simplest method: find the lesser error
 * with the width/height and respective log2 width/height of the cells.
 *
 * \todo The frame is divided into cells which can be 8x8 => 64x64.
 * As a smaller cell improves the algorithm precision, adapting the
 * x_start and y_start parameters of the grid would provoke a loss of
 * some pixels but would also result in more accurate algorithms.
 */
void IPAIPU3::calculateBdsGrid(const Size &bdsOutputSize)
{
	Size best;
	Size bestLog2;

	/* Set the BDS output size in the IPAConfiguration structure */
	context_.configuration.grid.bdsOutputSize = bdsOutputSize;

	uint32_t minError = std::numeric_limits<uint32_t>::max();
	for (uint32_t shift = kMinCellSizeLog2; shift <= kMaxCellSizeLog2; ++shift) {
		uint32_t width = std::clamp(bdsOutputSize.width >> shift,
					    kMinGridWidth,
					    kMaxGridWidth);

		width = width << shift;
		uint32_t error = utils::abs_diff(width, bdsOutputSize.width);
		if (error >= minError)
			continue;

		minError = error;
		best.width = width;
		bestLog2.width = shift;
	}

	minError = std::numeric_limits<uint32_t>::max();
	for (uint32_t shift = kMinCellSizeLog2; shift <= kMaxCellSizeLog2; ++shift) {
		uint32_t height = std::clamp(bdsOutputSize.height >> shift,
					     kMinGridHeight,
					     kMaxGridHeight);

		height = height << shift;
		uint32_t error = utils::abs_diff(height, bdsOutputSize.height);
		if (error >= minError)
			continue;

		minError = error;
		best.height = height;
		bestLog2.height = shift;
	}

	struct ipu3_uapi_grid_config &bdsGrid = context_.configuration.grid.bdsGrid;
	bdsGrid.x_start = 0;
	bdsGrid.y_start = 0;
	bdsGrid.width = best.width >> bestLog2.width;
	bdsGrid.block_width_log2 = bestLog2.width;
	bdsGrid.height = best.height >> bestLog2.height;
	bdsGrid.block_height_log2 = bestLog2.height;

	/* The ImgU pads the lines to a multiple of 4 cells. */
	context_.configuration.grid.stride = utils::alignUp(bdsGrid.width, 4);

	LOG(IPAIPU3, Debug) << "Best grid found is: ("
			    << (int)bdsGrid.width << " << " << (int)bdsGrid.block_width_log2 << ") x ("
			    << (int)bdsGrid.height << " << " << (int)bdsGrid.block_height_log2 << ")";
}

/**
 * \brief Configure the IPU3 IPA
 * \param[in] configInfo The IPA configuration data, received from the pipeline
 * handler
 * \param[in] ipaControls The IPA controls to update
 *
 * Calculate the best grid for the statistics based on the pipeline handler BDS
 * output, and parse the minimum and maximum exposure and analogue gain control
 * values.
 *
 * \todo Document what the BDS is, ideally in a block diagram of the ImgU.
 *
 * All algorithm modules are called to allow them to prepare the
 * \a IPASessionConfiguration structure for the \a IPAContext.
 */
int IPAIPU3::configure(const IPAConfigInfo &configInfo,
		       ControlInfoMap *ipaControls)
{
	if (configInfo.sensorControls.empty()) {
		LOG(IPAIPU3, Error) << "No sensor controls provided";
		return -ENODATA;
	}

	sensorInfo_ = configInfo.sensorInfo;

	lensCtrls_ = configInfo.lensControls;

	/* Clear the IPA context for the new streaming session. */
	context_.activeState = {};
	context_.configuration = {};
	context_.frameContexts.clear();

	/* Initialise the sensor configuration. */
	context_.configuration.sensor.lineDuration =
		sensorInfo_.minLineLength * 1.0s / sensorInfo_.pixelRate;
	context_.configuration.sensor.size = sensorInfo_.outputSize;

	/*
	 * Compute the sensor V4L2 controls to be used by the algorithms and
	 * to be set on the sensor.
	 */
	sensorCtrls_ = configInfo.sensorControls;

	calculateBdsGrid(configInfo.bdsOutputSize);

	/* Update the camera controls using the new sensor settings. */
	updateControls(sensorInfo_, sensorCtrls_, ipaControls);

	/* Update the IPASessionConfiguration using the sensor settings. */
	updateSessionConfiguration(sensorCtrls_);

	for (auto const &algo : algorithms()) {
		int ret = algo->configure(context_, configInfo);
		if (ret)
			return ret;
	}

	return 0;
}

/**
 * \brief Map the parameters and stats buffers allocated in the pipeline handler
 * \param[in] buffers The buffers to map
 */
void IPAIPU3::mapBuffers(const std::vector<IPABuffer> &buffers)
{
	for (const IPABuffer &buffer : buffers) {
		const FrameBuffer fb(buffer.planes);
		buffers_.emplace(buffer.id,
				 MappedFrameBuffer(&fb, MappedFrameBuffer::MapFlag::ReadWrite));
	}
}

/**
 * \brief Unmap the parameters and stats buffers
 * \param[in] ids The IDs of the buffers to unmap
 */
void IPAIPU3::unmapBuffers(const std::vector<unsigned int> &ids)
{
	for (unsigned int id : ids) {
		auto it = buffers_.find(id);
		if (it == buffers_.end())
			continue;

		buffers_.erase(it);
	}
}

/**
 * \brief Fill and return a buffer with ISP processing parameters for a frame
 * \param[in] frame The frame number
 * \param[in] bufferId ID of the parameter buffer to fill
 *
 * Algorithms are expected to fill the IPU3 parameter buffer for the next
 * frame given their most recent processing of the ImgU statistics.
 */
void IPAIPU3::fillParamsBuffer(const uint32_t frame, const uint32_t bufferId)
{
	auto it = buffers_.find(bufferId);
	if (it == buffers_.end()) {
		LOG(IPAIPU3, Error) << "Could not find param buffer!";
		return;
	}

	Span<uint8_t> mem = it->second.planes()[0];
	ipu3_uapi_params *params =
		reinterpret_cast<ipu3_uapi_params *>(mem.data());

	/*
	 * The incoming params buffer may contain uninitialised data, or the
	 * parameters of previously queued frames. Clearing the entire buffer
	 * may be an expensive operation, and the kernel will only read from
	 * structures which have their associated use-flag set.
	 *
	 * It is the responsibility of the algorithms to set the use flags
	 * accordingly for any data structure they update during prepare().
	 */
	params->use = {};

	IPAFrameContext &frameContext = context_.frameContexts.get(frame);

	for (auto const &algo : algorithms())
		algo->prepare(context_, frame, frameContext, params);

	paramsBufferReady.emit(frame);
}

/**
 * \brief Process the statistics generated by the ImgU
 * \param[in] frame The frame number
 * \param[in] frameTimestamp Timestamp of the frame
 * \param[in] bufferId ID of the statistics buffer
 * \param[in] sensorControls Sensor controls
 *
 * Parse the most recently processed image statistics from the ImgU. The
 * statistics are passed to each algorithm module to run their calculations and
 * update their state accordingly.
 */
void IPAIPU3::processStatsBuffer(const uint32_t frame,
				 [[maybe_unused]] const int64_t frameTimestamp,
				 const uint32_t bufferId, const ControlList &sensorControls)
{
	auto it = buffers_.find(bufferId);
	if (it == buffers_.end()) {
		LOG(IPAIPU3, Error) << "Could not find stats buffer!";
		return;
	}

	Span<uint8_t> mem = it->second.planes()[0];
	const ipu3_uapi_stats_3a *stats =
		reinterpret_cast<ipu3_uapi_stats_3a *>(mem.data());

	IPAFrameContext &frameContext = context_.frameContexts.get(frame);

	frameContext.sensor.exposure = sensorControls.get(V4L2_CID_EXPOSURE).get<int32_t>();
	frameContext.sensor.gain = camHelper_->gain(sensorControls.get(V4L2_CID_ANALOGUE_GAIN).get<int32_t>());

	ControlList metadata(controls::controls);

	for (auto const &algo : algorithms())
		algo->process(context_, frame, frameContext, stats, metadata);

	setControls(frame);

	/*
	 * \todo The Metadata provides a path to getting extended data
	 * out to the application. Further data such as a simplifed Histogram
	 * might have value to be exposed, however such data may be
	 * difficult to report in a generically parsable way and we
	 * likely want to avoid putting platform specific metadata in.
	 */

	metadataReady.emit(frame, metadata);
}

/**
 * \brief Queue a request and process the control list from the application
 * \param[in] frame The number of the frame which will be processed next
 * \param[in] controls The controls for the \a frame
 *
 * Parse the request to handle any IPA-managed controls that were set from the
 * application such as manual sensor settings.
 */
void IPAIPU3::queueRequest(const uint32_t frame, const ControlList &controls)
{
	IPAFrameContext &frameContext = context_.frameContexts.alloc(frame);

	for (auto const &algo : algorithms())
		algo->queueRequest(context_, frame, frameContext, controls);
}

/**
 * \brief Handle sensor controls for a given \a frame number
 * \param[in] frame The frame on which the sensor controls should be set
 *
 * Send the desired sensor control values to the pipeline handler to request
 * that they are applied on the camera sensor.
 */
void IPAIPU3::setControls(unsigned int frame)