libcamera/src/ipa/rkisp1/algorithms/agc.cpp
Daniel Scally fdcd5d04ec ipa: rkisp1: Remove bespoke Agc functions
Now that the rkisp1 Agc algorithm is a derivation of MeanLuminanceAgc
we can remove the bespoke functions from the IPA's class.

Reviewed-by: Stefan Klug <stefan.klug@ideasonboard.com>
Reviewed-by: Paul Elder <paul.elder@ideasonboard.com>
Reviewed-by: Jacopo Mondi <jacopo.mondi@ideasonboard.com>
Signed-off-by: Daniel Scally <dan.scally@ideasonboard.com>
Signed-off-by: Kieran Bingham <kieran.bingham@ideasonboard.com>
2024-05-08 12:54:57 +01:00

316 lines
10 KiB
C++

/* SPDX-License-Identifier: LGPL-2.1-or-later */
/*
* Copyright (C) 2021-2022, Ideas On Board
*
* agc.cpp - AGC/AEC mean-based control algorithm
*/
#include "agc.h"
#include <algorithm>
#include <chrono>
#include <cmath>
#include <libcamera/base/log.h>
#include <libcamera/base/utils.h>
#include <libcamera/control_ids.h>
#include <libcamera/ipa/core_ipa_interface.h>
#include "libipa/histogram.h"
/**
* \file agc.h
*/
namespace libcamera {
using namespace std::literals::chrono_literals;
namespace ipa::rkisp1::algorithms {
/**
* \class Agc
* \brief A mean-based auto-exposure algorithm
*/
LOG_DEFINE_CATEGORY(RkISP1Agc)
Agc::Agc()
{
supportsRaw_ = true;
}
/**
* \brief Initialise the AGC algorithm from tuning files
* \param[in] context The shared IPA context
* \param[in] tuningData The YamlObject containing Agc tuning data
*
* This function calls the base class' tuningData parsers to discover which
* control values are supported.
*
* \return 0 on success or errors from the base class
*/
int Agc::init(IPAContext &context, const YamlObject &tuningData)
{
int ret;
ret = parseTuningData(tuningData);
if (ret)
return ret;
context.ctrlMap.merge(controls());
return 0;
}
/**
* \brief Configure the AGC given a configInfo
* \param[in] context The shared IPA context
* \param[in] configInfo The IPA configuration data
*
* \return 0
*/
int Agc::configure(IPAContext &context, const IPACameraSensorInfo &configInfo)
{
/* Configure the default exposure and gain. */
context.activeState.agc.automatic.gain = context.configuration.sensor.minAnalogueGain;
context.activeState.agc.automatic.exposure =
10ms / context.configuration.sensor.lineDuration;
context.activeState.agc.manual.gain = context.activeState.agc.automatic.gain;
context.activeState.agc.manual.exposure = context.activeState.agc.automatic.exposure;
context.activeState.agc.autoEnabled = !context.configuration.raw;
context.activeState.agc.constraintMode = constraintModes().begin()->first;
context.activeState.agc.exposureMode = exposureModeHelpers().begin()->first;
/*
* Define the measurement window for AGC as a centered rectangle
* covering 3/4 of the image width and height.
*/
context.configuration.agc.measureWindow.h_offs = configInfo.outputSize.width / 8;
context.configuration.agc.measureWindow.v_offs = configInfo.outputSize.height / 8;
context.configuration.agc.measureWindow.h_size = 3 * configInfo.outputSize.width / 4;
context.configuration.agc.measureWindow.v_size = 3 * configInfo.outputSize.height / 4;
/* \todo Run this again when FrameDurationLimits is passed in */
setLimits(context.configuration.sensor.minShutterSpeed,
context.configuration.sensor.maxShutterSpeed,
context.configuration.sensor.minAnalogueGain,
context.configuration.sensor.maxAnalogueGain);
resetFrameCount();
return 0;
}
/**
* \copydoc libcamera::ipa::Algorithm::queueRequest
*/
void Agc::queueRequest(IPAContext &context,
[[maybe_unused]] const uint32_t frame,
IPAFrameContext &frameContext,
const ControlList &controls)
{
auto &agc = context.activeState.agc;
if (!context.configuration.raw) {
const auto &agcEnable = controls.get(controls::AeEnable);
if (agcEnable && *agcEnable != agc.autoEnabled) {
agc.autoEnabled = *agcEnable;
LOG(RkISP1Agc, Debug)
<< (agc.autoEnabled ? "Enabling" : "Disabling")
<< " AGC";
}
}
const auto &exposure = controls.get(controls::ExposureTime);
if (exposure && !agc.autoEnabled) {
agc.manual.exposure = *exposure * 1.0us
/ context.configuration.sensor.lineDuration;
LOG(RkISP1Agc, Debug)
<< "Set exposure to " << agc.manual.exposure;
}
const auto &gain = controls.get(controls::AnalogueGain);
if (gain && !agc.autoEnabled) {
agc.manual.gain = *gain;
LOG(RkISP1Agc, Debug) << "Set gain to " << agc.manual.gain;
}
frameContext.agc.autoEnabled = agc.autoEnabled;
if (!frameContext.agc.autoEnabled) {
frameContext.agc.exposure = agc.manual.exposure;
frameContext.agc.gain = agc.manual.gain;
}
}
/**
* \copydoc libcamera::ipa::Algorithm::prepare
*/
void Agc::prepare(IPAContext &context, const uint32_t frame,
IPAFrameContext &frameContext, rkisp1_params_cfg *params)
{
if (frameContext.agc.autoEnabled) {
frameContext.agc.exposure = context.activeState.agc.automatic.exposure;
frameContext.agc.gain = context.activeState.agc.automatic.gain;
}
if (frame > 0)
return;
/* Configure the measurement window. */
params->meas.aec_config.meas_window = context.configuration.agc.measureWindow;
/* Use a continuous method for measure. */
params->meas.aec_config.autostop = RKISP1_CIF_ISP_EXP_CTRL_AUTOSTOP_0;
/* Estimate Y as (R + G + B) x (85/256). */
params->meas.aec_config.mode = RKISP1_CIF_ISP_EXP_MEASURING_MODE_1;
params->module_cfg_update |= RKISP1_CIF_ISP_MODULE_AEC;
params->module_ens |= RKISP1_CIF_ISP_MODULE_AEC;
params->module_en_update |= RKISP1_CIF_ISP_MODULE_AEC;
/* Configure histogram. */
params->meas.hst_config.meas_window = context.configuration.agc.measureWindow;
/* Produce the luminance histogram. */
params->meas.hst_config.mode = RKISP1_CIF_ISP_HISTOGRAM_MODE_Y_HISTOGRAM;
/* Set an average weighted histogram. */
Span<uint8_t> weights{
params->meas.hst_config.hist_weight,
context.hw->numHistogramWeights
};
std::fill(weights.begin(), weights.end(), 1);
/* Step size can't be less than 3. */
params->meas.hst_config.histogram_predivider = 4;
/* Update the configuration for histogram. */
params->module_cfg_update |= RKISP1_CIF_ISP_MODULE_HST;
/* Enable the histogram measure unit. */
params->module_ens |= RKISP1_CIF_ISP_MODULE_HST;
params->module_en_update |= RKISP1_CIF_ISP_MODULE_HST;
}
void Agc::fillMetadata(IPAContext &context, IPAFrameContext &frameContext,
ControlList &metadata)
{
utils::Duration exposureTime = context.configuration.sensor.lineDuration
* frameContext.sensor.exposure;
metadata.set(controls::AnalogueGain, frameContext.sensor.gain);
metadata.set(controls::ExposureTime, exposureTime.get<std::micro>());
/* \todo Use VBlank value calculated from each frame exposure. */
uint32_t vTotal = context.configuration.sensor.size.height
+ context.configuration.sensor.defVBlank;
utils::Duration frameDuration = context.configuration.sensor.lineDuration
* vTotal;
metadata.set(controls::FrameDuration, frameDuration.get<std::micro>());
}
/**
* \brief Estimate the relative luminance of the frame with a given gain
* \param[in] gain The gain to apply to the frame
*
* This function estimates the average relative luminance of the frame that
* would be output by the sensor if an additional \a gain was applied.
*
* The estimation is based on the AE statistics for the current frame. Y
* averages for all cells are first multiplied by the gain, and then saturated
* to approximate the sensor behaviour at high brightness values. The
* approximation is quite rough, as it doesn't take into account non-linearities
* when approaching saturation. In this case, saturating after the conversion to
* YUV doesn't take into account the fact that the R, G and B components
* contribute differently to the relative luminance.
*
* The values are normalized to the [0.0, 1.0] range, where 1.0 corresponds to a
* theoretical perfect reflector of 100% reference white.
*
* More detailed information can be found in:
* https://en.wikipedia.org/wiki/Relative_luminance
*
* \return The relative luminance
*/
double Agc::estimateLuminance(double gain) const
{
double ySum = 0.0;
/* Sum the averages, saturated to 255. */
for (uint8_t expMean : expMeans_)
ySum += std::min(expMean * gain, 255.0);
/* \todo Weight with the AWB gains */
return ySum / expMeans_.size() / 255;
}
/**
* \brief Process RkISP1 statistics, and run AGC operations
* \param[in] context The shared IPA context
* \param[in] frame The frame context sequence number
* \param[in] frameContext The current frame context
* \param[in] stats The RKISP1 statistics and ISP results
* \param[out] metadata Metadata for the frame, to be filled by the algorithm
*
* Identify the current image brightness, and use that to estimate the optimal
* new exposure and gain for the scene.
*/
void Agc::process(IPAContext &context, [[maybe_unused]] const uint32_t frame,
IPAFrameContext &frameContext, const rkisp1_stat_buffer *stats,
ControlList &metadata)
{
if (!stats) {
fillMetadata(context, frameContext, metadata);
return;
}
/*
* \todo Verify that the exposure and gain applied by the sensor for
* this frame match what has been requested. This isn't a hard
* requirement for stability of the AGC (the guarantee we need in
* automatic mode is a perfect match between the frame and the values
* we receive), but is important in manual mode.
*/
const rkisp1_cif_isp_stat *params = &stats->params;
ASSERT(stats->meas_type & RKISP1_CIF_ISP_STAT_AUTOEXP);
Histogram hist({ params->hist.hist_bins, context.hw->numHistogramBins });
expMeans_ = { params->ae.exp_mean, context.hw->numAeCells };
/*
* The Agc algorithm needs to know the effective exposure value that was
* applied to the sensor when the statistics were collected.
*/
utils::Duration exposureTime = context.configuration.sensor.lineDuration
* frameContext.sensor.exposure;
double analogueGain = frameContext.sensor.gain;
utils::Duration effectiveExposureValue = exposureTime * analogueGain;
utils::Duration shutterTime;
double aGain, dGain;
std::tie(shutterTime, aGain, dGain) =
calculateNewEv(context.activeState.agc.constraintMode,
context.activeState.agc.exposureMode,
hist, effectiveExposureValue);
LOG(RkISP1Agc, Debug)
<< "Divided up shutter, analogue gain and digital gain are "
<< shutterTime << ", " << aGain << " and " << dGain;
IPAActiveState &activeState = context.activeState;
/* Update the estimated exposure and gain. */
activeState.agc.automatic.exposure = shutterTime / context.configuration.sensor.lineDuration;
activeState.agc.automatic.gain = aGain;
fillMetadata(context, frameContext, metadata);
expMeans_ = {};
}
REGISTER_IPA_ALGORITHM(Agc, "Agc")
} /* namespace ipa::rkisp1::algorithms */
} /* namespace libcamera */