libcamera/vivid.git - libcamera pipeline handler for VIVID

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/* SPDX-License-Identifier: LGPL-2.1-or-later */ /* * Copyright (C) 2021, Ideas On Board * * ipu3_agc.cpp - AGC/AEC mean-based control algorithm */ #include "agc.h" #include <algorithm> #include <chrono> #include <cmath> #include <libcamera/base/log.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::ipu3::algorithms { /** * \class Agc * \brief A mean-based auto-exposure algorithm * * This algorithm calculates a shutter time and an analogue gain so that the * average value of the green channel of the brightest 2% of pixels approaches * 0.5. The AWB gains are not used here, and all cells in the grid have the same * weight, like an average-metering case. In this metering mode, the camera uses * light information from the entire scene and creates an average for the final * exposure setting, giving no weighting to any particular portion of the * metered area. * * Reference: Battiato, Messina & Castorina. (2008). Exposure * Correction for Imaging Devices: An Overview. 10.1201/9781420054538.ch12. */ LOG_DEFINE_CATEGORY(IPU3Agc) /* Limits for analogue gain values */ static constexpr double kMinAnalogueGain = 1.0; static constexpr double kMaxAnalogueGain = 8.0; /* \todo Honour the FrameDurationLimits control instead of hardcoding a limit */ static constexpr utils::Duration kMaxShutterSpeed = 60ms; /* Histogram constants */ static constexpr uint32_t knumHistogramBins = 256; /* Target value to reach for the top 2% of the histogram */ static constexpr double kEvGainTarget = 0.5; /* Number of frames to wait before calculating stats on minimum exposure */ static constexpr uint32_t kNumStartupFrames = 10; /* * Relative luminance target. * * It's a number that's chosen so that, when the camera points at a grey * target, the resulting image brightness is considered right. */ static constexpr double kRelativeLuminanceTarget = 0.16; Agc::Agc() : frameCount_(0), lineDuration_(0s), minShutterSpeed_(0s), maxShutterSpeed_(0s), filteredExposure_(0s), currentExposure_(0s) { } /** * \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 IPAConfigInfo &configInfo) { stride_ = context.configuration.grid.stride; /* \todo use the IPAContext to provide the limits */ lineDuration_ = configInfo.sensorInfo.lineLength * 1.0s / configInfo.sensorInfo.pixelRate; minShutterSpeed_ = context.configuration.agc.minShutterSpeed; maxShutterSpeed_ = std::min(context.configuration.agc.maxShutterSpeed, kMaxShutterSpeed); minAnalogueGain_ = std::max(context.configuration.agc.minAnalogueGain, kMinAnalogueGain); maxAnalogueGain_ = std::min(context.configuration.agc.maxAnalogueGain, kMaxAnalogueGain); /* Configure the default exposure and gain. */ context.frameContext.agc.gain = minAnalogueGain_; context.frameContext.agc.exposure = minShutterSpeed_ / lineDuration_; return 0; } /** * \brief Estimate the mean value of the top 2% of the histogram * \param[in] stats The statistics computed by the ImgU * \param[in] grid The grid used to store the statistics in the IPU3 * \return The mean value of the top 2% of the histogram */ double Agc::measureBrightness(const ipu3_uapi_stats_3a *stats, const ipu3_uapi_grid_config &grid) const { /* Initialise the histogram array */ uint32_t hist[knumHistogramBins] = { 0 }; for (unsigned int cellY = 0; cellY < grid.height; cellY++) { for (unsigned int cellX = 0; cellX < grid.width; cellX++) { uint32_t cellPosition = cellY * stride_ + cellX; const ipu3_uapi_awb_set_item *cell = reinterpret_cast<const ipu3_uapi_awb_set_item *>( &stats->awb_raw_buffer.meta_data[cellPosition] ); uint8_t gr = cell->Gr_avg; uint8_t gb = cell->Gb_avg; /* * Store the average green value to estimate the * brightness. Even the overexposed pixels are * taken into account. */ hist[(gr + gb) / 2]++; } } /* Estimate the quantile mean of the top 2% of the histogram. */ return Histogram(Span<uint32_t>(hist)).interQuantileMean(0.98, 1.0); } /** * \brief Apply a filter on the exposure value to limit the speed of changes */ void Agc::filterExposure() { double speed = 0.2; /* Adapt instantly if we are in startup phase */ if (frameCount_ < kNumStartupFrames) speed = 1.0; if (filteredExposure_ == 0s) { /* DG stands for digital gain.*/ filteredExposure_ = currentExposure_; } else { /* * If we are close to the desired result, go faster to avoid making * multiple micro-adjustments. * \todo Make this customisable? */ if (filteredExposure_ < 1.2 * currentExposure_ && filteredExposure_ > 0.8 * currentExposure_) speed = sqrt(speed); filteredExposure_ = speed * currentExposure_ + filteredExposure_ * (1.0 - speed); } LOG(IPU3Agc, Debug) << "After filtering, total_exposure " << filteredExposure_; } /** * \brief Estimate the new exposure and gain values * \param[inout] frameContext The shared IPA frame Context * \param[in] yGain The gain calculated based on the relative luminance target * \param[in] iqMeanGain The gain calculated based on the relative luminance target */ void Agc::computeExposure(IPAFrameContext &frameContext, double yGain, double iqMeanGain) { /* Get the effective exposure and gain applied on the sensor. */


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