ipa: raspberrypi: agc: Move weights out of AGC
The region weights for the the AGC zones are handled by the AGC algorithm. Apply them directly in the IPA (vc4.cpp) to the statistics that we pass to the AGC. Signed-off-by: David Plowman <david.plowman@raspberrypi.com> Signed-off-by: Naushir Patuck <naush@raspberrypi.com> Reviewed-by: Jacopo Mondi <jacopo.mondi@ideasonboard.com> Signed-off-by: Laurent Pinchart <laurent.pinchart@ideasonboard.com>
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4 changed files with 41 additions and 16 deletions
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@ -6,6 +6,8 @@
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*/
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#pragma once
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#include <vector>
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#include <libcamera/base/utils.h>
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#include "algorithm.h"
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@ -18,6 +20,7 @@ public:
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AgcAlgorithm(Controller *controller) : Algorithm(controller) {}
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/* An AGC algorithm must provide the following: */
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virtual unsigned int getConvergenceFrames() const = 0;
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virtual std::vector<double> const &getWeights() const = 0;
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virtual void setEv(double ev) = 0;
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virtual void setFlickerPeriod(libcamera::utils::Duration flickerPeriod) = 0;
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virtual void setFixedShutter(libcamera::utils::Duration fixedShutter) = 0;
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@ -292,6 +292,18 @@ unsigned int Agc::getConvergenceFrames() const
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return config_.convergenceFrames;
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}
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std::vector<double> const &Agc::getWeights() const
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{
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/*
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* In case someone calls setMeteringMode and then this before the
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* algorithm has run and updated the meteringMode_ pointer.
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*/
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auto it = config_.meteringModes.find(meteringModeName_);
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if (it == config_.meteringModes.end())
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return meteringMode_->weights;
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return it->second.weights;
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}
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void Agc::setEv(double ev)
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{
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ev_ = ev;
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@ -595,19 +607,16 @@ static double computeInitialY(StatisticsPtr &stats, AwbStatus const &awb,
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ASSERT(weights.size() == stats->agcRegions.numRegions());
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/*
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* Note how the calculation below means that equal weights give you
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* "average" metering (i.e. all pixels equally important).
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* Note that the weights are applied by the IPA to the statistics directly,
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* before they are given to us here.
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*/
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double rSum = 0, gSum = 0, bSum = 0, pixelSum = 0;
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for (unsigned int i = 0; i < stats->agcRegions.numRegions(); i++) {
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auto ®ion = stats->agcRegions.get(i);
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double rAcc = std::min<double>(region.val.rSum * gain, (maxVal - 1) * region.counted);
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double gAcc = std::min<double>(region.val.gSum * gain, (maxVal - 1) * region.counted);
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double bAcc = std::min<double>(region.val.bSum * gain, (maxVal - 1) * region.counted);
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rSum += rAcc * weights[i];
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gSum += gAcc * weights[i];
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bSum += bAcc * weights[i];
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pixelSum += region.counted * weights[i];
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rSum += std::min<double>(region.val.rSum * gain, (maxVal - 1) * region.counted);
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gSum += std::min<double>(region.val.gSum * gain, (maxVal - 1) * region.counted);
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bSum += std::min<double>(region.val.bSum * gain, (maxVal - 1) * region.counted);
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pixelSum += region.counted;
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}
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if (pixelSum == 0.0) {
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LOG(RPiAgc, Warning) << "computeInitialY: pixelSum is zero";
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@ -69,6 +69,7 @@ public:
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char const *name() const override;
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int read(const libcamera::YamlObject ¶ms) override;
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unsigned int getConvergenceFrames() const override;
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std::vector<double> const &getWeights() const override;
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void setEv(double ev) override;
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void setFlickerPeriod(libcamera::utils::Duration flickerPeriod) override;
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void setMaxShutter(libcamera::utils::Duration maxShutter) override;
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@ -211,13 +211,25 @@ RPiController::StatisticsPtr IpaVc4::platformProcessStats(Span<uint8_t> mem)
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stats->awb_stats[i].counted,
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stats->awb_stats[i].notcounted });
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statistics->agcRegions.init(hw.agcRegions);
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for (i = 0; i < statistics->agcRegions.numRegions(); i++)
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statistics->agcRegions.set(i, { { stats->agc_stats[i].r_sum << scale,
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stats->agc_stats[i].g_sum << scale,
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stats->agc_stats[i].b_sum << scale },
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stats->agc_stats[i].counted,
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stats->awb_stats[i].notcounted });
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RPiController::AgcAlgorithm *agc = dynamic_cast<RPiController::AgcAlgorithm *>(
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controller_.getAlgorithm("agc"));
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if (!agc) {
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LOG(IPARPI, Debug) << "No AGC algorithm - not copying statistics";
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statistics->agcRegions.init(0);
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} else {
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statistics->agcRegions.init(hw.agcRegions);
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const std::vector<double> &weights = agc->getWeights();
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for (i = 0; i < statistics->agcRegions.numRegions(); i++) {
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uint64_t rSum = (stats->agc_stats[i].r_sum << scale) * weights[i];
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uint64_t gSum = (stats->agc_stats[i].g_sum << scale) * weights[i];
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uint64_t bSum = (stats->agc_stats[i].b_sum << scale) * weights[i];
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uint32_t counted = stats->agc_stats[i].counted * weights[i];
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uint32_t notcounted = stats->agc_stats[i].notcounted * weights[i];
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statistics->agcRegions.set(i, { { rSum, gSum, bSum },
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counted,
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notcounted });
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}
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}
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statistics->focusRegions.init(hw.focusRegions);
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for (i = 0; i < statistics->focusRegions.numRegions(); i++)
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