@@ -6,8 +6,6 @@
*/
#pragma once
-#include "pwl.h"
-
struct CacStatus {
std::vector<double> lutRx;
std::vector<double> lutRy;
@@ -6,7 +6,7 @@
*/
#pragma once
-#include "pwl.h"
+#include "libipa/pwl.h"
/*
* The "contrast" algorithm creates a gamma curve, optionally doing a little bit
@@ -14,7 +14,7 @@
*/
struct ContrastStatus {
- RPiController::Pwl gammaCurve;
+ libcamera::ipa::Pwl gammaCurve;
double brightness;
double contrast;
};
@@ -5,7 +5,6 @@ rpi_ipa_controller_sources = files([
'controller.cpp',
'device_status.cpp',
'histogram.cpp',
- 'pwl.cpp',
'rpi/af.cpp',
'rpi/agc.cpp',
'rpi/agc_channel.cpp',
@@ -32,4 +31,5 @@ rpi_ipa_controller_deps = [
]
rpi_ipa_controller_lib = static_library('rpi_ipa_controller', rpi_ipa_controller_sources,
+ include_directories : libipa_includes,
dependencies : rpi_ipa_controller_deps)
@@ -139,7 +139,7 @@ int Af::CfgParams::read(const libcamera::YamlObject ¶ms)
readNumber<uint32_t>(skipFrames, params, "skip_frames");
if (params.contains("map"))
- map.read(params["map"]);
+ map.readYaml(params["map"]);
else
LOG(RPiAf, Warning) << "No map defined";
@@ -721,7 +721,7 @@ bool Af::setLensPosition(double dioptres, int *hwpos)
if (mode_ == AfModeManual) {
LOG(RPiAf, Debug) << "setLensPosition: " << dioptres;
- ftarget_ = cfg_.map.domain().clip(dioptres);
+ ftarget_ = cfg_.map.domain().clamp(dioptres);
changed = !(initted_ && fsmooth_ == ftarget_);
updateLensPosition();
}
@@ -9,7 +9,8 @@
#include "../af_algorithm.h"
#include "../af_status.h"
#include "../pdaf_data.h"
-#include "../pwl.h"
+
+#include "libipa/pwl.h"
/*
* This algorithm implements a hybrid of CDAF and PDAF, favouring PDAF.
@@ -100,7 +101,7 @@ private:
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 */
+ libcamera::ipa::Pwl map; /* converts dioptres -> lens driver position */
CfgParams();
int read(const libcamera::YamlObject ¶ms);
@@ -130,7 +130,7 @@ int AgcConstraint::read(const libcamera::YamlObject ¶ms)
return -EINVAL;
qHi = *value;
- return yTarget.read(params["y_target"]);
+ return yTarget.readYaml(params["y_target"]);
}
static std::tuple<int, AgcConstraintMode>
@@ -237,7 +237,7 @@ int AgcConfig::read(const libcamera::YamlObject ¶ms)
return ret;
}
- ret = yTarget.read(params["y_target"]);
+ ret = yTarget.readYaml(params["y_target"]);
if (ret)
return ret;
@@ -715,7 +715,7 @@ 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 = c.yTarget.eval(c.yTarget.domain().clamp(lux));
targetY = std::min(EvGainYTargetLimit, targetY * evGain);
double iqm = h.interQuantileMean(c.qLo, c.qHi);
return (targetY * h.bins()) / iqm;
@@ -734,7 +734,7 @@ void AgcChannel::computeGain(StatisticsPtr &statistics, Metadata *imageMetadata,
* 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 = config_.yTarget.eval(config_.yTarget.domain().clamp(lux.lux));
targetY = std::min(EvGainYTargetLimit, targetY * evGain);
/*
@@ -12,10 +12,11 @@
#include <libcamera/base/utils.h>
+#include <libipa/pwl.h>
+
#include "../agc_status.h"
#include "../awb_status.h"
#include "../controller.h"
-#include "../pwl.h"
/* This is our implementation of AGC. */
@@ -40,7 +41,7 @@ struct AgcConstraint {
Bound bound;
double qLo;
double qHi;
- Pwl yTarget;
+ libcamera::ipa::Pwl yTarget;
int read(const libcamera::YamlObject ¶ms);
};
@@ -61,7 +62,7 @@ struct AgcConfig {
std::map<std::string, AgcExposureMode> exposureModes;
std::map<std::string, AgcConstraintMode> constraintModes;
std::vector<AgcChannelConstraint> channelConstraints;
- Pwl yTarget;
+ libcamera::ipa::Pwl yTarget;
double speed;
uint16_t startupFrames;
unsigned int convergenceFrames;
@@ -49,10 +49,10 @@ int AwbPrior::read(const libcamera::YamlObject ¶ms)
return -EINVAL;
lux = *value;
- return prior.read(params["prior"]);
+ return prior.readYaml(params["prior"]);
}
-static int readCtCurve(Pwl &ctR, Pwl &ctB, const libcamera::YamlObject ¶ms)
+static int readCtCurve(ipa::Pwl &ctR, ipa::Pwl &ctB, const libcamera::YamlObject ¶ms)
{
if (params.size() % 3) {
LOG(RPiAwb, Error) << "AwbConfig: incomplete CT curve entry";
@@ -207,7 +207,7 @@ void Awb::initialise()
* them.
*/
if (!config_.ctR.empty() && !config_.ctB.empty()) {
- syncResults_.temperatureK = config_.ctR.domain().clip(4000);
+ syncResults_.temperatureK = config_.ctR.domain().clamp(4000);
syncResults_.gainR = 1.0 / config_.ctR.eval(syncResults_.temperatureK);
syncResults_.gainG = 1.0;
syncResults_.gainB = 1.0 / config_.ctB.eval(syncResults_.temperatureK);
@@ -273,8 +273,8 @@ void Awb::setManualGains(double manualR, double manualB)
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_));
+ double ctR = config_.ctRInverse.eval(config_.ctRInverse.domain().clamp(1 / manualR_));
+ double ctB = config_.ctBInverse.eval(config_.ctBInverse.domain().clamp(1 / manualB_));
prevSyncResults_.temperatureK = (ctR + ctB) / 2;
syncResults_.temperatureK = prevSyncResults_.temperatureK;
}
@@ -468,7 +468,7 @@ double Awb::computeDelta2Sum(double gainR, double gainB)
return delta2Sum;
}
-Pwl Awb::interpolatePrior()
+ipa::Pwl Awb::interpolatePrior()
{
/*
* Interpolate the prior log likelihood function for our current lux
@@ -485,7 +485,7 @@ Pwl Awb::interpolatePrior()
idx++;
double lux0 = config_.priors[idx].lux,
lux1 = config_.priors[idx + 1].lux;
- return Pwl::combine(config_.priors[idx].prior,
+ return ipa::Pwl::combine(config_.priors[idx].prior,
config_.priors[idx + 1].prior,
[&](double /*x*/, double y0, double y1) {
return y0 + (y1 - y0) *
@@ -494,15 +494,15 @@ Pwl Awb::interpolatePrior()
}
}
-static double interpolateQuadatric(Pwl::Point const &a, Pwl::Point const &b,
- Pwl::Point const &c)
+static double interpolateQuadatric(PointF const &a, PointF const &b,
+ PointF 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;
+ PointF 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;
@@ -513,7 +513,7 @@ static double interpolateQuadatric(Pwl::Point const &a, Pwl::Point const &b,
return a.y < c.y - eps ? a.x : (c.y < a.y - eps ? c.x : b.x);
}
-double Awb::coarseSearch(Pwl const &prior)
+double Awb::coarseSearch(ipa::Pwl const &prior)
{
points_.clear(); /* assume doesn't deallocate memory */
size_t bestPoint = 0;
@@ -525,14 +525,14 @@ double Awb::coarseSearch(Pwl const &prior)
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 priorLogLikelihood = prior.eval(prior.domain().clamp(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));
+ points_.push_back(PointF(t, finalLogLikelihood));
if (points_.back().y < points_[bestPoint].y)
bestPoint = points_.size() - 1;
if (t == mode_->ctHi)
@@ -559,7 +559,7 @@ double Awb::coarseSearch(Pwl const &prior)
return t;
}
-void Awb::fineSearch(double &t, double &r, double &b, Pwl const &prior)
+void Awb::fineSearch(double &t, double &r, double &b, ipa::Pwl const &prior)
{
int spanR = -1, spanB = -1;
config_.ctR.eval(t, &spanR);
@@ -570,7 +570,7 @@ void Awb::fineSearch(double &t, double &r, double &b, Pwl const &prior)
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);
+ PointF transverse(bDiff, -rDiff);
if (transverse.len2() < 1e-6)
return;
/*
@@ -592,17 +592,17 @@ void Awb::fineSearch(double &t, double &r, double &b, Pwl const &prior)
for (int i = -nsteps; i <= nsteps; i++) {
double tTest = t + i * step;
double priorLogLikelihood =
- prior.eval(prior.domain().clip(tTest));
+ prior.eval(prior.domain().clamp(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];
+ PointF 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) +
+ PointF rbTest = PointF(rCurve, bCurve) +
transverse * points[j].x;
double rTest = rbTest.x, bTest = rbTest.y;
double gainR = 1 / rTest, gainB = 1 / bTest;
@@ -619,7 +619,7 @@ void Awb::fineSearch(double &t, double &r, double &b, Pwl const &prior)
* 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) +
+ PointF rbTest = PointF(rCurve, bCurve) +
transverse * interpolateQuadatric(points[bestPoint - 1],
points[bestPoint],
points[bestPoint + 1]);
@@ -653,7 +653,7 @@ void Awb::awbBayes()
* Get the current prior, and scale according to how many zones are
* valid... not entirely sure about this.
*/
- Pwl prior = interpolatePrior();
+ ipa::Pwl prior = interpolatePrior();
prior *= zones_.size() / (double)(statistics_->awbRegions.numRegions());
prior.map([](double x, double y) {
LOG(RPiAwb, Debug) << "(" << x << "," << y << ")";
@@ -10,11 +10,14 @@
#include <condition_variable>
#include <thread>
+#include <libcamera/geometry.h>
+
#include "../awb_algorithm.h"
-#include "../pwl.h"
#include "../awb_status.h"
#include "../statistics.h"
+#include "libipa/pwl.h"
+
namespace RPiController {
/* Control algorithm to perform AWB calculations. */
@@ -28,7 +31,7 @@ struct AwbMode {
struct AwbPrior {
int read(const libcamera::YamlObject ¶ms);
double lux; /* lux level */
- Pwl prior; /* maps CT to prior log likelihood for this lux level */
+ libcamera::ipa::Pwl prior; /* maps CT to prior log likelihood for this lux level */
};
struct AwbConfig {
@@ -41,10 +44,10 @@ struct AwbConfig {
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 */
+ libcamera::ipa::Pwl ctR; /* function maps CT to r (= R/G) */
+ libcamera::ipa::Pwl ctB; /* function maps CT to b (= B/G) */
+ libcamera::ipa::Pwl ctRInverse; /* inverse of ctR */
+ libcamera::ipa::Pwl ctBInverse; /* inverse of ctB */
/* table of illuminant priors at different lux levels */
std::vector<AwbPrior> priors;
/* AWB "modes" (determines the search range) */
@@ -161,11 +164,11 @@ private:
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);
+ libcamera::ipa::Pwl interpolatePrior();
+ double coarseSearch(libcamera::ipa::Pwl const &prior);
+ void fineSearch(double &t, double &r, double &b, libcamera::ipa::Pwl const &prior);
std::vector<RGB> zones_;
- std::vector<Pwl::Point> points_;
+ std::vector<libcamera::PointF> points_;
/* manual r setting */
double manualR_;
/* manual b setting */
@@ -71,7 +71,7 @@ int Ccm::read(const libcamera::YamlObject ¶ms)
int ret;
if (params.contains("saturation")) {
- ret = config_.saturation.read(params["saturation"]);
+ ret = config_.saturation.readYaml(params["saturation"]);
if (ret)
return ret;
}
@@ -172,7 +172,7 @@ void Ccm::prepare(Metadata *imageMetadata)
ccmStatus.saturation = saturation;
if (!config_.saturation.empty())
saturation *= config_.saturation.eval(
- config_.saturation.domain().clip(lux.lux));
+ config_.saturation.domain().clamp(lux.lux));
ccm = applySaturation(ccm, saturation);
for (int j = 0; j < 3; j++)
for (int i = 0; i < 3; i++)
@@ -8,8 +8,9 @@
#include <vector>
+#include <libipa/pwl.h>
+
#include "../ccm_algorithm.h"
-#include "../pwl.h"
namespace RPiController {
@@ -54,7 +55,7 @@ struct CtCcm {
struct CcmConfig {
std::vector<CtCcm> ccms;
- Pwl saturation;
+ libcamera::ipa::Pwl saturation;
};
class Ccm : public CcmAlgorithm
@@ -53,7 +53,7 @@ int Contrast::read(const libcamera::YamlObject ¶ms)
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"]);
+ return config_.gammaCurve.readYaml(params["gamma_curve"]);
}
void Contrast::setBrightness(double brightness)
@@ -92,10 +92,10 @@ void Contrast::prepare(Metadata *imageMetadata)
imageMetadata->set("contrast.status", status_);
}
-Pwl computeStretchCurve(Histogram const &histogram,
+ipa::Pwl computeStretchCurve(Histogram const &histogram,
ContrastConfig const &config)
{
- Pwl enhance;
+ ipa::Pwl enhance;
enhance.append(0, 0);
/*
* If the start of the histogram is rather empty, try to pull it down a
@@ -136,10 +136,10 @@ Pwl computeStretchCurve(Histogram const &histogram,
return enhance;
}
-Pwl applyManualContrast(Pwl const &gammaCurve, double brightness,
- double contrast)
+ipa::Pwl applyManualContrast(ipa::Pwl const &gammaCurve, double brightness,
+ double contrast)
{
- Pwl newGammaCurve;
+ ipa::Pwl newGammaCurve;
LOG(RPiContrast, Debug)
<< "Manual brightness " << brightness << " contrast " << contrast;
gammaCurve.map([&](double x, double y) {
@@ -160,7 +160,7 @@ void Contrast::process(StatisticsPtr &stats,
* 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;
+ ipa::Pwl gammaCurve = config_.gammaCurve;
if (ceEnable_) {
if (config_.loMax != 0 || config_.hiMax != 0)
gammaCurve = computeStretchCurve(histogram, config_).compose(gammaCurve);
@@ -8,8 +8,9 @@
#include <mutex>
+#include <libipa/pwl.h>
+
#include "../contrast_algorithm.h"
-#include "../pwl.h"
namespace RPiController {
@@ -26,7 +27,7 @@ struct ContrastConfig {
double hiHistogram;
double hiLevel;
double hiMax;
- Pwl gammaCurve;
+ libcamera::ipa::Pwl gammaCurve;
};
class Contrast : public ContrastAlgorithm
@@ -9,7 +9,6 @@
#include "../device_status.h"
#include "../lux_status.h"
-#include "../pwl.h"
#include "geq.h"
@@ -45,7 +44,7 @@ int Geq::read(const libcamera::YamlObject ¶ms)
}
if (params.contains("strength")) {
- int ret = config_.strength.read(params["strength"]);
+ int ret = config_.strength.readYaml(params["strength"]);
if (ret)
return ret;
}
@@ -67,7 +66,7 @@ void Geq::prepare(Metadata *imageMetadata)
GeqStatus geqStatus = {};
double strength = config_.strength.empty()
? 1.0
- : config_.strength.eval(config_.strength.domain().clip(luxStatus.lux));
+ : config_.strength.eval(config_.strength.domain().clamp(luxStatus.lux));
strength *= deviceStatus.analogueGain;
double offset = config_.offset * strength;
double slope = config_.slope * strength;
@@ -6,6 +6,8 @@
*/
#pragma once
+#include <libipa/pwl.h>
+
#include "../algorithm.h"
#include "../geq_status.h"
@@ -16,7 +18,7 @@ namespace RPiController {
struct GeqConfig {
uint16_t offset;
double slope;
- Pwl strength; /* lux to strength factor */
+ libcamera::ipa::Pwl strength; /* lux to strength factor */
};
class Geq : public Algorithm
@@ -42,7 +42,7 @@ void HdrConfig::read(const libcamera::YamlObject ¶ms, const std::string &mod
/* Lens shading related parameters. */
if (params.contains("spatial_gain_curve")) {
- spatialGainCurve.read(params["spatial_gain_curve"]);
+ spatialGainCurve.readYaml(params["spatial_gain_curve"]);
} else if (params.contains("spatial_gain")) {
double spatialGain = params["spatial_gain"].get<double>(2.0);
spatialGainCurve.append(0.0, spatialGain);
@@ -66,7 +66,7 @@ void HdrConfig::read(const libcamera::YamlObject ¶ms, const std::string &mod
iirStrength = params["iir_strength"].get<double>(8.0);
strength = params["strength"].get<double>(1.5);
if (tonemapEnable)
- tonemap.read(params["tonemap"]);
+ tonemap.readYaml(params["tonemap"]);
speed = params["speed"].get<double>(1.0);
if (params.contains("hi_quantile_targets")) {
hiQuantileTargets = params["hi_quantile_targets"].getList<double>().value();
@@ -212,7 +212,7 @@ bool Hdr::updateTonemap([[maybe_unused]] StatisticsPtr &stats, HdrConfig &config
/* When there's a change of HDR mode we start over with a new tonemap curve. */
if (delayedStatus_.mode != previousMode_) {
previousMode_ = delayedStatus_.mode;
- tonemap_ = Pwl();
+ tonemap_ = ipa::Pwl();
}
/* No tonemapping. No need to output a tonemap.status. */
@@ -275,7 +275,7 @@ bool Hdr::updateTonemap([[maybe_unused]] StatisticsPtr &stats, HdrConfig &config
double power = std::clamp(min_power, config.powerMin, config.powerMax);
/* Generate the tonemap, including the contrast adjustment factors. */
- Pwl tonemap;
+ libcamera::ipa::Pwl tonemap;
tonemap.append(0, 0);
for (unsigned int i = 0; i <= 6; i++) {
double x = 1 << (i + 9); /* x loops from 512 to 32768 inclusive */
@@ -12,9 +12,10 @@
#include <libcamera/geometry.h>
+#include <libipa/pwl.h>
+
#include "../hdr_algorithm.h"
#include "../hdr_status.h"
-#include "../pwl.h"
/* This is our implementation of an HDR algorithm. */
@@ -26,7 +27,7 @@ struct HdrConfig {
std::map<unsigned int, std::string> channelMap;
/* Lens shading related parameters. */
- Pwl spatialGainCurve; /* Brightness to gain curve for different image regions. */
+ libcamera::ipa::Pwl spatialGainCurve; /* Brightness to gain curve for different image regions. */
unsigned int diffusion; /* How much to diffuse the gain spatially. */
/* Tonemap related parameters. */
@@ -35,7 +36,7 @@ struct HdrConfig {
double detailSlope;
double iirStrength;
double strength;
- Pwl tonemap;
+ libcamera::ipa::Pwl tonemap;
/* These relate to adaptive tonemap calculation. */
double speed;
std::vector<double> hiQuantileTargets; /* quantiles to check for unsaturated images */
@@ -75,7 +76,7 @@ private:
HdrStatus status_; /* track the current HDR mode and channel */
HdrStatus delayedStatus_; /* track the delayed HDR mode and channel */
std::string previousMode_;
- Pwl tonemap_;
+ libcamera::ipa::Pwl tonemap_;
libcamera::Size regions_; /* stats regions */
unsigned int numRegions_; /* total number of stats regions */
std::vector<double> gains_[2];
@@ -33,7 +33,7 @@ int Tonemap::read(const libcamera::YamlObject ¶ms)
config_.detailSlope = params["detail_slope"].get<double>(0.1);
config_.iirStrength = params["iir_strength"].get<double>(1.0);
config_.strength = params["strength"].get<double>(1.0);
- config_.tonemap.read(params["tone_curve"]);
+ config_.tonemap.readYaml(params["tone_curve"]);
return 0;
}
@@ -6,8 +6,9 @@
*/
#pragma once
+#include <libipa/pwl.h>
+
#include "algorithm.h"
-#include "pwl.h"
namespace RPiController {
@@ -16,7 +17,7 @@ struct TonemapConfig {
double detailSlope;
double iirStrength;
double strength;
- Pwl tonemap;
+ libcamera::ipa::Pwl tonemap;
};
class Tonemap : public Algorithm
@@ -6,12 +6,12 @@
*/
#pragma once
-#include "pwl.h"
+#include <libipa/pwl.h>
struct TonemapStatus {
uint16_t detailConstant;
double detailSlope;
double iirStrength;
double strength;
- RPiController::Pwl tonemap;
+ libcamera::ipa::Pwl tonemap;
};