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-rw-r--r--src/ipa/raspberrypi/controller/rpi/alsc.cpp341
-rw-r--r--src/ipa/raspberrypi/controller/rpi/alsc.h29
2 files changed, 212 insertions, 158 deletions
diff --git a/src/ipa/raspberrypi/controller/rpi/alsc.cpp b/src/ipa/raspberrypi/controller/rpi/alsc.cpp
index eb4e2f94..51fe5d73 100644
--- a/src/ipa/raspberrypi/controller/rpi/alsc.cpp
+++ b/src/ipa/raspberrypi/controller/rpi/alsc.cpp
@@ -5,6 +5,7 @@
* alsc.cpp - ALSC (auto lens shading correction) control algorithm
*/
+#include <algorithm>
#include <functional>
#include <math.h>
#include <numeric>
@@ -24,9 +25,6 @@ LOG_DEFINE_CATEGORY(RPiAlsc)
#define NAME "rpi.alsc"
-static const int X = AlscCellsX;
-static const int Y = AlscCellsY;
-static const int XY = X * Y;
static const double InsufficientData = -1.0;
Alsc::Alsc(Controller *controller)
@@ -51,8 +49,11 @@ char const *Alsc::name() const
return NAME;
}
-static int generateLut(double *lut, const libcamera::YamlObject &params)
+static int generateLut(std::vector<double> &lut, const libcamera::YamlObject &params,
+ const Size &size)
{
+ /* These must be signed ints for the co-ordinate calculations below. */
+ int X = size.width, Y = size.height;
double cstrength = params["corner_strength"].get<double>(2.0);
if (cstrength <= 1.0) {
LOG(RPiAlsc, Error) << "corner_strength must be > 1.0";
@@ -81,9 +82,9 @@ static int generateLut(double *lut, const libcamera::YamlObject &params)
return 0;
}
-static int readLut(double *lut, const libcamera::YamlObject &params)
+static int readLut(std::vector<double> &lut, const libcamera::YamlObject &params, const Size &size)
{
- if (params.size() != XY) {
+ if (params.size() != size.width * size.height) {
LOG(RPiAlsc, Error) << "Invalid number of entries in LSC table";
return -EINVAL;
}
@@ -101,7 +102,7 @@ static int readLut(double *lut, const libcamera::YamlObject &params)
static int readCalibrations(std::vector<AlscCalibration> &calibrations,
const libcamera::YamlObject &params,
- std::string const &name)
+ std::string const &name, const Size &size)
{
if (params.contains(name)) {
double lastCt = 0;
@@ -119,7 +120,7 @@ static int readCalibrations(std::vector<AlscCalibration> &calibrations,
calibration.ct = lastCt = ct;
const libcamera::YamlObject &table = p["table"];
- if (table.size() != XY) {
+ if (table.size() != size.width * size.height) {
LOG(RPiAlsc, Error)
<< "Incorrect number of values for ct "
<< ct << " in " << name;
@@ -127,6 +128,7 @@ static int readCalibrations(std::vector<AlscCalibration> &calibrations,
}
int num = 0;
+ calibration.table.resize(size.width * size.height);
for (const auto &elem : table.asList()) {
value = elem.get<double>();
if (!value)
@@ -134,7 +136,7 @@ static int readCalibrations(std::vector<AlscCalibration> &calibrations,
calibration.table[num++] = *value;
}
- calibrations.push_back(calibration);
+ calibrations.push_back(std::move(calibration));
LOG(RPiAlsc, Debug)
<< "Read " << name << " calibration for ct " << ct;
}
@@ -144,6 +146,7 @@ static int readCalibrations(std::vector<AlscCalibration> &calibrations,
int Alsc::read(const libcamera::YamlObject &params)
{
+ config_.tableSize = getHardwareConfig().awbRegions;
config_.framePeriod = params["frame_period"].get<uint16_t>(12);
config_.startupFrames = params["startup_frames"].get<uint16_t>(10);
config_.speed = params["speed"].get<double>(0.05);
@@ -153,28 +156,29 @@ int Alsc::read(const libcamera::YamlObject &params)
config_.minCount = params["min_count"].get<double>(10.0);
config_.minG = params["min_G"].get<uint16_t>(50);
config_.omega = params["omega"].get<double>(1.3);
- config_.nIter = params["n_iter"].get<uint32_t>(X + Y);
+ config_.nIter = params["n_iter"].get<uint32_t>(config_.tableSize.width + config_.tableSize.height);
config_.luminanceStrength =
params["luminance_strength"].get<double>(1.0);
- for (int i = 0; i < XY; i++)
- config_.luminanceLut[i] = 1.0;
+ config_.luminanceLut.resize(config_.tableSize.width * config_.tableSize.height, 1.0);
int ret = 0;
if (params.contains("corner_strength"))
- ret = generateLut(config_.luminanceLut, params);
+ ret = generateLut(config_.luminanceLut, params, config_.tableSize);
else if (params.contains("luminance_lut"))
- ret = readLut(config_.luminanceLut, params["luminance_lut"]);
+ ret = readLut(config_.luminanceLut, params["luminance_lut"], config_.tableSize);
else
LOG(RPiAlsc, Warning)
<< "no luminance table - assume unity everywhere";
if (ret)
return ret;
- ret = readCalibrations(config_.calibrationsCr, params, "calibrations_Cr");
+ ret = readCalibrations(config_.calibrationsCr, params, "calibrations_Cr",
+ config_.tableSize);
if (ret)
return ret;
- ret = readCalibrations(config_.calibrationsCb, params, "calibrations_Cb");
+ ret = readCalibrations(config_.calibrationsCb, params, "calibrations_Cb",
+ config_.tableSize);
if (ret)
return ret;
@@ -187,13 +191,16 @@ int Alsc::read(const libcamera::YamlObject &params)
static double getCt(Metadata *metadata, double defaultCt);
static void getCalTable(double ct, std::vector<AlscCalibration> const &calibrations,
- double calTable[XY]);
-static void resampleCalTable(double const calTableIn[XY], CameraMode const &cameraMode,
- double calTableOut[XY]);
-static void compensateLambdasForCal(double const calTable[XY], double const oldLambdas[XY],
- double newLambdas[XY]);
-static void addLuminanceToTables(double results[3][Y][X], double const lambdaR[XY], double lambdaG,
- double const lambdaB[XY], double const luminanceLut[XY],
+ std::vector<double> &calTable);
+static void resampleCalTable(const std::vector<double> &calTableIn, CameraMode const &cameraMode,
+ const Size &size, std::vector<double> &calTableOut);
+static void compensateLambdasForCal(const std::vector<double> &calTable,
+ const std::vector<double> &oldLambdas,
+ std::vector<double> &newLambdas);
+static void addLuminanceToTables(std::array<std::vector<double>, 3> &results,
+ const std::vector<double> &lambdaR, double lambdaG,
+ const std::vector<double> &lambdaB,
+ const std::vector<double> &luminanceLut,
double luminanceStrength);
void Alsc::initialise()
@@ -201,7 +208,28 @@ void Alsc::initialise()
frameCount2_ = frameCount_ = framePhase_ = 0;
firstTime_ = true;
ct_ = config_.defaultCt;
+
+ const size_t XY = config_.tableSize.width * config_.tableSize.height;
+
+ for (auto &r : syncResults_)
+ r.resize(XY);
+ for (auto &r : prevSyncResults_)
+ r.resize(XY);
+ for (auto &r : asyncResults_)
+ r.resize(XY);
+
+ luminanceTable_.resize(XY);
+ asyncLambdaR_.resize(XY);
+ asyncLambdaB_.resize(XY);
/* The lambdas are initialised in the SwitchMode. */
+ lambdaR_.resize(XY);
+ lambdaB_.resize(XY);
+
+ /* Temporaries for the computations, but sensible to allocate this up-front! */
+ for (auto &c : tmpC_)
+ c.resize(XY);
+ for (auto &m : tmpM_)
+ m.resize(XY);
}
void Alsc::waitForAysncThread()
@@ -262,7 +290,7 @@ void Alsc::switchMode(CameraMode const &cameraMode,
* We must resample the luminance table like we do the others, but it's
* fixed so we can simply do it up front here.
*/
- resampleCalTable(config_.luminanceLut, cameraMode_, luminanceTable_);
+ resampleCalTable(config_.luminanceLut, cameraMode_, config_.tableSize, luminanceTable_);
if (resetTables) {
/*
@@ -272,18 +300,18 @@ void Alsc::switchMode(CameraMode const &cameraMode,
* the lambdas, but the rest of this code then echoes the code in
* doAlsc, without the adaptive algorithm.
*/
- for (int i = 0; i < XY; i++)
- lambdaR_[i] = lambdaB_[i] = 1.0;
- double calTableR[XY], calTableB[XY], calTableTmp[XY];
+ std::fill(lambdaR_.begin(), lambdaR_.end(), 1.0);
+ std::fill(lambdaB_.begin(), lambdaB_.end(), 1.0);
+ std::vector<double> &calTableR = tmpC_[0], &calTableB = tmpC_[1], &calTableTmp = tmpC_[2];
getCalTable(ct_, config_.calibrationsCr, calTableTmp);
- resampleCalTable(calTableTmp, cameraMode_, calTableR);
+ resampleCalTable(calTableTmp, cameraMode_, config_.tableSize, calTableR);
getCalTable(ct_, config_.calibrationsCb, calTableTmp);
- resampleCalTable(calTableTmp, cameraMode_, calTableB);
+ resampleCalTable(calTableTmp, cameraMode_, config_.tableSize, calTableB);
compensateLambdasForCal(calTableR, lambdaR_, asyncLambdaR_);
compensateLambdasForCal(calTableB, lambdaB_, asyncLambdaB_);
addLuminanceToTables(syncResults_, asyncLambdaR_, 1.0, asyncLambdaB_,
luminanceTable_, config_.luminanceStrength);
- memcpy(prevSyncResults_, syncResults_, sizeof(prevSyncResults_));
+ prevSyncResults_ = syncResults_;
framePhase_ = config_.framePeriod; /* run the algo again asap */
firstTime_ = false;
}
@@ -294,7 +322,7 @@ void Alsc::fetchAsyncResults()
LOG(RPiAlsc, Debug) << "Fetch ALSC results";
asyncFinished_ = false;
asyncStarted_ = false;
- memcpy(syncResults_, asyncResults_, sizeof(syncResults_));
+ syncResults_ = asyncResults_;
}
double getCt(Metadata *metadata, double defaultCt)
@@ -316,9 +344,9 @@ static void copyStats(RgbyRegions &regions, StatisticsPtr &stats,
if (!regions.numRegions())
regions.init(stats->awbRegions.size());
- double *rTable = (double *)status.r;
- double *gTable = (double *)status.g;
- double *bTable = (double *)status.b;
+ const std::vector<double> &rTable = status.r;
+ const std::vector<double> &gTable = status.g;
+ const std::vector<double> &bTable = status.b;
for (unsigned int i = 0; i < stats->awbRegions.numRegions(); i++) {
auto r = stats->awbRegions.get(i);
r.val.rSum = static_cast<uint64_t>(r.val.rSum / rTable[i]);
@@ -344,12 +372,9 @@ void Alsc::restartAsync(StatisticsPtr &stats, Metadata *imageMetadata)
if (imageMetadata->get("alsc.status", alscStatus) != 0) {
LOG(RPiAlsc, Warning)
<< "No ALSC status found for applied gains!";
- for (int y = 0; y < Y; y++)
- for (int x = 0; x < X; x++) {
- alscStatus.r[y][x] = 1.0;
- alscStatus.g[y][x] = 1.0;
- alscStatus.b[y][x] = 1.0;
- }
+ alscStatus.r.resize(config_.tableSize.width * config_.tableSize.height, 1.0);
+ alscStatus.g.resize(config_.tableSize.width * config_.tableSize.height, 1.0);
+ alscStatus.b.resize(config_.tableSize.width * config_.tableSize.height, 1.0);
}
copyStats(statistics_, stats, alscStatus);
framePhase_ = 0;
@@ -380,15 +405,15 @@ void Alsc::prepare(Metadata *imageMetadata)
fetchAsyncResults();
}
/* Apply IIR filter to results and program into the pipeline. */
- double *ptr = (double *)syncResults_,
- *pptr = (double *)prevSyncResults_;
- for (unsigned int i = 0; i < sizeof(syncResults_) / sizeof(double); i++)
- pptr[i] = speed * ptr[i] + (1.0 - speed) * pptr[i];
+ for (unsigned int j = 0; j < syncResults_.size(); j++) {
+ for (unsigned int i = 0; i < syncResults_[j].size(); i++)
+ prevSyncResults_[j][i] = speed * syncResults_[j][i] + (1.0 - speed) * prevSyncResults_[j][i];
+ }
/* Put output values into status metadata. */
AlscStatus status;
- memcpy(status.r, prevSyncResults_[0], sizeof(status.r));
- memcpy(status.g, prevSyncResults_[1], sizeof(status.g));
- memcpy(status.b, prevSyncResults_[2], sizeof(status.b));
+ status.r = prevSyncResults_[0];
+ status.g = prevSyncResults_[1];
+ status.b = prevSyncResults_[2];
imageMetadata->set("alsc.status", status);
}
@@ -432,18 +457,17 @@ void Alsc::asyncFunc()
}
void getCalTable(double ct, std::vector<AlscCalibration> const &calibrations,
- double calTable[XY])
+ std::vector<double> &calTable)
{
if (calibrations.empty()) {
- for (int i = 0; i < XY; i++)
- calTable[i] = 1.0;
+ std::fill(calTable.begin(), calTable.end(), 1.0);
LOG(RPiAlsc, Debug) << "no calibrations found";
} else if (ct <= calibrations.front().ct) {
- memcpy(calTable, calibrations.front().table, XY * sizeof(double));
+ calTable = calibrations.front().table;
LOG(RPiAlsc, Debug) << "using calibration for "
<< calibrations.front().ct;
} else if (ct >= calibrations.back().ct) {
- memcpy(calTable, calibrations.back().table, XY * sizeof(double));
+ calTable = calibrations.back().table;
LOG(RPiAlsc, Debug) << "using calibration for "
<< calibrations.back().ct;
} else {
@@ -454,7 +478,7 @@ void getCalTable(double ct, std::vector<AlscCalibration> const &calibrations,
LOG(RPiAlsc, Debug)
<< "ct is " << ct << ", interpolating between "
<< ct0 << " and " << ct1;
- for (int i = 0; i < XY; i++)
+ for (unsigned int i = 0; i < calTable.size(); i++)
calTable[i] =
(calibrations[idx].table[i] * (ct1 - ct) +
calibrations[idx + 1].table[i] * (ct - ct0)) /
@@ -462,9 +486,13 @@ void getCalTable(double ct, std::vector<AlscCalibration> const &calibrations,
}
}
-void resampleCalTable(double const calTableIn[XY],
- CameraMode const &cameraMode, double calTableOut[XY])
+void resampleCalTable(const std::vector<double> &calTableIn,
+ CameraMode const &cameraMode, const Size &size,
+ std::vector<double> &calTableOut)
{
+ int X = size.width;
+ int Y = size.height;
+
/*
* Precalculate and cache the x sampling locations and phases to save
* recomputing them on every row.
@@ -501,23 +529,24 @@ void resampleCalTable(double const calTableIn[XY],
yLo = Y - 1 - yLo;
yHi = Y - 1 - yHi;
}
- double const *rowAbove = calTableIn + X * yLo;
- double const *rowBelow = calTableIn + X * yHi;
+ double const *rowAbove = calTableIn.data() + X * yLo;
+ double const *rowBelow = calTableIn.data() + X * yHi;
+ double *out = calTableOut.data() + X * j;
for (int i = 0; i < X; i++) {
double above = rowAbove[xLo[i]] * (1 - xf[i]) +
rowAbove[xHi[i]] * xf[i];
double below = rowBelow[xLo[i]] * (1 - xf[i]) +
rowBelow[xHi[i]] * xf[i];
- *(calTableOut++) = above * (1 - yf) + below * yf;
+ *(out++) = above * (1 - yf) + below * yf;
}
}
}
/* Calculate chrominance statistics (R/G and B/G) for each region. */
-static void calculateCrCb(const RgbyRegions &awbRegion, double cr[XY],
- double cb[XY], uint32_t minCount, uint16_t minG)
+static void calculateCrCb(const RgbyRegions &awbRegion, std::vector<double> &cr,
+ std::vector<double> &cb, uint32_t minCount, uint16_t minG)
{
- for (int i = 0; i < XY; i++) {
+ for (unsigned int i = 0; i < cr.size(); i++) {
auto s = awbRegion.get(i);
if (s.counted <= minCount || s.val.gSum / s.counted <= minG) {
@@ -530,33 +559,34 @@ static void calculateCrCb(const RgbyRegions &awbRegion, double cr[XY],
}
}
-static void applyCalTable(double const calTable[XY], double C[XY])
+static void applyCalTable(const std::vector<double> &calTable, std::vector<double> &C)
{
- for (int i = 0; i < XY; i++)
+ for (unsigned int i = 0; i < C.size(); i++)
if (C[i] != InsufficientData)
C[i] *= calTable[i];
}
-void compensateLambdasForCal(double const calTable[XY],
- double const oldLambdas[XY],
- double newLambdas[XY])
+void compensateLambdasForCal(const std::vector<double> &calTable,
+ const std::vector<double> &oldLambdas,
+ std::vector<double> &newLambdas)
{
double minNewLambda = std::numeric_limits<double>::max();
- for (int i = 0; i < XY; i++) {
+ for (unsigned int i = 0; i < newLambdas.size(); i++) {
newLambdas[i] = oldLambdas[i] * calTable[i];
minNewLambda = std::min(minNewLambda, newLambdas[i]);
}
- for (int i = 0; i < XY; i++)
+ for (unsigned int i = 0; i < newLambdas.size(); i++)
newLambdas[i] /= minNewLambda;
}
-[[maybe_unused]] static void printCalTable(double const C[XY])
+[[maybe_unused]] static void printCalTable(const std::vector<double> &C,
+ const Size &size)
{
printf("table: [\n");
- for (int j = 0; j < Y; j++) {
- for (int i = 0; i < X; i++) {
- printf("%5.3f", 1.0 / C[j * X + i]);
- if (i != X - 1 || j != Y - 1)
+ for (unsigned int j = 0; j < size.height; j++) {
+ for (unsigned int i = 0; i < size.width; i++) {
+ printf("%5.3f", 1.0 / C[j * size.width + i]);
+ if (i != size.width - 1 || j != size.height - 1)
printf(",");
}
printf("\n");
@@ -577,9 +607,13 @@ static double computeWeight(double Ci, double Cj, double sigma)
}
/* Compute all weights. */
-static void computeW(double const C[XY], double sigma, double W[XY][4])
+static void computeW(const std::vector<double> &C, double sigma,
+ std::vector<std::array<double, 4>> &W, const Size &size)
{
- for (int i = 0; i < XY; i++) {
+ size_t XY = size.width * size.height;
+ size_t X = size.width;
+
+ for (unsigned int i = 0; i < XY; i++) {
/* Start with neighbour above and go clockwise. */
W[i][0] = i >= X ? computeWeight(C[i], C[i - X], sigma) : 0;
W[i][1] = i % X < X - 1 ? computeWeight(C[i], C[i + 1], sigma) : 0;
@@ -589,11 +623,16 @@ static void computeW(double const C[XY], double sigma, double W[XY][4])
}
/* Compute M, the large but sparse matrix such that M * lambdas = 0. */
-static void constructM(double const C[XY], double const W[XY][4],
- double M[XY][4])
+static void constructM(const std::vector<double> &C,
+ const std::vector<std::array<double, 4>> &W,
+ std::vector<std::array<double, 4>> &M,
+ const Size &size)
{
+ size_t XY = size.width * size.height;
+ size_t X = size.width;
+
double epsilon = 0.001;
- for (int i = 0; i < XY; i++) {
+ for (unsigned int i = 0; i < XY; i++) {
/*
* Note how, if C[i] == INSUFFICIENT_DATA, the weights will all
* be zero so the equation is still set up correctly.
@@ -614,79 +653,80 @@ static void constructM(double const C[XY], double const W[XY][4],
* left/right neighbours are zero down the left/right edges, so we don't need
* need to test the i value to exclude them.
*/
-static double computeLambdaBottom(int i, double const M[XY][4],
- double lambda[XY])
+static double computeLambdaBottom(int i, const std::vector<std::array<double, 4>> &M,
+ std::vector<double> &lambda, const Size &size)
{
- return M[i][1] * lambda[i + 1] + M[i][2] * lambda[i + X] +
+ return M[i][1] * lambda[i + 1] + M[i][2] * lambda[i + size.width] +
M[i][3] * lambda[i - 1];
}
-static double computeLambdaBottomStart(int i, double const M[XY][4],
- double lambda[XY])
+static double computeLambdaBottomStart(int i, const std::vector<std::array<double, 4>> &M,
+ std::vector<double> &lambda, const Size &size)
{
- return M[i][1] * lambda[i + 1] + M[i][2] * lambda[i + X];
+ return M[i][1] * lambda[i + 1] + M[i][2] * lambda[i + size.width];
}
-static double computeLambdaInterior(int i, double const M[XY][4],
- double lambda[XY])
+static double computeLambdaInterior(int i, const std::vector<std::array<double, 4>> &M,
+ std::vector<double> &lambda, const Size &size)
{
- return M[i][0] * lambda[i - X] + M[i][1] * lambda[i + 1] +
- M[i][2] * lambda[i + X] + M[i][3] * lambda[i - 1];
+ return M[i][0] * lambda[i - size.width] + M[i][1] * lambda[i + 1] +
+ M[i][2] * lambda[i + size.width] + M[i][3] * lambda[i - 1];
}
-static double computeLambdaTop(int i, double const M[XY][4],
- double lambda[XY])
+static double computeLambdaTop(int i, const std::vector<std::array<double, 4>> &M,
+ std::vector<double> &lambda, const Size &size)
{
- return M[i][0] * lambda[i - X] + M[i][1] * lambda[i + 1] +
+ return M[i][0] * lambda[i - size.width] + M[i][1] * lambda[i + 1] +
M[i][3] * lambda[i - 1];
}
-static double computeLambdaTopEnd(int i, double const M[XY][4],
- double lambda[XY])
+static double computeLambdaTopEnd(int i, const std::vector<std::array<double, 4>> &M,
+ std::vector<double> &lambda, const Size &size)
{
- return M[i][0] * lambda[i - X] + M[i][3] * lambda[i - 1];
+ return M[i][0] * lambda[i - size.width] + M[i][3] * lambda[i - 1];
}
/* Gauss-Seidel iteration with over-relaxation. */
-static double gaussSeidel2Sor(double const M[XY][4], double omega,
- double lambda[XY], double lambdaBound)
+static double gaussSeidel2Sor(const std::vector<std::array<double, 4>> &M, double omega,
+ std::vector<double> &lambda, double lambdaBound,
+ const Size &size)
{
+ int XY = size.width * size.height;
+ int X = size.width;
const double min = 1 - lambdaBound, max = 1 + lambdaBound;
- double oldLambda[XY];
+ std::vector<double> oldLambda = lambda;
int i;
- for (i = 0; i < XY; i++)
- oldLambda[i] = lambda[i];
- lambda[0] = computeLambdaBottomStart(0, M, lambda);
+ lambda[0] = computeLambdaBottomStart(0, M, lambda, size);
lambda[0] = std::clamp(lambda[0], min, max);
for (i = 1; i < X; i++) {
- lambda[i] = computeLambdaBottom(i, M, lambda);
+ lambda[i] = computeLambdaBottom(i, M, lambda, size);
lambda[i] = std::clamp(lambda[i], min, max);
}
for (; i < XY - X; i++) {
- lambda[i] = computeLambdaInterior(i, M, lambda);
+ lambda[i] = computeLambdaInterior(i, M, lambda, size);
lambda[i] = std::clamp(lambda[i], min, max);
}
for (; i < XY - 1; i++) {
- lambda[i] = computeLambdaTop(i, M, lambda);
+ lambda[i] = computeLambdaTop(i, M, lambda, size);
lambda[i] = std::clamp(lambda[i], min, max);
}
- lambda[i] = computeLambdaTopEnd(i, M, lambda);
+ lambda[i] = computeLambdaTopEnd(i, M, lambda, size);
lambda[i] = std::clamp(lambda[i], min, max);
/*
* Also solve the system from bottom to top, to help spread the updates
* better.
*/
- lambda[i] = computeLambdaTopEnd(i, M, lambda);
+ lambda[i] = computeLambdaTopEnd(i, M, lambda, size);
lambda[i] = std::clamp(lambda[i], min, max);
for (i = XY - 2; i >= XY - X; i--) {
- lambda[i] = computeLambdaTop(i, M, lambda);
+ lambda[i] = computeLambdaTop(i, M, lambda, size);
lambda[i] = std::clamp(lambda[i], min, max);
}
for (; i >= X; i--) {
- lambda[i] = computeLambdaInterior(i, M, lambda);
+ lambda[i] = computeLambdaInterior(i, M, lambda, size);
lambda[i] = std::clamp(lambda[i], min, max);
}
for (; i >= 1; i--) {
- lambda[i] = computeLambdaBottom(i, M, lambda);
+ lambda[i] = computeLambdaBottom(i, M, lambda, size);
lambda[i] = std::clamp(lambda[i], min, max);
}
- lambda[0] = computeLambdaBottomStart(0, M, lambda);
+ lambda[0] = computeLambdaBottomStart(0, M, lambda, size);
lambda[0] = std::clamp(lambda[0], min, max);
double maxDiff = 0;
for (i = 0; i < XY; i++) {
@@ -698,33 +738,33 @@ static double gaussSeidel2Sor(double const M[XY][4], double omega,
}
/* Normalise the values so that the smallest value is 1. */
-static void normalise(double *ptr, size_t n)
+static void normalise(std::vector<double> &results)
{
- double minval = ptr[0];
- for (size_t i = 1; i < n; i++)
- minval = std::min(minval, ptr[i]);
- for (size_t i = 0; i < n; i++)
- ptr[i] /= minval;
+ double minval = *std::min_element(results.begin(), results.end());
+ std::for_each(results.begin(), results.end(),
+ [minval](double val) { return val / minval; });
}
/* Rescale the values so that the average value is 1. */
-static void reaverage(Span<double> data)
+static void reaverage(std::vector<double> &data)
{
double sum = std::accumulate(data.begin(), data.end(), 0.0);
double ratio = 1 / (sum / data.size());
- for (double &d : data)
- d *= ratio;
+ std::for_each(data.begin(), data.end(),
+ [ratio](double val) { return val * ratio; });
}
-static void runMatrixIterations(double const C[XY], double lambda[XY],
- double const W[XY][4], double omega,
- int nIter, double threshold, double lambdaBound)
+static void runMatrixIterations(const std::vector<double> &C,
+ std::vector<double> &lambda,
+ const std::vector<std::array<double, 4>> &W,
+ std::vector<std::array<double, 4>> &M, double omega,
+ unsigned int nIter, double threshold, double lambdaBound,
+ const Size &size)
{
- double M[XY][4];
- constructM(C, W, M);
+ constructM(C, W, M, size);
double lastMaxDiff = std::numeric_limits<double>::max();
- for (int i = 0; i < nIter; i++) {
- double maxDiff = fabs(gaussSeidel2Sor(M, omega, lambda, lambdaBound));
+ for (unsigned int i = 0; i < nIter; i++) {
+ double maxDiff = fabs(gaussSeidel2Sor(M, omega, lambda, lambdaBound, size));
if (maxDiff < threshold) {
LOG(RPiAlsc, Debug)
<< "Stop after " << i + 1 << " iterations";
@@ -741,39 +781,44 @@ static void runMatrixIterations(double const C[XY], double lambda[XY],
lastMaxDiff = maxDiff;
}
/* We're going to normalise the lambdas so the total average is 1. */
- reaverage({ lambda, XY });
+ reaverage(lambda);
}
-static void addLuminanceRb(double result[XY], double const lambda[XY],
- double const luminanceLut[XY],
+static void addLuminanceRb(std::vector<double> &result, const std::vector<double> &lambda,
+ const std::vector<double> &luminanceLut,
double luminanceStrength)
{
- for (int i = 0; i < XY; i++)
+ for (unsigned int i = 0; i < result.size(); i++)
result[i] = lambda[i] * ((luminanceLut[i] - 1) * luminanceStrength + 1);
}
-static void addLuminanceG(double result[XY], double lambda,
- double const luminanceLut[XY],
+static void addLuminanceG(std::vector<double> &result, double lambda,
+ const std::vector<double> &luminanceLut,
double luminanceStrength)
{
- for (int i = 0; i < XY; i++)
+ for (unsigned int i = 0; i < result.size(); i++)
result[i] = lambda * ((luminanceLut[i] - 1) * luminanceStrength + 1);
}
-void addLuminanceToTables(double results[3][Y][X], double const lambdaR[XY],
- double lambdaG, double const lambdaB[XY],
- double const luminanceLut[XY],
+void addLuminanceToTables(std::array<std::vector<double>, 3> &results,
+ const std::vector<double> &lambdaR,
+ double lambdaG, const std::vector<double> &lambdaB,
+ const std::vector<double> &luminanceLut,
double luminanceStrength)
{
- addLuminanceRb((double *)results[0], lambdaR, luminanceLut, luminanceStrength);
- addLuminanceG((double *)results[1], lambdaG, luminanceLut, luminanceStrength);
- addLuminanceRb((double *)results[2], lambdaB, luminanceLut, luminanceStrength);
- normalise((double *)results, 3 * XY);
+ addLuminanceRb(results[0], lambdaR, luminanceLut, luminanceStrength);
+ addLuminanceG(results[1], lambdaG, luminanceLut, luminanceStrength);
+ addLuminanceRb(results[2], lambdaB, luminanceLut, luminanceStrength);
+ for (auto &r : results)
+ normalise(r);
}
void Alsc::doAlsc()
{
- double cr[XY], cb[XY], wr[XY][4], wb[XY][4], calTableR[XY], calTableB[XY], calTableTmp[XY];
+ std::vector<double> &cr = tmpC_[0], &cb = tmpC_[1], &calTableR = tmpC_[2],
+ &calTableB = tmpC_[3], &calTableTmp = tmpC_[4];
+ std::vector<std::array<double, 4>> &wr = tmpM_[0], &wb = tmpM_[1], &M = tmpM_[2];
+
/*
* Calculate our R/B ("Cr"/"Cb") colour statistics, and assess which are
* usable.
@@ -784,9 +829,9 @@ void Alsc::doAlsc()
* case the camera mode is not full-frame.
*/
getCalTable(ct_, config_.calibrationsCr, calTableTmp);
- resampleCalTable(calTableTmp, cameraMode_, calTableR);
+ resampleCalTable(calTableTmp, cameraMode_, config_.tableSize, calTableR);
getCalTable(ct_, config_.calibrationsCb, calTableTmp);
- resampleCalTable(calTableTmp, cameraMode_, calTableB);
+ resampleCalTable(calTableTmp, cameraMode_, config_.tableSize, calTableB);
/*
* You could print out the cal tables for this image here, if you're
* tuning the algorithm...
@@ -796,13 +841,13 @@ void Alsc::doAlsc()
applyCalTable(calTableR, cr);
applyCalTable(calTableB, cb);
/* Compute weights between zones. */
- computeW(cr, config_.sigmaCr, wr);
- computeW(cb, config_.sigmaCb, wb);
+ computeW(cr, config_.sigmaCr, wr, config_.tableSize);
+ computeW(cb, config_.sigmaCb, wb, config_.tableSize);
/* Run Gauss-Seidel iterations over the resulting matrix, for R and B. */
- runMatrixIterations(cr, lambdaR_, wr, config_.omega, config_.nIter,
- config_.threshold, config_.lambdaBound);
- runMatrixIterations(cb, lambdaB_, wb, config_.omega, config_.nIter,
- config_.threshold, config_.lambdaBound);
+ runMatrixIterations(cr, lambdaR_, wr, M, config_.omega, config_.nIter,
+ config_.threshold, config_.lambdaBound, config_.tableSize);
+ runMatrixIterations(cb, lambdaB_, wb, M, config_.omega, config_.nIter,
+ config_.threshold, config_.lambdaBound, config_.tableSize);
/*
* Fold the calibrated gains into our final lambda values. (Note that on
* the next run, we re-start with the lambda values that don't have the
diff --git a/src/ipa/raspberrypi/controller/rpi/alsc.h b/src/ipa/raspberrypi/controller/rpi/alsc.h
index 9167c9ff..85e998db 100644
--- a/src/ipa/raspberrypi/controller/rpi/alsc.h
+++ b/src/ipa/raspberrypi/controller/rpi/alsc.h
@@ -6,9 +6,13 @@
*/
#pragma once
+#include <array>
#include <mutex>
#include <condition_variable>
#include <thread>
+#include <vector>
+
+#include <libcamera/geometry.h>
#include "../algorithm.h"
#include "../alsc_status.h"
@@ -20,7 +24,7 @@ namespace RPiController {
struct AlscCalibration {
double ct;
- double table[AlscCellsX * AlscCellsY];
+ std::vector<double> table;
};
struct AlscConfig {
@@ -36,13 +40,14 @@ struct AlscConfig {
uint16_t minG;
double omega;
uint32_t nIter;
- double luminanceLut[AlscCellsX * AlscCellsY];
+ std::vector<double> luminanceLut;
double luminanceStrength;
std::vector<AlscCalibration> calibrationsCr;
std::vector<AlscCalibration> calibrationsCb;
double defaultCt; /* colour temperature if no metadata found */
double threshold; /* iteration termination threshold */
double lambdaBound; /* upper/lower bound for lambda from a value of 1 */
+ libcamera::Size tableSize;
};
class Alsc : public Algorithm
@@ -62,7 +67,7 @@ private:
AlscConfig config_;
bool firstTime_;
CameraMode cameraMode_;
- double luminanceTable_[AlscCellsX * AlscCellsY];
+ std::vector<double> luminanceTable_;
std::thread asyncThread_;
void asyncFunc(); /* asynchronous thread function */
std::mutex mutex_;
@@ -88,8 +93,8 @@ private:
int frameCount_;
/* counts up to startupFrames for Process function */
int frameCount2_;
- double syncResults_[3][AlscCellsY][AlscCellsX];
- double prevSyncResults_[3][AlscCellsY][AlscCellsX];
+ std::array<std::vector<double>, 3> syncResults_;
+ std::array<std::vector<double>, 3> prevSyncResults_;
void waitForAysncThread();
/*
* The following are for the asynchronous thread to use, though the main
@@ -100,12 +105,16 @@ private:
void fetchAsyncResults();
double ct_;
RgbyRegions statistics_;
- double asyncResults_[3][AlscCellsY][AlscCellsX];
- double asyncLambdaR_[AlscCellsX * AlscCellsY];
- double asyncLambdaB_[AlscCellsX * AlscCellsY];
+ std::array<std::vector<double>, 3> asyncResults_;
+ std::vector<double> asyncLambdaR_;
+ std::vector<double> asyncLambdaB_;
void doAlsc();
- double lambdaR_[AlscCellsX * AlscCellsY];
- double lambdaB_[AlscCellsX * AlscCellsY];
+ std::vector<double> lambdaR_;
+ std::vector<double> lambdaB_;
+
+ /* Temporaries for the computations */
+ std::array<std::vector<double>, 5> tmpC_;
+ std::array<std::vector<std::array<double, 4>>, 3> tmpM_;
};
} /* namespace RPiController */
generated by cgit v1.2.1 (git 2.18.0) at 2024-12-20 07:34:43 +0000