summaryrefslogtreecommitdiff
path: root/src
diff options
context:
space:
mode:
Diffstat (limited to 'src')
-rw-r--r--src/ipa/raspberrypi/controller/rpi/alsc.cpp218
-rw-r--r--src/ipa/raspberrypi/controller/rpi/alsc.h68
2 files changed, 164 insertions, 122 deletions
diff --git a/src/ipa/raspberrypi/controller/rpi/alsc.cpp b/src/ipa/raspberrypi/controller/rpi/alsc.cpp
index 51fe5d73..524c4809 100644
--- a/src/ipa/raspberrypi/controller/rpi/alsc.cpp
+++ b/src/ipa/raspberrypi/controller/rpi/alsc.cpp
@@ -49,11 +49,10 @@ char const *Alsc::name() const
return NAME;
}
-static int generateLut(std::vector<double> &lut, const libcamera::YamlObject &params,
- const Size &size)
+static int generateLut(Array2D<double> &lut, const libcamera::YamlObject &params)
{
/* These must be signed ints for the co-ordinate calculations below. */
- int X = size.width, Y = size.height;
+ int X = lut.dimensions().width, Y = lut.dimensions().height;
double cstrength = params["corner_strength"].get<double>(2.0);
if (cstrength <= 1.0) {
LOG(RPiAlsc, Error) << "corner_strength must be > 1.0";
@@ -82,9 +81,9 @@ static int generateLut(std::vector<double> &lut, const libcamera::YamlObject &pa
return 0;
}
-static int readLut(std::vector<double> &lut, const libcamera::YamlObject &params, const Size &size)
+static int readLut(Array2D<double> &lut, const libcamera::YamlObject &params)
{
- if (params.size() != size.width * size.height) {
+ if (params.size() != lut.size()) {
LOG(RPiAlsc, Error) << "Invalid number of entries in LSC table";
return -EINVAL;
}
@@ -128,7 +127,7 @@ static int readCalibrations(std::vector<AlscCalibration> &calibrations,
}
int num = 0;
- calibration.table.resize(size.width * size.height);
+ calibration.table.resize(size);
for (const auto &elem : table.asList()) {
value = elem.get<double>();
if (!value)
@@ -160,13 +159,13 @@ int Alsc::read(const libcamera::YamlObject &params)
config_.luminanceStrength =
params["luminance_strength"].get<double>(1.0);
- config_.luminanceLut.resize(config_.tableSize.width * config_.tableSize.height, 1.0);
+ config_.luminanceLut.resize(config_.tableSize, 1.0);
int ret = 0;
if (params.contains("corner_strength"))
- ret = generateLut(config_.luminanceLut, params, config_.tableSize);
+ ret = generateLut(config_.luminanceLut, params);
else if (params.contains("luminance_lut"))
- ret = readLut(config_.luminanceLut, params["luminance_lut"], config_.tableSize);
+ ret = readLut(config_.luminanceLut, params["luminance_lut"]);
else
LOG(RPiAlsc, Warning)
<< "no luminance table - assume unity everywhere";
@@ -191,16 +190,16 @@ int Alsc::read(const libcamera::YamlObject &params)
static double getCt(Metadata *metadata, double defaultCt);
static void getCalTable(double ct, std::vector<AlscCalibration> const &calibrations,
- 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,
+ Array2D<double> &calTable);
+static void resampleCalTable(const Array2D<double> &calTableIn, CameraMode const &cameraMode,
+ Array2D<double> &calTableOut);
+static void compensateLambdasForCal(const Array2D<double> &calTable,
+ const Array2D<double> &oldLambdas,
+ Array2D<double> &newLambdas);
+static void addLuminanceToTables(std::array<Array2D<double>, 3> &results,
+ const Array2D<double> &lambdaR, double lambdaG,
+ const Array2D<double> &lambdaB,
+ const Array2D<double> &luminanceLut,
double luminanceStrength);
void Alsc::initialise()
@@ -212,22 +211,22 @@ void Alsc::initialise()
const size_t XY = config_.tableSize.width * config_.tableSize.height;
for (auto &r : syncResults_)
- r.resize(XY);
+ r.resize(config_.tableSize);
for (auto &r : prevSyncResults_)
- r.resize(XY);
+ r.resize(config_.tableSize);
for (auto &r : asyncResults_)
- r.resize(XY);
+ r.resize(config_.tableSize);
- luminanceTable_.resize(XY);
- asyncLambdaR_.resize(XY);
- asyncLambdaB_.resize(XY);
+ luminanceTable_.resize(config_.tableSize);
+ asyncLambdaR_.resize(config_.tableSize);
+ asyncLambdaB_.resize(config_.tableSize);
/* The lambdas are initialised in the SwitchMode. */
- lambdaR_.resize(XY);
- lambdaB_.resize(XY);
+ lambdaR_.resize(config_.tableSize);
+ lambdaB_.resize(config_.tableSize);
/* Temporaries for the computations, but sensible to allocate this up-front! */
for (auto &c : tmpC_)
- c.resize(XY);
+ c.resize(config_.tableSize);
for (auto &m : tmpM_)
m.resize(XY);
}
@@ -290,7 +289,7 @@ 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_, config_.tableSize, luminanceTable_);
+ resampleCalTable(config_.luminanceLut, cameraMode_, luminanceTable_);
if (resetTables) {
/*
@@ -302,11 +301,11 @@ void Alsc::switchMode(CameraMode const &cameraMode,
*/
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];
+ Array2D<double> &calTableR = tmpC_[0], &calTableB = tmpC_[1], &calTableTmp = tmpC_[2];
getCalTable(ct_, config_.calibrationsCr, calTableTmp);
- resampleCalTable(calTableTmp, cameraMode_, config_.tableSize, calTableR);
+ resampleCalTable(calTableTmp, cameraMode_, calTableR);
getCalTable(ct_, config_.calibrationsCb, calTableTmp);
- resampleCalTable(calTableTmp, cameraMode_, config_.tableSize, calTableB);
+ resampleCalTable(calTableTmp, cameraMode_, calTableB);
compensateLambdasForCal(calTableR, lambdaR_, asyncLambdaR_);
compensateLambdasForCal(calTableB, lambdaB_, asyncLambdaB_);
addLuminanceToTables(syncResults_, asyncLambdaR_, 1.0, asyncLambdaB_,
@@ -411,9 +410,9 @@ void Alsc::prepare(Metadata *imageMetadata)
}
/* Put output values into status metadata. */
AlscStatus status;
- status.r = prevSyncResults_[0];
- status.g = prevSyncResults_[1];
- status.b = prevSyncResults_[2];
+ status.r = prevSyncResults_[0].data();
+ status.g = prevSyncResults_[1].data();
+ status.b = prevSyncResults_[2].data();
imageMetadata->set("alsc.status", status);
}
@@ -457,7 +456,7 @@ void Alsc::asyncFunc()
}
void getCalTable(double ct, std::vector<AlscCalibration> const &calibrations,
- std::vector<double> &calTable)
+ Array2D<double> &calTable)
{
if (calibrations.empty()) {
std::fill(calTable.begin(), calTable.end(), 1.0);
@@ -486,12 +485,12 @@ void getCalTable(double ct, std::vector<AlscCalibration> const &calibrations,
}
}
-void resampleCalTable(const std::vector<double> &calTableIn,
- CameraMode const &cameraMode, const Size &size,
- std::vector<double> &calTableOut)
+void resampleCalTable(const Array2D<double> &calTableIn,
+ CameraMode const &cameraMode,
+ Array2D<double> &calTableOut)
{
- int X = size.width;
- int Y = size.height;
+ int X = calTableIn.dimensions().width;
+ int Y = calTableIn.dimensions().height;
/*
* Precalculate and cache the x sampling locations and phases to save
@@ -529,9 +528,9 @@ void resampleCalTable(const std::vector<double> &calTableIn,
yLo = Y - 1 - yLo;
yHi = Y - 1 - yHi;
}
- double const *rowAbove = calTableIn.data() + X * yLo;
- double const *rowBelow = calTableIn.data() + X * yHi;
- double *out = calTableOut.data() + X * j;
+ double const *rowAbove = calTableIn.ptr() + X * yLo;
+ double const *rowBelow = calTableIn.ptr() + X * yHi;
+ double *out = calTableOut.ptr() + X * j;
for (int i = 0; i < X; i++) {
double above = rowAbove[xLo[i]] * (1 - xf[i]) +
rowAbove[xHi[i]] * xf[i];
@@ -543,8 +542,8 @@ void resampleCalTable(const std::vector<double> &calTableIn,
}
/* Calculate chrominance statistics (R/G and B/G) for each region. */
-static void calculateCrCb(const RgbyRegions &awbRegion, std::vector<double> &cr,
- std::vector<double> &cb, uint32_t minCount, uint16_t minG)
+static void calculateCrCb(const RgbyRegions &awbRegion, Array2D<double> &cr,
+ Array2D<double> &cb, uint32_t minCount, uint16_t minG)
{
for (unsigned int i = 0; i < cr.size(); i++) {
auto s = awbRegion.get(i);
@@ -559,16 +558,16 @@ static void calculateCrCb(const RgbyRegions &awbRegion, std::vector<double> &cr,
}
}
-static void applyCalTable(const std::vector<double> &calTable, std::vector<double> &C)
+static void applyCalTable(const Array2D<double> &calTable, Array2D<double> &C)
{
for (unsigned int i = 0; i < C.size(); i++)
if (C[i] != InsufficientData)
C[i] *= calTable[i];
}
-void compensateLambdasForCal(const std::vector<double> &calTable,
- const std::vector<double> &oldLambdas,
- std::vector<double> &newLambdas)
+void compensateLambdasForCal(const Array2D<double> &calTable,
+ const Array2D<double> &oldLambdas,
+ Array2D<double> &newLambdas)
{
double minNewLambda = std::numeric_limits<double>::max();
for (unsigned int i = 0; i < newLambdas.size(); i++) {
@@ -579,9 +578,9 @@ void compensateLambdasForCal(const std::vector<double> &calTable,
newLambdas[i] /= minNewLambda;
}
-[[maybe_unused]] static void printCalTable(const std::vector<double> &C,
- const Size &size)
+[[maybe_unused]] static void printCalTable(const Array2D<double> &C)
{
+ const Size &size = C.dimensions();
printf("table: [\n");
for (unsigned int j = 0; j < size.height; j++) {
for (unsigned int i = 0; i < size.width; i++) {
@@ -607,11 +606,11 @@ static double computeWeight(double Ci, double Cj, double sigma)
}
/* Compute all weights. */
-static void computeW(const std::vector<double> &C, double sigma,
- std::vector<std::array<double, 4>> &W, const Size &size)
+static void computeW(const Array2D<double> &C, double sigma,
+ std::vector<std::array<double, 4>> &W)
{
- size_t XY = size.width * size.height;
- size_t X = size.width;
+ size_t XY = C.size();
+ size_t X = C.dimensions().width;
for (unsigned int i = 0; i < XY; i++) {
/* Start with neighbour above and go clockwise. */
@@ -623,13 +622,12 @@ static void computeW(const std::vector<double> &C, double sigma,
}
/* Compute M, the large but sparse matrix such that M * lambdas = 0. */
-static void constructM(const std::vector<double> &C,
+static void constructM(const Array2D<double> &C,
const std::vector<std::array<double, 4>> &W,
- std::vector<std::array<double, 4>> &M,
- const Size &size)
+ std::vector<std::array<double, 4>> &M)
{
- size_t XY = size.width * size.height;
- size_t X = size.width;
+ size_t XY = C.size();
+ size_t X = C.dimensions().width;
double epsilon = 0.001;
for (unsigned int i = 0; i < XY; i++) {
@@ -654,79 +652,78 @@ static void constructM(const std::vector<double> &C,
* need to test the i value to exclude them.
*/
static double computeLambdaBottom(int i, const std::vector<std::array<double, 4>> &M,
- std::vector<double> &lambda, const Size &size)
+ Array2D<double> &lambda)
{
- return M[i][1] * lambda[i + 1] + M[i][2] * lambda[i + size.width] +
+ return M[i][1] * lambda[i + 1] + M[i][2] * lambda[i + lambda.dimensions().width] +
M[i][3] * lambda[i - 1];
}
static double computeLambdaBottomStart(int i, const std::vector<std::array<double, 4>> &M,
- std::vector<double> &lambda, const Size &size)
+ Array2D<double> &lambda)
{
- return M[i][1] * lambda[i + 1] + M[i][2] * lambda[i + size.width];
+ return M[i][1] * lambda[i + 1] + M[i][2] * lambda[i + lambda.dimensions().width];
}
static double computeLambdaInterior(int i, const std::vector<std::array<double, 4>> &M,
- std::vector<double> &lambda, const Size &size)
+ Array2D<double> &lambda)
{
- 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];
+ return M[i][0] * lambda[i - lambda.dimensions().width] + M[i][1] * lambda[i + 1] +
+ M[i][2] * lambda[i + lambda.dimensions().width] + M[i][3] * lambda[i - 1];
}
static double computeLambdaTop(int i, const std::vector<std::array<double, 4>> &M,
- std::vector<double> &lambda, const Size &size)
+ Array2D<double> &lambda)
{
- return M[i][0] * lambda[i - size.width] + M[i][1] * lambda[i + 1] +
+ return M[i][0] * lambda[i - lambda.dimensions().width] + M[i][1] * lambda[i + 1] +
M[i][3] * lambda[i - 1];
}
static double computeLambdaTopEnd(int i, const std::vector<std::array<double, 4>> &M,
- std::vector<double> &lambda, const Size &size)
+ Array2D<double> &lambda)
{
- return M[i][0] * lambda[i - size.width] + M[i][3] * lambda[i - 1];
+ return M[i][0] * lambda[i - lambda.dimensions().width] + M[i][3] * lambda[i - 1];
}
/* Gauss-Seidel iteration with over-relaxation. */
static double gaussSeidel2Sor(const std::vector<std::array<double, 4>> &M, double omega,
- std::vector<double> &lambda, double lambdaBound,
- const Size &size)
+ Array2D<double> &lambda, double lambdaBound)
{
- int XY = size.width * size.height;
- int X = size.width;
+ int XY = lambda.size();
+ int X = lambda.dimensions().width;
const double min = 1 - lambdaBound, max = 1 + lambdaBound;
- std::vector<double> oldLambda = lambda;
+ Array2D<double> oldLambda = lambda;
int i;
- lambda[0] = computeLambdaBottomStart(0, M, lambda, size);
+ lambda[0] = computeLambdaBottomStart(0, M, lambda);
lambda[0] = std::clamp(lambda[0], min, max);
for (i = 1; i < X; i++) {
- lambda[i] = computeLambdaBottom(i, M, lambda, size);
+ lambda[i] = computeLambdaBottom(i, M, lambda);
lambda[i] = std::clamp(lambda[i], min, max);
}
for (; i < XY - X; i++) {
- lambda[i] = computeLambdaInterior(i, M, lambda, size);
+ lambda[i] = computeLambdaInterior(i, M, lambda);
lambda[i] = std::clamp(lambda[i], min, max);
}
for (; i < XY - 1; i++) {
- lambda[i] = computeLambdaTop(i, M, lambda, size);
+ lambda[i] = computeLambdaTop(i, M, lambda);
lambda[i] = std::clamp(lambda[i], min, max);
}
- lambda[i] = computeLambdaTopEnd(i, M, lambda, size);
+ lambda[i] = computeLambdaTopEnd(i, M, lambda);
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, size);
+ lambda[i] = computeLambdaTopEnd(i, M, lambda);
lambda[i] = std::clamp(lambda[i], min, max);
for (i = XY - 2; i >= XY - X; i--) {
- lambda[i] = computeLambdaTop(i, M, lambda, size);
+ lambda[i] = computeLambdaTop(i, M, lambda);
lambda[i] = std::clamp(lambda[i], min, max);
}
for (; i >= X; i--) {
- lambda[i] = computeLambdaInterior(i, M, lambda, size);
+ lambda[i] = computeLambdaInterior(i, M, lambda);
lambda[i] = std::clamp(lambda[i], min, max);
}
for (; i >= 1; i--) {
- lambda[i] = computeLambdaBottom(i, M, lambda, size);
+ lambda[i] = computeLambdaBottom(i, M, lambda);
lambda[i] = std::clamp(lambda[i], min, max);
}
- lambda[0] = computeLambdaBottomStart(0, M, lambda, size);
+ lambda[0] = computeLambdaBottomStart(0, M, lambda);
lambda[0] = std::clamp(lambda[0], min, max);
double maxDiff = 0;
for (i = 0; i < XY; i++) {
@@ -738,7 +735,7 @@ static double gaussSeidel2Sor(const std::vector<std::array<double, 4>> &M, doubl
}
/* Normalise the values so that the smallest value is 1. */
-static void normalise(std::vector<double> &results)
+static void normalise(Array2D<double> &results)
{
double minval = *std::min_element(results.begin(), results.end());
std::for_each(results.begin(), results.end(),
@@ -746,7 +743,7 @@ static void normalise(std::vector<double> &results)
}
/* Rescale the values so that the average value is 1. */
-static void reaverage(std::vector<double> &data)
+static void reaverage(Array2D<double> &data)
{
double sum = std::accumulate(data.begin(), data.end(), 0.0);
double ratio = 1 / (sum / data.size());
@@ -754,17 +751,16 @@ static void reaverage(std::vector<double> &data)
[ratio](double val) { return val * ratio; });
}
-static void runMatrixIterations(const std::vector<double> &C,
- std::vector<double> &lambda,
+static void runMatrixIterations(const Array2D<double> &C,
+ Array2D<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)
+ unsigned int nIter, double threshold, double lambdaBound)
{
- constructM(C, W, M, size);
+ constructM(C, W, M);
double lastMaxDiff = std::numeric_limits<double>::max();
for (unsigned int i = 0; i < nIter; i++) {
- double maxDiff = fabs(gaussSeidel2Sor(M, omega, lambda, lambdaBound, size));
+ double maxDiff = fabs(gaussSeidel2Sor(M, omega, lambda, lambdaBound));
if (maxDiff < threshold) {
LOG(RPiAlsc, Debug)
<< "Stop after " << i + 1 << " iterations";
@@ -784,26 +780,26 @@ static void runMatrixIterations(const std::vector<double> &C,
reaverage(lambda);
}
-static void addLuminanceRb(std::vector<double> &result, const std::vector<double> &lambda,
- const std::vector<double> &luminanceLut,
+static void addLuminanceRb(Array2D<double> &result, const Array2D<double> &lambda,
+ const Array2D<double> &luminanceLut,
double luminanceStrength)
{
for (unsigned int i = 0; i < result.size(); i++)
result[i] = lambda[i] * ((luminanceLut[i] - 1) * luminanceStrength + 1);
}
-static void addLuminanceG(std::vector<double> &result, double lambda,
- const std::vector<double> &luminanceLut,
+static void addLuminanceG(Array2D<double> &result, double lambda,
+ const Array2D<double> &luminanceLut,
double luminanceStrength)
{
for (unsigned int i = 0; i < result.size(); i++)
result[i] = lambda * ((luminanceLut[i] - 1) * luminanceStrength + 1);
}
-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,
+void addLuminanceToTables(std::array<Array2D<double>, 3> &results,
+ const Array2D<double> &lambdaR,
+ double lambdaG, const Array2D<double> &lambdaB,
+ const Array2D<double> &luminanceLut,
double luminanceStrength)
{
addLuminanceRb(results[0], lambdaR, luminanceLut, luminanceStrength);
@@ -815,8 +811,8 @@ void addLuminanceToTables(std::array<std::vector<double>, 3> &results,
void Alsc::doAlsc()
{
- std::vector<double> &cr = tmpC_[0], &cb = tmpC_[1], &calTableR = tmpC_[2],
- &calTableB = tmpC_[3], &calTableTmp = tmpC_[4];
+ Array2D<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];
/*
@@ -829,9 +825,9 @@ void Alsc::doAlsc()
* case the camera mode is not full-frame.
*/
getCalTable(ct_, config_.calibrationsCr, calTableTmp);
- resampleCalTable(calTableTmp, cameraMode_, config_.tableSize, calTableR);
+ resampleCalTable(calTableTmp, cameraMode_, calTableR);
getCalTable(ct_, config_.calibrationsCb, calTableTmp);
- resampleCalTable(calTableTmp, cameraMode_, config_.tableSize, calTableB);
+ resampleCalTable(calTableTmp, cameraMode_, calTableB);
/*
* You could print out the cal tables for this image here, if you're
* tuning the algorithm...
@@ -841,13 +837,13 @@ void Alsc::doAlsc()
applyCalTable(calTableR, cr);
applyCalTable(calTableB, cb);
/* Compute weights between zones. */
- computeW(cr, config_.sigmaCr, wr, config_.tableSize);
- computeW(cb, config_.sigmaCb, wb, config_.tableSize);
+ computeW(cr, config_.sigmaCr, wr);
+ computeW(cb, config_.sigmaCb, wb);
/* Run Gauss-Seidel iterations over the resulting matrix, for R and B. */
runMatrixIterations(cr, lambdaR_, wr, M, config_.omega, config_.nIter,
- config_.threshold, config_.lambdaBound, config_.tableSize);
+ config_.threshold, config_.lambdaBound);
runMatrixIterations(cb, lambdaB_, wb, M, config_.omega, config_.nIter,
- config_.threshold, config_.lambdaBound, config_.tableSize);
+ config_.threshold, config_.lambdaBound);
/*
* 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 85e998db..1ab61299 100644
--- a/src/ipa/raspberrypi/controller/rpi/alsc.h
+++ b/src/ipa/raspberrypi/controller/rpi/alsc.h
@@ -22,9 +22,55 @@ namespace RPiController {
/* Algorithm to generate automagic LSC (Lens Shading Correction) tables. */
+/*
+ * The Array2D class is a very thin wrapper round std::vector so that it can
+ * be used in exactly the same way in the code but carries its correct width
+ * and height ("dimensions") with it.
+ */
+
+template<typename T>
+class Array2D
+{
+public:
+ using Size = libcamera::Size;
+
+ const Size &dimensions() const { return dimensions_; }
+
+ size_t size() const { return data_.size(); }
+
+ const std::vector<T> &data() const { return data_; }
+
+ void resize(const Size &dims)
+ {
+ dimensions_ = dims;
+ data_.resize(dims.width * dims.height);
+ }
+
+ void resize(const Size &dims, const T &value)
+ {
+ resize(dims);
+ std::fill(data_.begin(), data_.end(), value);
+ }
+
+ T &operator[](int index) { return data_[index]; }
+
+ const T &operator[](int index) const { return data_[index]; }
+
+ T *ptr() { return data_.data(); }
+
+ const T *ptr() const { return data_.data(); }
+
+ auto begin() { return data_.begin(); }
+ auto end() { return data_.end(); }
+
+private:
+ Size dimensions_;
+ std::vector<T> data_;
+};
+
struct AlscCalibration {
double ct;
- std::vector<double> table;
+ Array2D<double> table;
};
struct AlscConfig {
@@ -40,7 +86,7 @@ struct AlscConfig {
uint16_t minG;
double omega;
uint32_t nIter;
- std::vector<double> luminanceLut;
+ Array2D<double> luminanceLut;
double luminanceStrength;
std::vector<AlscCalibration> calibrationsCr;
std::vector<AlscCalibration> calibrationsCb;
@@ -67,7 +113,7 @@ private:
AlscConfig config_;
bool firstTime_;
CameraMode cameraMode_;
- std::vector<double> luminanceTable_;
+ Array2D<double> luminanceTable_;
std::thread asyncThread_;
void asyncFunc(); /* asynchronous thread function */
std::mutex mutex_;
@@ -93,8 +139,8 @@ private:
int frameCount_;
/* counts up to startupFrames for Process function */
int frameCount2_;
- std::array<std::vector<double>, 3> syncResults_;
- std::array<std::vector<double>, 3> prevSyncResults_;
+ std::array<Array2D<double>, 3> syncResults_;
+ std::array<Array2D<double>, 3> prevSyncResults_;
void waitForAysncThread();
/*
* The following are for the asynchronous thread to use, though the main
@@ -105,15 +151,15 @@ private:
void fetchAsyncResults();
double ct_;
RgbyRegions statistics_;
- std::array<std::vector<double>, 3> asyncResults_;
- std::vector<double> asyncLambdaR_;
- std::vector<double> asyncLambdaB_;
+ std::array<Array2D<double>, 3> asyncResults_;
+ Array2D<double> asyncLambdaR_;
+ Array2D<double> asyncLambdaB_;
void doAlsc();
- std::vector<double> lambdaR_;
- std::vector<double> lambdaB_;
+ Array2D<double> lambdaR_;
+ Array2D<double> lambdaB_;
/* Temporaries for the computations */
- std::array<std::vector<double>, 5> tmpC_;
+ std::array<Array2D<double>, 5> tmpC_;
std::array<std::vector<std::array<double, 4>>, 3> tmpM_;
};