diff --git a/src/ipa/raspberrypi/controller/alsc_status.h b/src/ipa/raspberrypi/controller/alsc_status.h index e5aa7e37c330..49a9f4a0cb5a 100644 --- a/src/ipa/raspberrypi/controller/alsc_status.h +++ b/src/ipa/raspberrypi/controller/alsc_status.h @@ -6,16 +6,17 @@ */ #pragma once +#include + /* * The ALSC algorithm should post the following structure into the image's * "alsc.status" metadata. */ -constexpr unsigned int AlscCellsX = 16; -constexpr unsigned int AlscCellsY = 12; - struct AlscStatus { - double r[AlscCellsY][AlscCellsX]; - double g[AlscCellsY][AlscCellsX]; - double b[AlscCellsY][AlscCellsX]; + std::vector r; + std::vector g; + std::vector b; + unsigned int rows; + unsigned int cols; }; diff --git a/src/ipa/raspberrypi/controller/rpi/alsc.cpp b/src/ipa/raspberrypi/controller/rpi/alsc.cpp index eb4e2f9496e1..51fe5d73f52d 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 #include #include #include @@ -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 ¶ms) +static int generateLut(std::vector &lut, const libcamera::YamlObject ¶ms, + 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(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 ¶ms) return 0; } -static int readLut(double *lut, const libcamera::YamlObject ¶ms) +static int readLut(std::vector &lut, const libcamera::YamlObject ¶ms, 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 ¶ms) static int readCalibrations(std::vector &calibrations, const libcamera::YamlObject ¶ms, - 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 &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 &calibrations, } int num = 0; + calibration.table.resize(size.width * size.height); for (const auto &elem : table.asList()) { value = elem.get(); if (!value) @@ -134,7 +136,7 @@ static int readCalibrations(std::vector &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 &calibrations, int Alsc::read(const libcamera::YamlObject ¶ms) { + config_.tableSize = getHardwareConfig().awbRegions; config_.framePeriod = params["frame_period"].get(12); config_.startupFrames = params["startup_frames"].get(10); config_.speed = params["speed"].get(0.05); @@ -153,28 +156,29 @@ int Alsc::read(const libcamera::YamlObject ¶ms) config_.minCount = params["min_count"].get(10.0); config_.minG = params["min_G"].get(50); config_.omega = params["omega"].get(1.3); - config_.nIter = params["n_iter"].get(X + Y); + config_.nIter = params["n_iter"].get(config_.tableSize.width + config_.tableSize.height); config_.luminanceStrength = params["luminance_strength"].get(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 ¶ms) static double getCt(Metadata *metadata, double defaultCt); static void getCalTable(double ct, std::vector 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 &calTable); +static void resampleCalTable(const std::vector &calTableIn, CameraMode const &cameraMode, + const Size &size, std::vector &calTableOut); +static void compensateLambdasForCal(const std::vector &calTable, + const std::vector &oldLambdas, + std::vector &newLambdas); +static void addLuminanceToTables(std::array, 3> &results, + const std::vector &lambdaR, double lambdaG, + const std::vector &lambdaB, + const std::vector &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 &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 ®ions, 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 &rTable = status.r; + const std::vector &gTable = status.g; + const std::vector &bTable = status.b; for (unsigned int i = 0; i < stats->awbRegions.numRegions(); i++) { auto r = stats->awbRegions.get(i); r.val.rSum = static_cast(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 const &calibrations, - double calTable[XY]) + std::vector &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 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 const &calibrations, } } -void resampleCalTable(double const calTableIn[XY], - CameraMode const &cameraMode, double calTableOut[XY]) +void resampleCalTable(const std::vector &calTableIn, + CameraMode const &cameraMode, const Size &size, + std::vector &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 &cr, + std::vector &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 &calTable, std::vector &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 &calTable, + const std::vector &oldLambdas, + std::vector &newLambdas) { double minNewLambda = std::numeric_limits::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 &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 &C, double sigma, + std::vector> &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 &C, + const std::vector> &W, + std::vector> &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> &M, + std::vector &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> &M, + std::vector &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> &M, + std::vector &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> &M, + std::vector &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> &M, + std::vector &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> &M, double omega, + std::vector &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 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 &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 data) +static void reaverage(std::vector &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 &C, + std::vector &lambda, + const std::vector> &W, + std::vector> &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::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 &result, const std::vector &lambda, + const std::vector &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 &result, double lambda, + const std::vector &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, 3> &results, + const std::vector &lambdaR, + double lambdaG, const std::vector &lambdaB, + const std::vector &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 &cr = tmpC_[0], &cb = tmpC_[1], &calTableR = tmpC_[2], + &calTableB = tmpC_[3], &calTableTmp = tmpC_[4]; + std::vector> &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 9167c9ffa2e3..85e998db40e9 100644 --- a/src/ipa/raspberrypi/controller/rpi/alsc.h +++ b/src/ipa/raspberrypi/controller/rpi/alsc.h @@ -6,9 +6,13 @@ */ #pragma once +#include #include #include #include +#include + +#include #include "../algorithm.h" #include "../alsc_status.h" @@ -20,7 +24,7 @@ namespace RPiController { struct AlscCalibration { double ct; - double table[AlscCellsX * AlscCellsY]; + std::vector table; }; struct AlscConfig { @@ -36,13 +40,14 @@ struct AlscConfig { uint16_t minG; double omega; uint32_t nIter; - double luminanceLut[AlscCellsX * AlscCellsY]; + std::vector luminanceLut; double luminanceStrength; std::vector calibrationsCr; std::vector 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 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, 3> syncResults_; + std::array, 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, 3> asyncResults_; + std::vector asyncLambdaR_; + std::vector asyncLambdaB_; void doAlsc(); - double lambdaR_[AlscCellsX * AlscCellsY]; - double lambdaB_[AlscCellsX * AlscCellsY]; + std::vector lambdaR_; + std::vector lambdaB_; + + /* Temporaries for the computations */ + std::array, 5> tmpC_; + std::array>, 3> tmpM_; }; } /* namespace RPiController */ diff --git a/src/ipa/raspberrypi/raspberrypi.cpp b/src/ipa/raspberrypi/raspberrypi.cpp index e24529920a4b..c74558f1dc0c 100644 --- a/src/ipa/raspberrypi/raspberrypi.cpp +++ b/src/ipa/raspberrypi/raspberrypi.cpp @@ -14,6 +14,7 @@ #include #include #include +#include #include @@ -174,7 +175,7 @@ private: void applyDPC(const struct DpcStatus *dpcStatus, ControlList &ctrls); void applyLS(const struct AlscStatus *lsStatus, ControlList &ctrls); void applyAF(const struct AfStatus *afStatus, ControlList &lensCtrls); - void resampleTable(uint16_t dest[], double const src[12][16], int destW, int destH); + void resampleTable(uint16_t dest[], const std::vector &src, int destW, int destH); std::map buffers_; @@ -1769,7 +1770,7 @@ void IPARPi::applyAF(const struct AfStatus *afStatus, ControlList &lensCtrls) * Resamples a 16x12 table with central sampling to destW x destH with corner * sampling. */ -void IPARPi::resampleTable(uint16_t dest[], double const src[12][16], +void IPARPi::resampleTable(uint16_t dest[], const std::vector &src, int destW, int destH) { /* @@ -1794,8 +1795,8 @@ void IPARPi::resampleTable(uint16_t dest[], double const src[12][16], double yf = y - yLo; int yHi = yLo < 11 ? yLo + 1 : 11; yLo = yLo > 0 ? yLo : 0; - double const *rowAbove = src[yLo]; - double const *rowBelow = src[yHi]; + double const *rowAbove = src.data() + yLo * 16; + double const *rowBelow = src.data() + yHi * 16; for (int i = 0; i < destW; 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];