int analyse(const char* filename, const char* outFile){
Mat img = cv_imread(filename), imgG, imgTmp;
if(!img.data){
//cerr << "invalid image" << endl;
throw "[ghosts] invalid image";
}
cvtColor(img, imgG, CV_BGR2GRAY);
int bCntX = (img.cols - w ) / bSize, bCntY = (img.rows - w) / bSize;
int bCnt = bCntX * bCntY;
int bCntR = bCnt;
int res = 0;
vector<vector<vector<double> > > bGhosts(bCnt);
vector<vector<vector<double> > > bInv(bCnt);
vector<double> bPredict(bCnt);
for(int i = 0; i < bCnt; i++){
bGhosts[i].resize(w * w);
for(int j = 0; j < w * w; j++)
bGhosts[i][j].resize(101);
}
double elaAv = 0.0;
for(int q = min(qNorm, qMin); q <= qMax; q++){
if(!(q == qNorm || (q >= qMin && q <= qMax)))
continue;
for(int j = 0; j < w * w; j++){
Rect curRoi = Rect(j % w, j / w, img.cols - j % w, img.rows - j / w);
vector<int> compParams;
vector<uchar> buff;
compParams.push_back(CV_IMWRITE_JPEG_QUALITY);
compParams.push_back(q);
imencode(".jpg", imgG(curRoi), buff, compParams);
imgTmp = imdecode(buff, 0);
for(int i = 0; i < bCnt; i++){
bGhosts[i][j][q] = calcDiff(imgG(curRoi), imgTmp, bCoordX, bCoordY, bCoordX + bSize, bCoordY + bSize);
if(q == qNorm && j == 1)
elaAv += bGhosts[i][j][q];
}
}
fprintf(stderr, "\r%d", q);
}
elaAv /= bCnt;
for(int i = 0; i < bCnt; i++){
vector<double> predictArgsV;
predictArgsV.push_back(bCoordX);
predictArgsV.push_back(bCoordY);
predictArgsV.push_back(elaAv);
predictArgsV.push_back(bGhosts[i][1][qNorm]);
bPredict[i] = predictF(imgG, predictArgsV);
if(bPredict[i] == 1)
bCntR--;
}
for(int i = 0; i < bCnt; i++)
for(int j = 0; j < w * w; j++)
bGhosts[i][j] = nrm(bGhosts[i][j]);
if(1){
for(int i = 0; i < bCnt; i++){
bInv[i].resize(101);
if(bPredict[i] == 1)
continue;
vector<double> m1V(101), m2V(101);
for(int q = qMin; q <= qMax; q++){
for(int j = 1; j < w * w; j++) // -- j = 1
m1V[q] += bGhosts[i][j][q];
m1V[q] /= w * w - 1;
}
for(int q = qMin; q <= qMax; q++){
for(int j = 1; j < w * w; j++) // -- j = 1
m2V[q] += bGhosts[i][j][q] * bGhosts[i][j][q];
m2V[q] = sqrt(m2V[q] / (w * w - 1) - m1V[q] * m1V[q]);
}
for(int q = qMin; q <= qMax; q++){
double maxD = -1, minD = 2;
for(int j = 1; j < w * w; j++){ // -- j = 1
if(bGhosts[i][j][q] < minD)
minD = bGhosts[i][j][q];
if(bGhosts[i][j][q] > maxD)
maxD = bGhosts[i][j][q];
}
double dlt = max((maxD - minD) / 3.0, 0.01);
double dlt1 = max((maxD - minD) / 6.0, 0.004);
if((bGhosts[i][0][q] < minD - dlt || bGhosts[i][0][q] > maxD + dlt)/* && q <= qMax - 3 && q >= qMin + 3*/){
bInv[i][q].push_back(1);
}else
bInv[i][q].push_back(0);
if((bGhosts[i][0][q] < minD - dlt1 || bGhosts[i][0][q] > maxD + dlt1)/* && q <= qMax - 3 && q >= qMin + 3*/){
bInv[i][q].push_back(1);
}else
bInv[i][q].push_back(0);
}
}
vector<double> qMask(101);
int qMaskCnt = 0;
for(int q = qMin; q <= qMax; q++){
for(int i = 0; i < bCnt; i++){
if(bPredict[i] == 1)
continue;
if(bInv[i][q][0] == 1)
qMask[q]++;
}
if(qMask[q] / bCntR > 0.5){
qMask[q] = 1;
qMaskCnt++;
}else
qMask[q] = 0;
cerr << qMask[q];
}
cerr << endl;
if(qMaskCnt < 3){
//cerr << "don't want to analyse" << endl;
//throw "[ghosts] don't want to analyse";
return -1;
}
for(int i = 0; i < bCnt; i++){
int clr;
if(bPredict[i] == 1)
clr = 0;
else{
int tmpI2 = 0;
for(int q = qMin; q <= qMax; q++)
if(qMask[q] == 1 && bInv[i][q][1] == 1){
tmpI2++;
}
if((tmpI2 <= 0 && qMaskCnt >= 3) ||
(tmpI2 <= 1 && qMaskCnt >= 4) ||
(tmpI2 <= 2 && qMaskCnt >= 5) ||
(tmpI2 <= 3 && qMaskCnt >= 8))
tmpI2 = 0;
clr = (tmpI2 == 0);
}
if(clr){
res++;
for(int ix = bCoordX; ix < bCoordX + bSize; ix++)
for(int iy = bCoordY; iy < bCoordY + bSize; iy++)
img.at<Vec3b>(iy, ix)[2] = 255;
}
}
if(outFile)
cv_imwrite(outFile, img);
}
return res;
}
void TimeIndependentSolver::inverseIteration(double coordStep, int gridColumns, double eigenValue, Task *task, double threshold, double *output)
{
int rank, commSize;
MPI_Comm_rank(MPI_COMM_WORLD, &rank);
MPI_Comm_size(MPI_COMM_WORLD, &commSize);
int n = gridColumns / commSize;
int additionalElementsCount = 0;
if (rank == commSize - 1) {
additionalElementsCount = gridColumns % commSize;
}
int totalCount = n + additionalElementsCount;
double * eigenVector = new double[totalCount];
double * calcVector = new double[totalCount];
double * diagElements = new double[totalCount];
double * f = new double[totalCount];
double * c = new double[totalCount];
#pragma omp parallel for
for (int i = 0; i < totalCount; ++i) {
diagElements[i] = getDiagValue(task, rank * n + i, coordStep) - eigenValue;
}
calcFirstApproximation(eigenVector, diagElements, coordStep, totalCount, n, task);
Logger::verbose("First approximation calculated");
for (int iteration = 1;;++iteration) {
Logger::debug("Start iteration #" + std::to_string(iteration));
memcpy(c, diagElements, totalCount * sizeof(double));
#pragma omp parallel for
for (int i = 0; i < totalCount; ++i) {
f[i] = eigenVector[i] / eigenValue;
}
prepareTDA(totalCount, f, c, rank, commSize);
Logger::debug("PrepareTDA success");
calcNewVector(c, f, calcVector, totalCount, rank, commSize);
Logger::debug("Calc new vector success");
double diff = calcDiff(totalCount, eigenVector, calcVector);
Logger::debug("Diff calculated: " + std::to_string(diff / threshold));
if (diff < threshold) {
Logger::verbose("Diff: " + std::to_string(diff / threshold));
Logger::verbose("Threshold: " + std::to_string(threshold / threshold));
Logger::verbose("Iteration: " + std::to_string(iteration));
break;
}
double *qwe = eigenVector;
eigenVector = calcVector;
calcVector = qwe;
}
MPI_Gather(eigenVector, n, MPI_DOUBLE, output, n, MPI_DOUBLE, 0, MPI_COMM_WORLD);
delete f;
delete c;
delete calcVector;
delete eigenVector;
delete diagElements;
}
static void addMeasurement(Packet_t *packet)
{
xvector[vectorPos] = packet->accX;
yvector[vectorPos] = packet->accY;
zvector[vectorPos] = packet->accZ;
vectorPos++;
if (vectorPos < NUM_SAMPLES) return;
vectorPos = 0;
float s = stdev(xvector) + stdev(yvector) + stdev(zvector);
// PRINTF("stdev = %u\n", (uint16_t) s);
float accelVector[3] = {
average(xvector) - groundVector[0],
average(yvector) - groundVector[1],
average(zvector) - groundVector[2]
};
// PRINTF("accel=(%d %d %d)\n", (int)accelVector[0], (int)accelVector[1], (int)accelVector[2]);
bool nowFwd, nowBack;
float accLen = vlength(accelVector);
if (accLen < ONE_G / 10) {
nowBack = nowFwd = false;
} else {
normalizeQuick(accelVector, accLen);
nowFwd = sameDirection(fwdVector, accelVector);
nowBack = inverseDirection(fwdVector, accelVector);
}
int now = nowFwd ? 1 : (nowBack ? -1 : 0);
bool diffFromPrevious;
static bool notFirstTime;
if (notFirstTime) {
// float difference = (calcDiff(xvector, prevxvector)
// + calcDiff(yvector, prevyvector)
// + calcDiff(zvector, prevzvector)) / 3.0;
float difference = calcDiff(xvector, prevavgxvector)
+ calcDiff(yvector, prevavgyvector)
+ calcDiff(zvector, prevavgzvector);
// PRINTF("difference=%d\n", (int)difference);
diffFromPrevious = (difference >= 30 * (ONE_G / 10));
} else {
notFirstTime = true;
diffFromPrevious = false;
}
bool pastBack = false;
bool pastFwd = false;
if (past[0] + past[1] + past[2] >= 1) {
pastFwd = true;
} else if (past[0] + past[1] + past[2] <= -1) {
pastBack = true;
}
past[0] = past[1];
past[1] = past[2];
past[2] = now;
bool wasMoving = !bayesStandingMode;
#if 0
PRINTF("SSD \t%d\n", (int)(s >= THRESH_LOW));
PRINTF("MSD \t%d\n", (int)(s >= THRESH_MEDIUM));
PRINTF("LSD \t%d\n" , (int)(s > THRESH_HIGH));
PRINTF("Accelerating\t%d\n", (int)(nowFwd));
PRINTF("PastAccel \t%d\n", (int)(pastFwd));
PRINTF("PastBrake \t%d\n", (int)(pastBack));
PRINTF("WasMoving \t%d\n", (int)(wasMoving));
PRINTF("Diff \t%d\n", (int)(diffFromPrevious));
#endif
calcNewProb(s, wasMoving, pastBack, pastFwd, nowFwd, diffFromPrevious);
}