vector<Plate> DetectRegions::segment(Mat input){
vector<Plate> output;
//convert image to gray
Mat img_gray; //= *new Mat(input.size().width,input.size().height, CV_8UC1);
cvtColor(input, img_gray, CV_BGR2GRAY);
blur(img_gray, img_gray, Size(5,5));
//Finde vertical lines. Car plates have high density of vertical lines
Mat img_sobel;
Sobel(img_gray, img_sobel, CV_8U, 1, 0, 3, 1, 0, BORDER_DEFAULT);
if(showSteps)
imshow("Sobel", img_sobel);
//threshold image
Mat img_threshold;
threshold(img_sobel, img_threshold, 0, 255, CV_THRESH_OTSU+CV_THRESH_BINARY);
if(showSteps)
imshow("Threshold", img_threshold);
//Morphplogic operation close
Mat element = getStructuringElement(MORPH_RECT, Size(17, 3) );
morphologyEx(img_threshold, img_threshold, CV_MOP_CLOSE, element);
if(showSteps)
imshow("Close", img_threshold);
//Find contours of possibles plates
vector< vector< Point> > contours;
findContours(img_threshold,
contours, // a vector of contours
CV_RETR_EXTERNAL, // retrieve the external contours
CV_CHAIN_APPROX_NONE); // all pixels of each contours
//Start to iterate to each contour founded
vector<vector<Point> >::iterator itc= contours.begin();
vector<RotatedRect> rects;
//Remove patch that are no inside limits of aspect ratio and area.
while (itc!=contours.end()) {
//Create bounding rect of object
RotatedRect mr= minAreaRect(Mat(*itc));
if( !verifySizes(mr)){
itc= contours.erase(itc);
}else{
++itc;
rects.push_back(mr);
}
}
// Draw blue contours on a white image
cv::Mat result;
input.copyTo(result);
cv::drawContours(result,contours,
-1, // draw all contours
cv::Scalar(255,0,0), // in blue
1); // with a thickness of 1
for(int i=0; i< rects.size(); i++){
//For better rect cropping for each posible box
//Make floodfill algorithm because the plate has white background
//And then we can retrieve more clearly the contour box
circle(result, rects[i].center, 3, Scalar(0,255,0), -1);
//get the min size between width and height
float minSize=(rects[i].size.width < rects[i].size.height)?rects[i].size.width:rects[i].size.height;
minSize=minSize-minSize*0.5;
//initialize rand and get 5 points around center for floodfill algorithm
srand ( time(NULL) );
//Initialize floodfill parameters and variables
Mat mask;
mask.create(input.rows + 2, input.cols + 2, CV_8UC1);
mask= Scalar::all(0);
int loDiff = 30;
int upDiff = 30;
int connectivity = 4;
int newMaskVal = 255;
int NumSeeds = 10;
Rect ccomp;
int flags = connectivity + (newMaskVal << 8 ) + CV_FLOODFILL_FIXED_RANGE + CV_FLOODFILL_MASK_ONLY;
for(int j=0; j<NumSeeds; j++){
Point seed;
seed.x=rects[i].center.x+rand()%(int)minSize-(minSize/2);
seed.y=rects[i].center.y+rand()%(int)minSize-(minSize/2);
circle(result, seed, 1, Scalar(0,255,255), -1);
int area = floodFill(input, mask, seed, Scalar(255,0,0), &ccomp, Scalar(loDiff, loDiff, loDiff), Scalar(upDiff, upDiff, upDiff), flags);
}
if(showSteps)
imshow("MASK", mask);
//cvWaitKey(0);
//Check new floodfill mask match for a correct patch.
//Get all points detected for get Minimal rotated Rect
vector<Point> pointsInterest;
Mat_<uchar>::iterator itMask= mask.begin<uchar>();
Mat_<uchar>::iterator end= mask.end<uchar>();
for( ; itMask!=end; ++itMask)
if(*itMask==255)
pointsInterest.push_back(itMask.pos());
RotatedRect minRect = minAreaRect(pointsInterest);
if(verifySizes(minRect)){
// rotated rectangle drawing
Point2f rect_points[4]; minRect.points( rect_points );
for( int j = 0; j < 4; j++ )
line( result, rect_points[j], rect_points[(j+1)%4], Scalar(0,0,255), 1, 8 );
//Get rotation matrix
float r= (float)minRect.size.width / (float)minRect.size.height;
float angle=minRect.angle;
if(r<1)
angle=90+angle;
Mat rotmat= getRotationMatrix2D(minRect.center, angle,1);
//Create and rotate image
Mat img_rotated;
warpAffine(input, img_rotated, rotmat, input.size(), CV_INTER_CUBIC);
//Crop image
Size rect_size=minRect.size;
if(r < 1)
swap(rect_size.width, rect_size.height);
Mat img_crop;
getRectSubPix(img_rotated, rect_size, minRect.center, img_crop);
Mat resultResized;
resultResized.create(33,144, CV_8UC3);
resize(img_crop, resultResized, resultResized.size(), 0, 0, INTER_CUBIC);
//Equalize croped image
Mat grayResult;
cvtColor(resultResized, grayResult, CV_BGR2GRAY);
blur(grayResult, grayResult, Size(3,3));
grayResult=histeq(grayResult);
if(saveRegions){
stringstream ss(stringstream::in | stringstream::out);
ss << "tmp/" << filename << "_" << i << ".jpg";
imwrite(ss.str(), grayResult);
}
output.push_back(Plate(grayResult,minRect.boundingRect()));
}
}
if(showSteps)
imshow("Contours", result);
return output;
}
void ClothingSearcher::getTheMaskOfCloth(const Mat &image, Mat &mask,
const std::vector<int> floodfill_thresholds )
{
if( image.channels() == 1 )
return;
//get the mask of cloth region using floodfill algorithm
Mat edges;
computeEdgeMap( image, edges );
//to lower down the complexity, resize the original image to smaller one
Mat small_image;
Size small_size( image.cols, image.rows );
if( image.cols > 320 ){
float scale = image.cols / 320;
small_size.width = image.cols / scale;
small_size.height = image.rows / scale;
cv::resize( image, small_image, small_size );
}
else
small_image = image.clone();
//convert to yuv color space
Mat yuv = Mat( small_size, CV_8UC3 );
cvtColor( small_image, yuv, CV_BGR2RGB );
//the mask used in floodfill should be 2 pixels widther and higher than the image
int sw = small_size.width;
int sh = small_size.height;
Mat mask_plus_border;
mask_plus_border = Mat::zeros( sh + 2, sw + 2, CV_8UC1 );
mask = mask_plus_border( cv::Rect( 1, 1, sw, sh ) );
cv::resize( edges, mask, small_size );
closeOperation( mask );
cv::Rect rect;
prepareSeedsRegionForFloodfill( small_image, rect );
rectangle( small_image, rect, Scalar( 0, 255, 0 ) );
//imshow( "tets", small_image );
waitKey(0);
Scalar lowerDiff = Scalar( floodfill_thresholds[0], floodfill_thresholds[0], floodfill_thresholds[0] );
Scalar upperDiff = Scalar( floodfill_thresholds[0], floodfill_thresholds[0], floodfill_thresholds[0]);
const int CONNECTED_COMPONENTS = 4;
const int flags = CONNECTED_COMPONENTS | FLOODFILL_FIXED_RANGE | FLOODFILL_MASK_ONLY;
Mat edge_mask = mask.clone();
const int X_POINTS = 8;
const int Y_POINTS = 8;
const int X_STEP = rect.width / X_POINTS;
const int Y_STEP = rect.height / Y_POINTS;
for( int i = rect.x + X_STEP; i < (int)(rect.x + rect.width ); i += X_STEP ){
for( int j = rect.y + Y_STEP; j < (int)(rect.y + rect.height ); j += Y_STEP ){
circle( small_image, cv::Point( i, j), 3, Scalar( 0, 0, 255 ) );
floodFill( yuv, mask_plus_border, cv::Point( i, j), Scalar(), NULL,
lowerDiff, upperDiff, flags );
}
}
//imshow( "mask", small_image );
waitKey(0);
mask -= edge_mask;
}
/*******************************************************************************
* Function: extractFGTargets
* Description: extract FG targets with given conditions and return objects
* Arguments:
inImg - input image
fgImg - output FG mask image
seLength - length of structuring elements (opening)
threshVal - threshold value for converting to binary image
minArea - minimum area of FG targets
maxArea - maximum area of FG targets
minAspRatio - minimum aspect ratio of FG targets
maxAspRatio - maximum aspect ratio of FG targets
* Returns: vector<FGObject>* - all extracted FG targets
* Comments:
* Revision:
*******************************************************************************/
vector<FGObject>*
FGExtraction::extractFGTargets(InputArray inImg, OutputArray fgImg, int seLength, int threshVal,
double minArea, double maxArea,
double minAspRatio, double maxAspRatio)
{
double theta = 0.4;
if(!inImg.obj) return NULL;
_inImg = inImg.getMat();
this->init();
//showImage("inImg", _inImg);
// background subtraction by opening
int err = subtractBGOpenDiagonal(inImg, _bgsImg, threshVal, seLength);
if (err>0) {
vector<FGObject>* fgObjects = new vector<FGObject>;
return fgObjects;
}
//subtractBGMedian(inImg.getMat(), bgSubImg, threshVal, seLength);
//showImage("inImg", _inImg, 0, 1);
//showImage("bgSub", _bgsImg);
// get the contour
vector<vector<Point>> contours = extractContours(_bgsImg);
//cout<<contours.size()<<endl;
// double local thresholding
// histogram backprojection
Mat mask = Mat::zeros(_bgsImg.size(), CV_8U);
vector<int> areas(contours.size());
int cnt = 0;
int argMax = 0;
int max_area = 0;
for(vector<vector<Point> >::const_iterator it = contours.begin(); it != contours.end(); ++it){
Rect uprightBox = boundingRect(*it);
areas[cnt] = uprightBox.height*uprightBox.width;
if (areas[cnt]>max_area) {
max_area = areas[cnt];
argMax = cnt;
}
cnt++;
}
//showImage("inImg", _inImg, 0, 1);
vector<Point> largestContour = contours[argMax]; //***** only use the largest contour
RotatedRect orientedBox = orientedBoundingBox(largestContour);
orientedBox.size.width *= 1.5;
orientedBox.size.height *= 1.5;
ellipse(mask, orientedBox, Scalar(255), -1);
//Rect tempRect = boundingRect(largestContour);
//Mat tempImg = mask(tempRect);
//imshow("tempImg", tempImg);
//imshow("mask", mask);
//waitKey(0);
// double local thresholding
double percentage = 0.8;
doubleThresholdByValue(percentage, mask);
/*finish = clock();
duration = (double)(finish - start) / (double)CLOCKS_PER_SEC;
cout << duration << " sec" << endl;
start = clock();*/
// remove noise by a median filter
medianBlur(_fgHighImg, _fgHighImg, 3);
medianBlur(_fgLowImg, _fgLowImg, 3);
//showImage("_fgHighImg", _fgHighImg);
//showImage("_fgLowImg", _fgLowImg);
/*finish = clock();
duration = (double)(finish - start) / (double)CLOCKS_PER_SEC;
cout << duration << " sec" << endl;
start = clock();*/
// merge two masks using histogram backprojection
//showImage("_fgImg", _fgImg);
//showImage("mask", mask);
updateByHistBackproject(theta, mask);
ellipse(mask, orientedBox, Scalar(0), -1);
ellipse(_fgHighImg, orientedBox, Scalar(0), -1);
ellipse(_fgLowImg, orientedBox, Scalar(0), -1);
//}
// thresholding by area and variance
#ifdef IMAGE_DOWNSAMPLING
int dilateSESize = 3;
int erodeSESize = 3;
int varThresh = 30;
#else
int dilateSESize = 7;
int erodeSESize = 7;
int varThresh = 30;
#endif
//showImage("fg high", _fgHighImg, 0, 1);
//showImage("fg low", _fgLowImg, 0, 1);
//showImage("after histbp", _fgImg, 0);
thresholdByAreaRatioVar(minArea, maxArea, dilateSESize, erodeSESize, minAspRatio, maxAspRatio, varThresh);
//showImage("after area threshold", _fgImg, 0);
// post-processing
postProcessing(_fgImg, _fgImg);
//imshow("_fgImg",_fgImg);
//waitKey(0);
// fill the holes of the fgImg
_fgImg.copyTo(fgImg);
floodFill(fgImg, cv::Point(0,0), Scalar(255));
//imshow("fgImg",fgImg);
//waitKey(0);
bitwise_not(fgImg, fgImg);
bitwise_or(fgImg, _fgImg, _fgImg);
//imshow("inImg", inImg);
//imshow("_fgImg",_fgImg);
//waitKey(0);
// opening
RotatedRect rotatedR = fitEllipse(Mat(largestContour));
float objHeight = min(rotatedR.size.height,rotatedR.size.width);
int seSize = int(objHeight/10.0+0.5);
Mat se = getStructuringElement(MORPH_ELLIPSE, Size(seSize, seSize)); //***** choose different size according to object height
morphologyEx(_fgImg, _fgImg, MORPH_OPEN, se);
//imshow("_fgImg",_fgImg);
//waitKey(0);
// close
morphologyEx(_fgImg, _fgImg, MORPH_CLOSE, se);
// timer
/*clock_t start, finish;
double duration = 0.0;
start = clock();
finish = clock();
duration = (double)(finish - start) / (double)CLOCKS_PER_SEC;
cout << duration << " sec" << endl;*/
thresholdByAreaRatioVar(0.5*minArea, maxArea, 1, 1, minAspRatio, maxAspRatio, 30);
// push targets into our vector
//Mat largeInImg;
#ifdef IMAGE_DOWNSAMPLING
resize(_fgImg, _fgImg, Size(), 2, 2, INTER_LINEAR);
resize(_inImg, largeInImg, Size(), 2, 2, INTER_LINEAR);
#endif
//tempImg = _fgImg.clone();
//findContours(tempImg, contours, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_SIMPLE, Point(0, 0));
//tempImg.release();
//imshow("_fgImg",_fgImg);
//waitKey(0);
contours = extractContours(_fgImg);
vector<FGObject>* fgObjects = new vector<FGObject>;
//Mat mask8U = Mat::zeros(largeInImg.size(), CV_8U);
for (size_t i = 0; i < contours.size(); i++){
double area = contourArea(contours[i]);
RotatedRect orientedRect = orientedBoundingBox(contours[i]);
Point2f points[4];
orientedRect.points(points);
/*
orientedRect.size.width *= 1.5;
orientedRect.size.height *= 1.5;
ellipse(mask8U, orientedRect, Scalar(255), -1);
int channels[] = {0};
int nbins = 16;
const int histSize[] = {nbins};
float range[] = {0, 255};
const float* ranges[] = {range};
Mat hist;
cv::calcHist(&largeInImg, 1, channels, mask8U, hist, 1, histSize, ranges);
*/
// push targets into our vector
FGObject* obj = new FGObject;
//obj->histogram = hist;
obj->setObjectProperties(area, orientedRect.angle, contours[i], points, SOURCE_UNRECTIFIED);
if(obj->isPartialOut(_fgImg.cols, _fgImg.rows) == false){
fgObjects->push_back(*obj);
}
delete obj;
//ellipse(mask8U, orientedRect, Scalar(0), -1);
}
// eliminate artifacts with width of 1 at the border...
rectangle(_fgImg, Point(0,0), Point(_fgImg.cols-1, _fgImg.rows-1), Scalar(0));
fgImg.getMatRef() = _fgImg.clone();
return fgObjects;
}
Mat& CHandGestureRecognitionSystemDlg::FeatureDetect(const Mat& image_input, Mat& image_output)
{
image_input.copyTo(image_output);
cvtColor(image_output, image_output, CV_BGR2GRAY);
#ifdef _DEBUG
TRACE("gray image channels = %d\n", image_output.channels());
#endif
// morphology
Mat kernel = Mat(3,3,CV_8UC1, Scalar(255));
morphologyEx(image_output, image_output, MORPH_OPEN, kernel);
// floodfill
int num_floodfill = 0;
int area_max = 0;
int value_max = 0;
for (int i = 0; i < image_output.rows; i++) {
unsigned char* p_out = image_output.ptr<uchar>(i);
for (int j = 0; j < image_output.cols; j++) {
if (*(p_out + j) == 255) {
num_floodfill++;
Scalar new_val = Scalar(num_floodfill);
Point seed = Point(j, i);
CRect rect;
int area = floodFill(image_output,seed, new_val);
if (area > area_max) {
area_max = area;
value_max = num_floodfill;
}
}
}
}
// max area
int area_left = image_output.cols;
int area_right = 0;
int area_top = image_output.rows;
int area_buttom = 0;
for (int i = 0; i < image_output.rows; i++) {
unsigned char* p_out = image_output.ptr<uchar>(i);
for (int j = 0; j < image_output.cols; j++) {
if (*(p_out + j) == value_max) {
*(p_out + j) = 255;
if (area_left > j) area_left = j;
if (area_right < j) area_right = j;
if (area_top > i) area_top = i;
if (area_buttom < i) area_buttom = i;
} else {
*(p_out + j) = 0;
}
}
}
#ifdef _DEBUG
TRACE("area_left = %d\n", area_left);
TRACE("area_right = %d\n", area_right);
TRACE("area_top = %d\n", area_top);
TRACE("area_buttom = %d\n", area_buttom);
#endif
// rectangle
rectangle(image_output, Point(area_left, area_top), Point(area_right, area_buttom), Scalar(255), 5);
// moment
Moments moment = moments(image_output);
int center_x = moment.m10 / moment.m00;
int center_y = moment.m01 / moment.m00;
point_end = Point(center_x, center_y);
circle(image_output, point_end, 10, Scalar(255), 5);
GetVector(point_begin, point_end);
if (vector_length >= 20 || point_begin == Point(image_width / 2, image_height / 2)) {
point_begin = point_end;
}
#ifdef _DEBUG
TRACE("vector_length = %f\n", vector_length);
TRACE("vector_angle = %f\n", vector_angle);
#endif
return image_output;
}
void GameEngine::generateLevel() {
//Clear out the last level
for (vector<Actor*>::iterator it = monsters.begin(); it != monsters.end(); ++it)
delete (*it);
monsters.clear();
for (vector<Pickup*>::iterator it = pickups.begin(); it != pickups.end(); ++it)
delete (*it);
pickups.clear();
map.clear();
playableMap.clear();
//Set tile graphics for curr floor
if (currLevel == 1) {
wallTile = 0x103;
floorTile = 0x100;
}
else if (currLevel > 1) {
wallTile = 0x14D;
floorTile = 0x13E;
delete boss;
}
//Initialize the outer map vector
for (int i = 0; i < worldSize; i++) {
vector<Cell> v;
map.push_back(v);
}
//Generate the map boundaries
lib.loop_portion(Point(0, 0), Point(worldSize, worldSize), [&](Point p) {
Cell c(p, 2, wallTile, 0);
map[p.x()].push_back(c);
});
//Generate the random rooms
for (int i = 0; i < rand() % 130 + 100; i++) {
Point pStart((rand() % 55 + 1), (rand() % 55 + 1));
Point pEnd(pStart.x() + (rand() % 6 + 3), pStart.y() + (rand() % 6 + 3));
fillBox(pStart, pEnd);
}
//Flood fill to connect the world
int currZone = 0;
vector<int> zoneSize;
lib.loop_portion(Point(0, 0), Point(worldSize, worldSize), [&](Point p) {
if (map[p.x()][p.y()].getCellType() != 2 && map[p.x()][p.y()].getZone() == 0) {
currZone++;
int size = floodFill(map[p.x()][p.y()].getLoc(), currZone, 0);
zoneSize.push_back(size);
}
});
//Get biggest zone in array
int max = zoneSize[0];
int largestZone = 0;
for (unsigned int i = 1; i < zoneSize.size(); i++) {
if (zoneSize[i] > max) {
largestZone = i;
max = zoneSize[i];
}
}
largestZone++; //Offset for vector index
//Get rid of everything but largest zone
int end = worldSize - 1;
lib.loop_portion(Point(0, 0), Point(worldSize, worldSize), [&](Point p) {
Cell& c = map[p.x()][p.y()];
if (c.getZone() != largestZone) {
if ((p.x() + 1 < end && map[p.x() + 1][p.y()].getZone() == largestZone) ||
(p.x() - 1 > 0 && map[p.x() - 1][p.y()].getZone() == largestZone) ||
(p.y() + 1 < end && map[p.x()][p.y() + 1].getZone() == largestZone) ||
(p.y() - 1 > 0 && map[p.x()][p.y() - 1].getZone() == largestZone) ||
(p.x() - 1 > 0 && p.y() - 1 > 0 && map[p.x() - 1][p.y() - 1].getZone() == largestZone) ||
(p.x() - 1 > 0 && p.y() + 1 < end && map[p.x() - 1][p.y() + 1].getZone() == largestZone) ||
(p.x() + 1 < end && p.y() - 1 > 0 && map[p.x() + 1][p.y() - 1].getZone() == largestZone) ||
(p.x() + 1 < end && p.y() + 1 < end && map[p.x() + 1][p.y() + 1].getZone() == largestZone)) {
c.setTile(wallTile);
c.setTileType(2);
}
else {
c.setTile(0);
c.setTileType(2);
}
}
else if (c.getLoc().x() == end)
c.setTile(0);
});
//Set player starting position
lib.loop_portion(Point(0, 0), Point(worldSize - 1, worldSize - 1), [&](Point p) {
if (map[p.x()][p.y()].getZone() != 0 && map[p.x()][p.y()].getCellType() != 2)
playableMap.push_back(map[p.x()][p.y()].getLoc());
});
//Add monsters
for (unsigned int i = 0; i < playableMap.size(); i++) {
int chance = rand() % 30;
if (chance == 15) {
//Make the monster
ActorDef def = pickfromtable<ActorDef>(actordefs);
monsters.push_back(new Actor(def, playableMap[i], false, false));
map[playableMap[i].x()][playableMap[i].y()].setActor(monsters.back());
//Give chance to spawn with item
chance = rand() % 5 + 1; //Give 10% chance to spawn
if (chance == 3) {
PickupDef def = pickfromtable<PickupDef>(pickupdefs);
pickups.push_back(new Pickup(def, playableMap[i]));
map[playableMap[i].x()][playableMap[i].y()].setPickup(pickups.back());
}
}
}
//Set starting pos
Point heroLoc = getRandomLoc();
screenOrientation = heroLoc;
hero->setLoc(screenOrientation);
//Add stairs, shop, boss
stairLoc = addToRandomLoc(Cell(Point(), 5, 0x1A0, -1));
shop = Shop(addToRandomLoc(Cell(Point(), 6, 0x0C0, -1)), currLevel, pickupdefs, &lib, hero, &log, &invLog);
bossLoc = addToRandomLoc(Cell(Point(), 7, 0x1AB, -1));
bossInRoomLoc = Point(5, 2);
//Instantiate the boss map
for (int i = 0; i < bossMapSize; i++) {
vector<Cell> row;
for (int j = 0; j < bossMapSize; j++) {
if (i == 0 || i == bossMapSize - 1 || j == 0 || j == bossMapSize - 1)
row.push_back(Cell(Point(i, j), 2, 0x14B, 1));
else
row.push_back(Cell(Point(i, j), 1, 0x122, 1));
}
bossMap.push_back(row);
}
//Add the boss to its location in the boss map
int which = rand() % bossdefs.size();
boss = new Actor(bossdefs[which], bossInRoomLoc, false, true);
bossMap[bossInRoomLoc.x()][bossInRoomLoc.y()].setActor(boss);
}
int main()
{
int t, row, col, i, j, count = 0;
unsigned char **Room;
unsigned char temp;
FILE *fp;
fp = fopen("input.txt", "r");
if (fp == NULL) return 0; /* start FILE IO */
fscanf(fp, "%d", &t); /* read Data Number */
while (t--)
{
fscanf(fp, "%d %d", &col, &row); /* read Data */
Room = (unsigned char**)malloc(sizeof(unsigned char*)*row); /* read Room data */
for (i = 0; i < row; i++)
Room[i] = (unsigned char*)malloc(sizeof(unsigned char)*(col));
for (i = 0; i < row; i++)
{
for (j = 0; j < col; j++)
{
fscanf(fp, "%c", &temp);
while ((temp != '.') && (temp != '+')) fscanf(fp, "%c", &temp);
Room[i][j] = temp;
}
}
for (i = 1; i < row-1; i++) for (j = 0; j < col; j++) if (Room[i][j] == '.') count += floodFill(Room, i, j, '.', '+', &count); /* figure out result */
printf("%d\n", count); /* print output */
Sorting(roomSIZE, 0, count);
for (i = 0; i < count; i++)
printf("%d ", roomSIZE[i]);
printf("\n");
for (i = 0; i < row; i++) /* initialize Room memory */
{
free(Room[i]);
Room[i] = NULL;
}
free(Room);
Room = NULL;
for (i = 0; i < count; i++) roomSIZE[i] = 0; /* initialize roomsize */
count = 0; /* initialize room counter */
}
fclose(fp); /* close FILE IO */
return 1;
}
void colorFill( int x, int y, COLOR fillColor )
{
//boundaryFill(x, y, fillColor);
floodFill(x, y, fillColor);
}
static void gpath_draw_filled_custom(GContext* ctx, GPath *path, GColor8 fill_color){
if(path->num_points == 0)
return;
GPoint offset = path->offset;
int32_t rotation = path->rotation;
int32_t s = sin_lookup(rotation);
int32_t c = cos_lookup(rotation);
// Rotate each point of the gpath and memorize the min/max
GPoint* points_rot = malloc(sizeof(GPoint) * path->num_points);
GPoint top_right = (GPoint){(1 << 15)-1,(1 << 15)-1};
GPoint bottom_left= (GPoint){-(1 << 15),-(1 << 15)};
for(uint32_t i=0; i<path->num_points; i++){
points_rot[i].x = (path->points[i].x * c - path->points[i].y * s) / TRIG_MAX_RATIO + offset.x;
points_rot[i].y = (path->points[i].x * s + path->points[i].y * c) / TRIG_MAX_RATIO + offset.y;
if(points_rot[i].x > bottom_left.x)
bottom_left.x = points_rot[i].x;
if(points_rot[i].x < top_right.x)
top_right.x = points_rot[i].x;
if(points_rot[i].y > bottom_left.y)
bottom_left.y = points_rot[i].y;
if(points_rot[i].y < top_right.y)
top_right.y = points_rot[i].y;
}
// Create an array bitmap pebble v2 style (1 bit equals 1 pixel)
int32_t bytes_per_row = (bottom_left.x - top_right.x + 1) / 8 + ((bottom_left.x - top_right.x + 1) % 8 == 0 ? 0 : 1);
int32_t h = bottom_left.y - top_right.y + 1;
uint8_t* pixels = malloc(bytes_per_row * h);
memset(pixels, 0, bytes_per_row * h);
// And draw the outline path in this 1 bit image
GPoint prev_p = points_rot[path->num_points - 1];
GPoint p;
for(uint32_t i=0; i<path->num_points; i++){
p = points_rot[i];
bmpDrawLine(pixels, bytes_per_row, prev_p.x - top_right.x, prev_p.y - top_right.y, p.x - top_right.x, p.y - top_right.y);
prev_p = p;
}
free(points_rot);
// Compute the starting point for the flow fill algorithm
// TODO tobe improved
GPoint start;
start.x = (points_rot[0].x + points_rot[1].x) / 2;
start.y = (points_rot[0].y + points_rot[1].y) / 2;
if(points_rot[0].x < points_rot[1].x){
if(points_rot[0].y < points_rot[1].y){
start.x--;
start.y++;
}
else {
start.x++;
start.y++;
}
}
else {
if(points_rot[0].y < points_rot[1].y){
start.x--;
start.y--;
}
else {
start.x++;
start.y--;
}
}
// Capture the frame buffer
GBitmap* bitmap = graphics_capture_frame_buffer(ctx);
// flood fill the gpath
floodFill(bitmap, pixels, bytes_per_row, start, top_right, fill_color);
// Release the frame buffer
graphics_release_frame_buffer(ctx, bitmap);
//Release the working variables
free(pixels);
}
void solveMaze()
{
//Reset maze to 0
initializeMaze(&maze);
//We Know at the starting point, there's something behind us
setN(&maze[0][0], 1);
mouse.direction.x = 0;
mouse.direction.y = -1;
mouse.x = 0;
mouse.y = 0;
//Disable the mouse for now
enableDrive(0);
turnOnTimers(0, 0);
int areWeSearching = UserInterfaceIntro();
//Does the user want to skip the search phase and load a maze from EEPROM
if(areWeSearching)
{
/* SEARCH MAZE */
for(int i = 0; i < 10; i++)
{
turnOnLeds(7);
_delay_ms(10);
turnOnLeds(0);
_delay_ms(90);
}
//Init Mouse
enableDrive(1);
turnOnTimers(1, 1);
setDirection(0, 0);
//Update Sensors
updateSensors();
updateSensors();
updateWalls();
//Go Forward first block
mouse.IR_LONG_CHECK_LEFT = 2;
mouse.IR_LONG_CHECK_RIGHT = 2;
straight(480, 0, mouse.maxVelocity, mouse.maxVelocity, mouse.acceleration, mouse.deceleration);
mouse.x += mouse.direction.x;
mouse.y -= mouse.direction.y;
/* SEARCH */
InitialSearchRun();
//Search is Complete!
updateWalls();
/* TURN AROUND */
mouse.rightMotor.stepCount = mouse.leftMotor.stepCount = 0;
StopFromSpeedHalf();
mouse.rightMotor.stepCount = mouse.leftMotor.stepCount = 0;
moveBackwards();
//Save Maze to EEPROM
saveCurrentMaze();
writeMemByte(MOUSE_DIRECTION, firstTurn);
mouse.rightMotor.stepCount = mouse.leftMotor.stepCount = 0;
moveForwardHalf();
//Current Mouse Direction
int dirx = mouse.direction.x;
int diry = mouse.direction.y;
//Reverse and go back
mouse.direction.x = -dirx;
mouse.direction.y = -diry;
//Set Position to next block
mouse.x += mouse.direction.x;
mouse.y -= mouse.direction.y;
/* RETURN SEARCH*/
ReturnSearchRun();
//Turn Around
mouse.rightMotor.stepCount = mouse.leftMotor.stepCount = 0;
StopFromSpeedHalf();
mouse.rightMotor.stepCount = mouse.leftMotor.stepCount = 0;
moveBackwards();
//Save Maze to EEPROM
saveCurrentMaze();
writeMemByte(MOUSE_DIRECTION, firstTurn);
/* PICK UP AND PLACE MOUSE */
enableDrive(0);
waitForButtonPressed();
}
/* FAST RUN */
FastRun();
//Completed Search run, go back and search some more
turnAroundInPlace();
floodFill(maze, firstTurn, mouse.x, mouse.y);
/* RETURN */
ReturnSearchRun();
//Turn Around
mouse.rightMotor.stepCount = mouse.leftMotor.stepCount = 0;
StopFromSpeedHalf();
mouse.rightMotor.stepCount = mouse.leftMotor.stepCount = 0;
moveBackwards();
//Save Maze to EEPROM
saveCurrentMaze();
writeMemByte(MOUSE_DIRECTION, firstTurn);
stopMouse();
while(!isButtonPushed(1));
printMaze(maze);
}
bool Scraper::FindAllBMPs(const searchType type, HBITMAP hBmp, const double threshold, const int maxMatch, vector<MATCHPOINTS> &matches)
{
// Convert HBITMAP to Mat
unique_ptr<Gdiplus::Bitmap> pBitmap;
pBitmap.reset(Gdiplus::Bitmap::FromHBITMAP(hBmp, NULL));
Mat img = CGdiPlus::CopyBmpToMat(pBitmap.get());
pBitmap.reset();
cvtColor( img, img, CV_BGRA2BGR );
// Find right image group
imageType iType =
type==searchGoldStorage ? goldStorage :
type==searchElixStorage ? elixStorage :
type==searchDarkStorage ? darkStorage :
type==searchLootCollector ? collector :
type==searchLootBubble ? lootBubble :
type==searchDonateButton ? donateButton : (imageType) 0;
int iTypeIndex = -1;
for (int i = 0; i < (int) imageGroups.size(); i++)
if (imageGroups[i].iType == iType)
iTypeIndex = i;
if (iTypeIndex == -1)
return false;
// Scan through each Mat in this image group
int count = 0;
for (int i = 0; i < (int) imageGroups[iTypeIndex].mats.size(); i++)
{
// Get matches for this image
Mat result( FindMatch(img, imageGroups[iTypeIndex].mats[i]) );
// Parse through matches in result set
while (count < maxMatch)
{
double minVal, maxVal;
Point minLoc, maxLoc;
minMaxLoc(result, &minVal, &maxVal, &minLoc, &maxLoc);
// Fill haystack with pure green so we don't match this same location
rectangle(img, maxLoc, cv::Point(maxLoc.x + imageGroups[iTypeIndex].mats[i].cols, maxLoc.y + imageGroups[iTypeIndex].mats[i].rows), CV_RGB(0,255,0), 2);
// Fill results array with lo vals, so we don't match this same location
floodFill(result, maxLoc, 0, 0, Scalar(0.1), Scalar(1.0));
if (maxVal >= threshold && maxVal > 0)
{
// Check if this point is within 10 pixels of an existing match to avoid dupes
bool alreadyFound = false;
for (int k=0; k<count; k++)
{
if (DistanceBetweenTwoPoints((double) maxLoc.x, (double) maxLoc.y, (double) matches.at(k).x, (double) matches.at(k).y) < 10.0)
{
alreadyFound = true;
break;
}
}
// Add matched location to the vector
if (alreadyFound == false)
{
MATCHPOINTS match;
match.val = maxVal;
match.x = maxLoc.x;
match.y = maxLoc.y;
matches.push_back(match);
count++;
}
}
else
{
break;
}
}
if (count >= maxMatch)
break;
}
return true;
}
void Plane::fill() {
floodFill(center);
}
bool HandSplitterNew::compute(ForegroundExtractorNew& foreground_extractor, MotionProcessorNew& motion_processor, string name, bool visualize)
{
if (value_store.get_bool("first_pass", false) == false)
{
value_store.set_bool("first_pass", true);
algo_name += name;
}
bool algo_name_found = false;
for (String& algo_name_current : algo_name_vec_old)
if (algo_name_current == algo_name)
{
algo_name_found = true;
break;
}
LowPassFilter* low_pass_filter = value_store.get_low_pass_filter("low_pass_filter");
//------------------------------------------------------------------------------------------------------------------------
Mat image_find_contours = Mat::zeros(HEIGHT_SMALL, WIDTH_SMALL, CV_8UC1);
for (BlobNew& blob : *foreground_extractor.blob_detector.blobs)
if (blob.active)
blob.fill(image_find_contours, 254);
vector<vector<Point>> contours = legacyFindContours(image_find_contours);
if (contours.size() == 0)
return false;
int complexity = 0;
for (vector<Point>& contour : contours)
{
vector<Point> contour_approximated;
approxPolyDP(Mat(contour), contour_approximated, 10, false);
complexity += contour_approximated.size();
}
//------------------------------------------------------------------------------------------------------------------------
int x_min = foreground_extractor.x_min_result;
int x_max = foreground_extractor.x_max_result;
int y_min = foreground_extractor.y_min_result;
int y_max = foreground_extractor.y_max_result;
float x_seed_vec0_max = value_store.get_float("x_seed_vec0_max");
float x_seed_vec1_min = value_store.get_float("x_seed_vec1_min");
int intensity_array[WIDTH_SMALL] { 0 };
for (BlobNew& blob : *foreground_extractor.blob_detector.blobs)
if (blob.active)
for (Point& pt : blob.data)
++intensity_array[pt.x];
vector<Point> hist_pt_vec;
for (int i = 0; i < WIDTH_SMALL; ++i)
{
int j = intensity_array[i];
low_pass_filter->compute(j, 0.5, "histogram_j");
if (j < 10)
continue;
for (int j_current = 0; j_current < j; ++j_current)
hist_pt_vec.push_back(Point(i, j_current));
}
Point seed0 = Point(x_min, 0);
Point seed1 = Point(x_max, 0);
vector<Point> seed_vec0;
vector<Point> seed_vec1;
while (true)
{
seed_vec0.clear();
seed_vec1.clear();
for (Point& pt : hist_pt_vec)
{
float dist0 = get_distance(pt, seed0, false);
float dist1 = get_distance(pt, seed1, false);
if (dist0 < dist1)
seed_vec0.push_back(pt);
else
seed_vec1.push_back(pt);
}
if (seed_vec0.size() == 0 || seed_vec1.size() == 0)
break;
Point seed0_new = Point(0, 0);
for (Point& pt : seed_vec0)
{
seed0_new.x += pt.x;
seed0_new.y += pt.y;
}
seed0_new.x /= seed_vec0.size();
seed0_new.y /= seed_vec0.size();
Point seed1_new = Point(0, 0);
for (Point& pt : seed_vec1)
{
seed1_new.x += pt.x;
seed1_new.y += pt.y;
}
seed1_new.x /= seed_vec1.size();
seed1_new.y /= seed_vec1.size();
if (seed0 == seed0_new && seed1 == seed1_new)
break;
seed0 = seed0_new;
seed1 = seed1_new;
}
bool dual = false;
if (seed_vec0.size() > 0 && seed_vec1.size() > 0)
{
x_seed_vec0_max = seed_vec0[seed_vec0.size() - 1].x;
x_seed_vec1_min = seed_vec1[0].x;
low_pass_filter->compute_if_smaller(x_seed_vec0_max, 0.5, "x_seed_vec0_max");
low_pass_filter->compute_if_larger(x_seed_vec1_min, 0.5, "x_seed_vec1_min");
value_store.set_float("x_seed_vec0_max", x_seed_vec0_max);
value_store.set_float("x_seed_vec1_min", x_seed_vec1_min);
value_store.set_bool("x_min_max_set", true);
//------------------------------------------------------------------------------------------------------------------------
int width0 = x_seed_vec0_max - x_min;
int width1 = x_max - x_seed_vec1_min;
int width_min = min(width0, width1);
float gap_size = x_seed_vec1_min - x_seed_vec0_max;
low_pass_filter->compute_if_larger(gap_size, 0.1, "gap_size");
//------------------------------------------------------------------------------------------------------------------------
bool bool_complexity = complexity >= 15;
bool bool_width_min = width_min >= 20;
bool bool_gap_size = gap_size >= 5;
bool bool_gap_order = x_seed_vec0_max < x_seed_vec1_min;
dual = bool_gap_order && bool_width_min && (bool_gap_size || bool_complexity);
}
//------------------------------------------------------------------------------------------------------------------------
BlobNew* blob_max_size_left = NULL;
BlobNew* blob_max_size_right = NULL;
BlobNew* blob_max_size = NULL;
for (BlobNew& blob : *foreground_extractor.blob_detector.blobs)
{
if (blob.x <= motion_processor.x_separator_middle && (blob_max_size_left == NULL || blob.count > blob_max_size_left->count))
blob_max_size_left = &blob;
else if (blob.x > motion_processor.x_separator_middle && (blob_max_size_right == NULL || blob.count > blob_max_size_right->count))
blob_max_size_right = &blob;
if (blob_max_size == NULL || blob.count > blob_max_size->count)
blob_max_size = &blob;
}
//------------------------------------------------------------------------------------------------------------------------
int count_left = 0;
int count_right = 0;
int x_min_left = 9999;
int x_max_left = 0;
int x_min_right = 9999;
int x_max_right = 0;
for (BlobNew& blob : *foreground_extractor.blob_detector.blobs)
if (blob.active)
{
for (Point& pt : blob.data)
if (pt.x < motion_processor.x_separator_middle)
{
++count_left;
if (pt.x < x_min_left)
x_min_left = pt.x;
if (pt.x > x_max_left)
x_max_left = pt.x;
}
else
{
++count_right;
if (pt.x < x_min_right)
x_min_right = pt.x;
if (pt.x > x_max_right)
x_max_right = pt.x;
}
}
int width_left = x_max_left - x_min_left;
int width_right = x_max_right - x_min_right;
//------------------------------------------------------------------------------------------------------------------------
bool reference_is_left = value_store.get_bool("reference_is_left", false);
bool dual_old = value_store.get_bool("dual_old", dual);
bool merge = value_store.get_bool("merge", false);
if (!dual && dual_old)
{
float count_small = reference_is_left ? count_right : count_left;
float count_large = reference_is_left ? count_left : count_right;
if (count_small / count_large > 0.5)
{
merge = true;
value_store.set_bool("merge", merge);
}
}
dual_old = dual;
value_store.set_bool("dual_old", dual_old);
//------------------------------------------------------------------------------------------------------------------------
int reference_x_offset = value_store.get_int("reference_x_offset", 0);
int reference_x_offset_blob = value_store.get_int("reference_x_offset_blob", 0);
bool do_reset = value_store.get_bool("do_reset", false);
if (dual || !algo_name_found || do_reset)
{
if (dual)
{
motion_processor.compute_x_separator_middle = false;
set_value(&motion_processor.x_separator_middle, (x_seed_vec1_min + x_seed_vec0_max) / 2, 0, WIDTH_SMALL_MINUS);
}
reference_is_left = count_left > count_right;
value_store.set_bool("reference_is_left", reference_is_left);
if (!algo_name_found || do_reset)
set_value(&motion_processor.x_separator_middle, motion_processor.x_separator_middle_median, 0, WIDTH_SMALL_MINUS);
int reference_x = reference_is_left ? foreground_extractor.x_min_result : foreground_extractor.x_max_result;
reference_x_offset = reference_x - motion_processor.x_separator_middle;
value_store.set_int("reference_x_offset", reference_x_offset);
int reference_x_blob = -1;
if (reference_is_left && blob_max_size_left != NULL)
reference_x_blob = blob_max_size_left->x_max;
else if (!reference_is_left && blob_max_size_right != NULL)
reference_x_blob = blob_max_size_right->x_min;
if (reference_x_blob != -1)
{
reference_x_offset_blob = reference_x_blob - motion_processor.x_separator_middle;
value_store.set_int("reference_x_offset_blob", reference_x_offset_blob);
}
merge = false;
value_store.set_bool("merge", merge);
do_reset = false;
value_store.set_bool("do_reset", do_reset);
}
//------------------------------------------------------------------------------------------------------------------------
if (!dual && !merge)
{
int reference_x = reference_is_left ? foreground_extractor.x_min_result : foreground_extractor.x_max_result;
int reference_x_blob = reference_is_left ? blob_max_size->x_max : blob_max_size->x_min;
const int x_separator_middle_target = reference_x_blob - reference_x_offset_blob;
const int x_separator_middle = motion_processor.x_separator_middle;
const int i_increment = x_separator_middle_target > motion_processor.x_separator_middle ? 1 : -1;
int cost = 0;
for (int i = x_separator_middle; i != x_separator_middle_target; i += i_increment)
for (int j = 0; j < HEIGHT_SMALL; ++j)
if (foreground_extractor.image_foreground.ptr<uchar>(j, i)[0] > 0)
++cost;
if ((float)cost / blob_max_size->count < 0.5)
set_value(&motion_processor.x_separator_middle, x_separator_middle_target, 0, WIDTH_SMALL_MINUS);
else
{
do_reset = true;
value_store.set_bool("do_reset", do_reset);
}
}
//------------------------------------------------------------------------------------------------------------------------
Point seed_left = value_store.get_point("seed_left", Point(x_min, 0));
Point seed_right = value_store.get_point("seed_right", Point(x_max, 0));
if (merge || dual)
{
seed_left = Point(0, 0);
int seed_left_count = 0;
for (BlobNew& blob : blobs_left)
for (Point& pt : blob.data)
{
seed_left.x += pt.x;
seed_left.y += pt.y;
++seed_left_count;
}
seed_right = Point(0, 0);
int seed_right_count = 0;
for (BlobNew& blob : blobs_right)
for (Point& pt : blob.data)
{
seed_right.x += pt.x;
seed_right.y += pt.y;
++seed_right_count;
}
if (seed_left_count > 0 && seed_right_count > 0)
{
seed_left.x /= seed_left_count;
seed_left.y /= seed_left_count;
seed_right.x /= seed_right_count;
seed_right.y /= seed_right_count;
vector<Point> seed_left_vec;
vector<Point> seed_right_vec;
while (true)
{
seed_left_vec.clear();
seed_right_vec.clear();
for (BlobNew& blob : *foreground_extractor.blob_detector.blobs)
if (blob.active)
for (Point& pt : blob.data)
{
float dist_left = get_distance(pt, seed_left, false);
float dist_right = get_distance(pt, seed_right, false);
if (dist_left < dist_right)
seed_left_vec.push_back(pt);
else
seed_right_vec.push_back(pt);
}
if (seed_left_vec.size() > 0 && seed_right_vec.size() > 0)
{
Point seed_left_new = Point(0, 0);
for (Point& pt : seed_left_vec)
{
seed_left_new.x += pt.x;
seed_left_new.y += pt.y;
}
seed_left_new.x /= seed_left_vec.size();
seed_left_new.y /= seed_left_vec.size();
Point seed_right_new = Point(0, 0);
for (Point& pt : seed_right_vec)
{
seed_right_new.x += pt.x;
seed_right_new.y += pt.y;
}
seed_right_new.x /= seed_right_vec.size();
seed_right_new.y /= seed_right_vec.size();
if (seed_left.x == seed_left_new.x && seed_left.y == seed_left_new.y &&
seed_right.x == seed_right_new.x && seed_right.y == seed_right_new.y)
{
break;
}
seed_left = seed_left_new;
seed_right = seed_right_new;
}
else
break;
}
if (merge)
set_value(&motion_processor.x_separator_middle, (seed_left.x + seed_right.x) / 2, 0, WIDTH_SMALL_MINUS);
}
}
value_store.set_point("seed_left", seed_left);
value_store.set_point("seed_right", seed_right);
//------------------------------------------------------------------------------------------------------------------------
const int x_separator_middle = motion_processor.x_separator_middle;
const int x_separator_middle_median = motion_processor.x_separator_middle_median;
const int x_separator_left_median = motion_processor.x_separator_left_median;
const int x_separator_right_median = motion_processor.x_separator_right_median;
const int y_separator_down_median = motion_processor.y_separator_down_median;
const int y_separator_up_median = motion_processor.y_separator_up_median;
while (dual)
{
const int i_min = seed_left.x;
const int i_max = seed_right.x;
const int j_min = 0;
const int j_max = y_separator_up_median;
if (!(i_max > i_min && i_min >= 0 && i_max <= WIDTH_SMALL_MINUS))
break;
Point pt0 = Point(i_min, 0);
Point pt1 = Point(i_max, 0);
Point pt2 = Point(x_separator_middle, j_max); //tip point
if (pt2.y < 2 || i_max - i_min < 2)
break;
Mat image_triangle_fill = Mat::zeros(j_max + 1, WIDTH_SMALL, CV_8UC1);
line(image_triangle_fill, pt0, pt2, Scalar(254), 1);
line(image_triangle_fill, pt1, pt2, Scalar(254), 1);
floodFill(image_triangle_fill, Point(x_separator_middle, 0), Scalar(254));
for (int i = i_min; i <= i_max; ++i)
for (int j = j_min; j <= j_max; ++j)
if (image_triangle_fill.ptr<uchar>(j, i)[0] > 0)
motion_processor.fill_image_background_static(i, j, motion_processor.image_ptr);
break;
}
//------------------------------------------------------------------------------------------------------------------------
x_min_result_right = 9999;
x_max_result_right = -1;
y_min_result_right = 9999;
y_max_result_right = -1;
x_min_result_left = 9999;
x_max_result_left = -1;
y_min_result_left = 9999;
y_max_result_left = -1;
blobs_right.clear();
blobs_left.clear();
for (BlobNew& blob : *foreground_extractor.blob_detector.blobs)
if (blob.active)
{
if (blob.x > motion_processor.x_separator_middle)
{
if (blob.x_min < x_min_result_right)
x_min_result_right = blob.x_min;
if (blob.x_max > x_max_result_right)
x_max_result_right = blob.x_max;
if (blob.y_min < y_min_result_right)
y_min_result_right = blob.y_min;
if (blob.y_max > y_max_result_right)
y_max_result_right = blob.y_max;
blobs_right.push_back(blob);
}
else
{
if (blob.x_min < x_min_result_left)
x_min_result_left = blob.x_min;
if (blob.x_max > x_max_result_left)
x_max_result_left = blob.x_max;
if (blob.y_min < y_min_result_left)
y_min_result_left = blob.y_min;
if (blob.y_max > y_max_result_left)
y_max_result_left = blob.y_max;
blobs_left.push_back(blob);
}
}
//------------------------------------------------------------------------------------------------------------------------
if (visualize)
{
Mat image_visualization = Mat::zeros(HEIGHT_SMALL, WIDTH_SMALL, CV_8UC1);
for (BlobNew& blob : *foreground_extractor.blob_detector.blobs)
if (blob.active)
blob.fill(image_visualization, 254);
line(image_visualization, Point(x_separator_left_median, 0), Point(x_separator_left_median, 999), Scalar(254), 1);
line(image_visualization, Point(x_separator_right_median, 0), Point(x_separator_right_median, 999), Scalar(254), 1);
line(image_visualization, Point(x_separator_middle, 0), Point(x_separator_middle, 999), Scalar(254), 1);
line(image_visualization, Point(0, y_separator_down_median), Point(999, y_separator_down_median), Scalar(254), 1);
line(image_visualization, Point(0, y_separator_up_median), Point(999, y_separator_up_median), Scalar(254), 1);
imshow("image_visualizationsdlkfjhasdf" + name, image_visualization);
}
if (blobs_right.size() > 0 || blobs_left.size() > 0)
{
algo_name_vec.push_back(algo_name);
return true;
}
return false;
}
