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Move files (#61)
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* move files

* remove dots
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@Sauro98
Sauro98 authored Jul 23, 2021
1 parent b9ba253 commit 9bf71a4
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Showing 5 changed files with 70 additions and 40 deletions.
10 changes: 8 additions & 2 deletions BoatSeaDetector.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -149,7 +149,7 @@ int main(int argc, char** argv)

SegmentationHelper sHelper = SegmentationHelper(input_directory, images_ext);
auto segmentationInfos = sHelper.loadInfos(false);
computeShowMetrics(segmentationInfos,true, false, &classifier, params.addBg, params.maxDim, params.minNormVariance, params.minPercArea, params.maxOverlapMetric);
computeShowMetrics(segmentationInfos,true, true, &classifier, params.addBg, params.maxDim, params.minNormVariance, params.minPercArea, params.maxOverlapMetric);
//writeParamsToFile(params, input_directory + "parameters.txt");
}

Expand All @@ -175,12 +175,18 @@ void computeShowMetrics(std::vector<SegmentationInfo>& infos, bool displayImages
//std::cout<<"pre segmentation"<<std::endl;
imageInfo.performSegmentation(displayImages, addBg, maxDim, minNormVariance);
//std::cout<<"pre IOU"<<std::endl;
auto ious = imageInfo.computeIOU(displayImages, minPercArea, maxOverlapMetric, falsePos, falseNeg);
uint falsePosCurr= 0;
uint falseNegCurr = 0;
auto ious = imageInfo.computeIOU(displayImages, minPercArea, maxOverlapMetric, falsePosCurr, falseNegCurr);
falsePos += falsePosCurr;
falseNeg += falseNegCurr;
//std::cout<<"post IOU"<<std::endl;
if(detailed){
std::cout<<imageInfo.getName()<<std::endl;
for(const auto& iou: ious)
std::cout<<"iou: "<<iou<<std::endl;
std::cout<<"False positives: "<<falsePosCurr<<std::endl;
std::cout<<"False negatives: "<<falseNegCurr<<std::endl;
}

allIous.insert(allIous.end(), ious.begin(), ious.end());
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2 changes: 1 addition & 1 deletion DatasetHelper.cpp
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Expand Up @@ -108,7 +108,7 @@ void loadDataset(
}
}

std::cout<<"sz "<<inputs.size()<<std::endl;
//std::cout<<"sz "<<inputs.size()<<std::endl;

if (vInputs.size() < vSize || tInputs.size() < tSize)
std::cout<<"Warning: not enough samples in the data file"<<std::endl;
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4 changes: 2 additions & 2 deletions KMeansClassifier.cpp
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Expand Up @@ -192,11 +192,11 @@ void KMeansClassifier::load(cv::String& inputDirectory, bool bg){
loadDataset(inputDirectory + "_boats_kp_dataset.txt", boatsCentroids, vOutputs, vInputs, vOutputs, tInputs, tOutputs, 1000000,0,0, true);
loadDataset(inputDirectory + "_bg_kp_dataset.txt", bgCentroids, vOutputs, vInputs, vOutputs, tInputs, tOutputs, 1000000,0,0, true);
*/
std::cout<<"Start mat creation"<<std::endl;
//std::cout<<"Start mat creation"<<std::endl;
bgCMat = matFromVecOfVec<double>(bgCentroids, CV_64F);
seaCMat = matFromVecOfVec<double>(seaCentroids, CV_64F);
boatsCMat = matFromVecOfVec<double>(boatsCentroids, CV_64F);
boatsCMat32 = matFromVecOfVec<float>(boatsCentroids, CV_32F);

std::cout<<"End mat creation"<<std::endl;
//std::cout<<"End mat creation"<<std::endl;
}
89 changes: 54 additions & 35 deletions SegmentationHelper.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -166,6 +166,7 @@ void SegmentationInfo::showLabeledKps(){
cv::drawKeypoints(kpImg, seaKps, kpImg, cv::Scalar(0,0,255));
cv::drawKeypoints(kpImg, bgKps, kpImg, cv::Scalar(255,0,0));
cv::imshow("kps", kpImg);
//cv::imwrite(imageName.substr(0,imageName.size()-4) + "_labeled_kps.png", kpImg);
}


Expand All @@ -177,29 +178,40 @@ bool inHollowMat(int r, int c, const cv::Size& size){
return r > 0 && c>0 && r < size.height && c < size.width && (r!=0 || c!=0);
}

void drawMarkersFromGrid(cv::Mat& img, cv::Mat& grid, cv::Mat& coms, double deltaX, double deltaY, cv::Scalar color){
void drawSingleMarker(cv::Mat& img, cv::Mat& grid, cv::Vec2f& com, int r, int c, int layer, double deltaX, double deltaY, double x0, double y0, cv::Scalar color){

if(com[0] > 0. && com[1] > 0.){
cv::circle(img, cv::Point2f(com[0], com[1]),1, color, -1, 8, 0 );
}else{
for(int nr = -1; nr <=1; nr++){
for(int nc = -1; nc <=1; nc++){
if(inHollowMat(r+nr, c+nc, img.size())){
if(grid.at<Vec3b>(r+nr,c+nc)(layer) > 0){
double x01 = x0 + nc*(deltaX/2);
double y01 = y0 + nr*(deltaY/2);
cv::circle(img, cv::Point2f(x01, y01),1, color, -1, 8, 0 );
}
}
}
}
//cv::circle(img, cv::Point2f(x0, y0),1, color, -1, 8, 0 );
}
}

void drawMarkersFromGrid(cv::Mat& img, cv::Mat& grid, cv::Mat& bgComs, cv::Mat& seaComs, cv::Mat& boatsComs, double deltaX, double deltaY){
for(int r = 0; r < grid.rows; r++){
const double y0 = deltaY*r + deltaY/2;
for(int c = 0; c < grid.cols; c++){
const double x0 = deltaX*c + deltaX/2;
if(grid.at<uchar>(r,c) > 0){
cv::Vec2f com = coms.at<cv::Vec2f>(r,c);
if(com[0] > 0. && com[1] > 0.){
cv::circle(img, cv::Point2f(com[0], com[1]),1, color, -1, 8, 0 );
}else{
for(int nr = -1; nr <=1; nr++){
for(int nc = -1; nc <=1; nc++){
if(inHollowMat(r+nr, c+nc, img.size())){
if(grid.at<uchar>(r+nr,c+nc) > 0){
double x01 = x0 + nc*(deltaX/2);
double y01 = y0 + nr*(deltaY/2);
cv::circle(img, cv::Point2f(x01, y01),1, color, -1, 8, 0 );
}
}
}
}
//cv::circle(img, cv::Point2f(x0, y0),1, color, -1, 8, 0 );
}
if(grid.at<Vec3b>(r,c)(BOAT_GRID_INDEX) > 0){
cv::Vec2f com = boatsComs.at<cv::Vec2f>(r,c);
drawSingleMarker(img, grid, com, r, c, BOAT_GRID_INDEX, deltaX, deltaY, x0, y0, cv::Scalar::all(BOAT_LABEL));
} else if (grid.at<Vec3b>(r,c)(SEA_GRID_INDEX) > 0){
cv::Vec2f com = seaComs.at<cv::Vec2f>(r,c);
drawSingleMarker(img, grid, com, r, c, SEA_GRID_INDEX, deltaX, deltaY, x0, y0, cv::Scalar::all(SEA_LABEL));
} else if (grid.at<Vec3b>(r,c)(BG_GRID_INDEX) > 0) {
cv::Vec2f com = bgComs.at<cv::Vec2f>(r,c);
drawSingleMarker(img, grid, com, r, c, BG_GRID_INDEX, deltaX, deltaY, x0, y0, cv::Scalar::all(BG_LABEL));
}
}
}
Expand Down Expand Up @@ -358,7 +370,7 @@ bool isNoisySmallBoat(cv::Mat& boatsGrid, double varThreshold){
float varY = varVec(ys, meanY);
float varCoeffX = sqrtf(varX) / boatsGrid.cols;
float varCoeffY = sqrtf(varY) / boatsGrid.rows;
std::cout<<"varcoeffX "<<varCoeffX<<" varcoeffY "<<varCoeffY;
//std::cout<<"varcoeffX "<<varCoeffX<<" varcoeffY "<<varCoeffY;
// If the detected boats are small and distributed over 33% of both directions then
// it is most likely that the detected boats are noise. It is not possible
// to distinguish an image with many sparse small boats to an image with just
Expand All @@ -376,7 +388,7 @@ bool isNoisySmallBoat(cv::Mat& boatsGrid, double varThreshold){
} else {
condNumber = varCoeffY / varCoeffX;
}
std::cout<<" cond num "<<condNumber<<std::endl;
//std::cout<<" cond num "<<condNumber<<std::endl;
// We want the largest variance to be at least 1.5 times the smallest one to have
// a predominant detection direction
if(condNumber > 1.5f)
Expand Down Expand Up @@ -481,8 +493,12 @@ void SegmentationInfo::performSegmentation(bool showResults, bool addBg, uint ma

if(image.rows >= image.cols){
cels_x = (maxDim * image.cols)/(image.rows);
if (cels_x == 0)
cels_x = 1;
} else {
cels_y = (maxDim * image.rows)/(image.cols);
if (cels_y == 0)
cels_y = 1;
}

double delta_x = image.cols/cels_x;
Expand Down Expand Up @@ -512,12 +528,12 @@ void SegmentationInfo::performSegmentation(bool showResults, bool addBg, uint ma


if(bigBoatFlag){
std::cout<<"big boat"<<std::endl;
//std::cout<<"big boat"<<std::endl;
morphMask(chs[BOAT_GRID_INDEX],5);
cv::morphologyEx(chs[BOAT_GRID_INDEX], chs[BOAT_GRID_INDEX], cv::MORPH_ERODE, cv::getStructuringElement(cv::MORPH_RECT, cv::Size(3,3)));

} else {
std::cout<<"small boat"<<std::endl;
//std::cout<<"small boat"<<std::endl;
bool isNoisy = isNoisySmallBoat(chs[BOAT_GRID_INDEX],0.2);
if(isNoisy){
// noise, erase hard
Expand All @@ -535,23 +551,24 @@ void SegmentationInfo::performSegmentation(bool showResults, bool addBg, uint ma
cv::morphologyEx(chs[SEA_GRID_INDEX], chs[SEA_GRID_INDEX], cv::MORPH_ERODE, cv::getStructuringElement(cv::MORPH_RECT, cv::Size(3,3)));
}


// BG has lowest priority, drawn first
drawMarkersFromGrid(markersMask, chs[BG_GRID_INDEX],bgComs, delta_x, delta_y, cv::Scalar::all(BG_LABEL));
// sea drawn next
drawMarkersFromGrid(markersMask, chs[SEA_GRID_INDEX], seaComs, delta_x, delta_y, cv::Scalar::all(SEA_LABEL));
// boats have highest priority and so gat drawn last
drawMarkersFromGrid(markersMask, chs[BOAT_GRID_INDEX],boatsComs, delta_x, delta_y, cv::Scalar::all(BOAT_LABEL));



drawGridOnMat(denseMarkers, chs[BG_GRID_INDEX],bgComs, delta_x, delta_y, cv::Scalar(255,0,0));
drawGridOnMat(denseMarkers, chs[SEA_GRID_INDEX],seaComs, delta_x, delta_y, cv::Scalar(0,0,255));
drawGridOnMat(denseMarkers, chs[BOAT_GRID_INDEX],boatsComs, delta_x, delta_y, cv::Scalar(0,255,0));

cv::Mat mergedGrid;
cv::merge(chs, 3, mergedGrid);

// BG has lowest priority, drawn first
drawMarkersFromGrid(markersMask, mergedGrid,bgComs, seaComs, boatsComs, delta_x, delta_y);
/*// sea drawn next
drawMarkersFromGrid(markersMask, chs[SEA_GRID_INDEX], seaComs, delta_x, delta_y, cv::Scalar::all(SEA_LABEL));
// boats have highest priority and so gat drawn last
drawMarkersFromGrid(markersMask, chs[BOAT_GRID_INDEX],boatsComs, delta_x, delta_y, cv::Scalar::all(BOAT_LABEL));*/

if(showResults){
cv::imshow("dense markers", denseMarkers);
//cv::imwrite(imageName.substr(0,imageName.size()-4) + "_dense_markers.png", denseMarkers);
}


Expand Down Expand Up @@ -582,6 +599,7 @@ void SegmentationInfo::performSegmentation(bool showResults, bool addBg, uint ma
if (showResults) {
wshed = wshed*0.5 + image*0.5;
imshow( "watershed transform", wshed );
//cv::imwrite(imageName.substr(0,imageName.size()-4) + "_watershed_transform.png", wshed);
//drawBlobPyramidBoats(image, segmentationResult, 5);
}
}
Expand Down Expand Up @@ -731,11 +749,11 @@ void SegmentationInfo::findBBoxes(bool showBoxes, double minPercArea, double max
// compute bounding boxes on the result
smasked.binaryToBBoxes(boatsSegments, estBboxes, true);

std::cout<<"Size before "<<estBboxes.size()<<std::endl;
//std::cout<<"Size before "<<estBboxes.size()<<std::endl;

mergeOverlappingRectangles(estBboxes, maxOverlapMetric);

std::cout<<"Size after "<<estBboxes.size()<<std::endl;
//std::cout<<"Size after "<<estBboxes.size()<<std::endl;

uint prevSize = estBboxes.size();
uint newSize = prevSize;
Expand All @@ -759,7 +777,8 @@ void SegmentationInfo::findBBoxes(bool showBoxes, double minPercArea, double max
for(auto& box: estBboxes) {
cv::rectangle(bboxes_img, box, cv::Scalar(0,255,0),2);
}
cv::imshow("bboxes after", bboxes_img);
cv::imshow("bboxes", bboxes_img);
//cv::imwrite(imageName.substr(0,imageName.size()-4) + "_bboxes.png", bboxes_img);
}


Expand Down
5 changes: 5 additions & 0 deletions SegmentationHelper.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -26,6 +26,7 @@
#include <random>
#include <iterator>
#include <math.h>
#include <stdlib.h>

#include "SiftMasked.h"
#include "BlackWhite_He.h"
Expand Down Expand Up @@ -56,6 +57,10 @@ class SegmentationInfo {
void appendSeaDescriptors(std::vector<std::vector<double>>& vect, bool addEnc) const;
void appendBgDescriptors(std::vector<std::vector<double>>& vect, bool addEnc) const;

std::vector<cv::Rect>& getBBoxes(){ return estBboxes;}
cv::Mat& getsegmentationResults(){return segmentationResult;}
std::vector<cv::KeyPoint> getboatKps() {return boatKps;}

private:
cv::String imageName;
std::vector<cv::Rect> trueBboxes, estBboxes;
Expand Down

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