void Test::RunCannyTest(const RGBImage* in) {
Gaussian smoother;
Sobel sobel;
Canny canny;
StudentPreProcessing converter;
double sigma = 1.6;
int kernelSize = 5;
// Convert RGB to Intensity
IntensityImage* grey = ImageFactory::newIntensityImage(in->getWidth(), in->getHeight());
grey = converter.stepToIntensityImage(*in);
BaseTimer timer;
int total = 0;
for (int i = 0; i < 10; ++i) {
timer.start();
/* Start of Canny */
// 1. Smooth Intensity with Gaussian
IntensityImage* gaussian = ImageFactory::newIntensityImage(in->getWidth() - kernelSize, in->getHeight() - kernelSize);
smoother.smoothImage(grey, gaussian, sigma, kernelSize);
// 2. Find edges with Sobel (convolve X and Y separately for Canny)
int sobelKernelSize = 3;
IntensityImage* sobelX = ImageFactory::newIntensityImage(gaussian->getWidth() - sobelKernelSize, gaussian->getHeight() - sobelKernelSize);
IntensityImage* sobelY = ImageFactory::newIntensityImage(gaussian->getWidth() - sobelKernelSize, gaussian->getHeight() - sobelKernelSize);
sobel.filterXY(gaussian, sobelX, sobelY);
// 3. Apply non-maximum suppresion
IntensityImage* nonMaxSuppression = ImageFactory::newIntensityImage(sobelX->getWidth(), sobelX->getHeight());
canny.nonMaximumSurpression(sobelX, sobelY, nonMaxSuppression);
// 4. Apply hysteresis threshold
IntensityImage* hysteresisThreshold = ImageFactory::newIntensityImage(sobelX->getWidth(), sobelX->getHeight());
canny.threshold(nonMaxSuppression, hysteresisThreshold, 60, 70);
timer.stop();
std::cout << timer.elapsedMilliSeconds() << " ms" << std::endl;
total += timer.elapsedMilliSeconds();
timer.reset();
if (i == 9)
ImageIO::saveIntensityImage(*hysteresisThreshold, ImageIO::getDebugFileName("Canny.png"));
}
std::cout << "Average time per Canny edge detection: " << (total / 10) << " ms" << std::endl;
std::cout << "Press the X in the console window to exit program" << std::endl;
}
void Test::RunScaleTest(RGBImage* in) {
StudentPreProcessing sPre;
IntensityImage* grey = ImageFactory::newIntensityImage(in->getWidth(), in->getHeight());
grey = sPre.stepToIntensityImage(*in);
IntensityImage* scale;
BaseTimer timer;
int total = 0;
for (int i = 0; i < 10; ++i) {
timer.start();
scale = sPre.stepScaleImage(*grey);
timer.stop();
std::cout << timer.elapsedMicroSeconds() << " us" << std::endl;
total += timer.elapsedMicroSeconds();
timer.reset();
}
std::cout << "Gemiddelde tijd: " << (total / 10) << " us" << std::endl;
}
bool executeSteps(DLLExecution * executor) {
//Execute the four Pre-processing steps
if (!executor->executePreProcessingStep1(false)) {
std::cout << "Pre-processing step 1 failed!" << std::endl;
return false;
}
if (!executor->executePreProcessingStep2(false)) {
std::cout << "Pre-processing step 2 failed!" << std::endl;
return false;
}
ImageIO::saveIntensityImage(*executor->resultPreProcessingStep2, ImageIO::getDebugFileName("Pre-processing-2.png"));
if (!executor->executePreProcessingStep3(false)) {
std::cout << "Pre-processing step 3 failed!" << std::endl;
return false;
}
ImageIO::saveIntensityImage(*executor->resultPreProcessingStep3, ImageIO::getDebugFileName("Pre-processing-3.png"));
if (!executor->executePreProcessingStep4(false)) {
std::cout << "Pre-processing step 4 failed!" << std::endl;
return false;
}
ImageIO::saveIntensityImage(*executor->resultPreProcessingStep4, ImageIO::getDebugFileName("Pre-processing-4.png"));
//Execute the localization steps
if (!executor->prepareLocalization()) {
std::cout << "Localization preparation failed!" << std::endl;
return false;
}
std::vector<long long> time;
for (int i = 0; i < 10000; ++i){
bt.start();
if (!executor->executeLocalizationStep1(true)) {
std::cout << "Localization step 1 failed!" << std::endl;
return false;
}
bt.stop();
time.push_back(bt.elapsedMicroSeconds()); \
bt.reset();
}
long long total = 0;
for (int i = 0; i < time.size(); ++i){
total = total + time[i];
}
long long average = total / time.size();
std::cout << average;
if (!executor->executeLocalizationStep2(false)) {
std::cout << "Localization step 2 failed!" << std::endl;
return false;
}
if (!executor->executeLocalizationStep3(false)) {
std::cout << "Localization step 3 failed!" << std::endl;
return false;
}
if (!executor->executeLocalizationStep4(false)) {
std::cout << "Localization step 4 failed!" << std::endl;
return false;
}
if (!executor->executeLocalizationStep5(false)) {
std::cout << "Localization step 5 failed!" << std::endl;
return false;
}
//Execute the extraction steps
if (!executor->prepareExtraction()) {
std::cout << "Extraction preparation failed!" << std::endl;
return false;
}
if (!executor->executeExtractionStep1(false)) {
std::cout << "Extraction step 1 failed!" << std::endl;
return false;
}
if (!executor->executeExtractionStep2(false)) {
std::cout << "Extraction step 2 failed!" << std::endl;
return false;
}
if (!executor->executeExtractionStep3(false)) {
std::cout << "Extraction step 3 failed!" << std::endl;
return false;
}
//Post processing and representation
if (!executor->executePostProcessing()) {
std::cout << "Post-processing failed!" << std::endl;
return false;
}
drawFeatureDebugImage(*executor->resultPreProcessingStep1, executor->featuresScaled);
if (!executor->executeRepresentation()) {
std::cout << "Representation failed!" << std::endl;
return false;
}
return true;
}
