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Merge remote-tracking branch 'upstream/3.4' into merge-3.4

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This commit is contained in:
Alexander Alekhin
2021-10-07 04:27:22 +00:00
parent 4dd3ab8f32 a3d7811f24
commit 03a08435e2
7 changed files with 70 additions and 14 deletions
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modules/features2d/src/blobdetector.cpp
+16 -7
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@@ -44,6 +44,8 @@
#include <iterator>
#include <limits>
#include <opencv2/core/utils/logger.hpp>
// Requires CMake flag: DEBUG_opencv_features2d=ON
//#define DEBUG_BLOB_DETECTOR
@@ -317,6 +319,19 @@ void SimpleBlobDetectorImpl::detect(InputArray image, std::vector<cv::KeyPoint>&
CV_Error(Error::StsUnsupportedFormat, "Blob detector only supports 8-bit images!");
}
CV_CheckGT(params.thresholdStep, 0.0f, "");
if (params.minThreshold + params.thresholdStep >= params.maxThreshold)
{
// https://github.com/opencv/opencv/issues/6667
CV_LOG_ONCE_INFO(NULL, "SimpleBlobDetector: params.minDistBetweenBlobs is ignored for case with single threshold");
#if 0 // OpenCV 5.0
CV_CheckEQ(params.minRepeatability, 1u, "Incompatible parameters for case with single threshold");
#else
if (params.minRepeatability != 1)
CV_LOG_WARNING(NULL, "SimpleBlobDetector: params.minRepeatability=" << params.minRepeatability << " is incompatible for case with single threshold. Empty result is expected.");
#endif
}
std::vector < std::vector<Center> > centers;
for (double thresh = params.minThreshold; thresh < params.maxThreshold; thresh += params.thresholdStep)
{
@@ -325,19 +340,13 @@ void SimpleBlobDetectorImpl::detect(InputArray image, std::vector<cv::KeyPoint>&
std::vector < Center > curCenters;
findBlobs(grayscaleImage, binarizedImage, curCenters);
if(params.maxThreshold - params.minThreshold <= params.thresholdStep) {
// if the difference between min and max threshold is less than the threshold step
// we're only going to enter the loop once, so we need to add curCenters
// to ensure we still use minDistBetweenBlobs
centers.push_back(curCenters);
}
std::vector < std::vector<Center> > newCenters;
for (size_t i = 0; i < curCenters.size(); i++)
{
bool isNew = true;
for (size_t j = 0; j < centers.size(); j++)
{
double dist = norm(centers[j][centers[j].size() / 2 ].location - curCenters[i].location);
double dist = norm(centers[j][ centers[j].size() / 2 ].location - curCenters[i].location);
isNew = dist >= params.minDistBetweenBlobs && dist >= centers[j][ centers[j].size() / 2 ].radius && dist >= curCenters[i].radius;
if (!isNew)
{