How to use OpenCV SimpleBlobDetector - opencv

Question

Instead of any additional blob detection library, how do I use the cv::SimpleBlobDetector class and its function detectblobs()?

Answer 1

Python: Reads image blob.jpg and performs blob detection with different parameters.
#!/usr/bin/python
# Standard imports
import cv2
import numpy as np;
# Read image
im = cv2.imread("blob.jpg")
# Setup SimpleBlobDetector parameters.
params = cv2.SimpleBlobDetector_Params()
# Change thresholds
params.minThreshold = 10
params.maxThreshold = 200
# Filter by Area.
params.filterByArea = True
params.minArea = 1500
# Filter by Circularity
params.filterByCircularity = True
params.minCircularity = 0.1
# Filter by Convexity
params.filterByConvexity = True
params.minConvexity = 0.87
# Filter by Inertia
params.filterByInertia = True
params.minInertiaRatio = 0.01
# Create a detector with the parameters
# OLD: detector = cv2.SimpleBlobDetector(params)
detector = cv2.SimpleBlobDetector_create(params)
# Detect blobs.
keypoints = detector.detect(im)
# Draw detected blobs as red circles.
# cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS ensures
# the size of the circle corresponds to the size of blob
im_with_keypoints = cv2.drawKeypoints(im, keypoints, np.array([]), (0,0,255), cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS)
# Show blobs
cv2.imshow("Keypoints", im_with_keypoints)
cv2.waitKey(0)
C++: Reads image blob.jpg and performs blob detection with different parameters.
#include "opencv2/opencv.hpp"
using namespace cv;
using namespace std;
int main(int argc, char** argv)
{
// Read image
#if CV_MAJOR_VERSION < 3 // If you are using OpenCV 2
Mat im = imread("blob.jpg", CV_LOAD_IMAGE_GRAYSCALE);
#else
Mat im = imread("blob.jpg", IMREAD_GRAYSCALE);
#endif
// Setup SimpleBlobDetector parameters.
SimpleBlobDetector::Params params;
// Change thresholds
params.minThreshold = 10;
params.maxThreshold = 200;
// Filter by Area.
params.filterByArea = true;
params.minArea = 1500;
// Filter by Circularity
params.filterByCircularity = true;
params.minCircularity = 0.1;
// Filter by Convexity
params.filterByConvexity = true;
params.minConvexity = 0.87;
// Filter by Inertia
params.filterByInertia = true;
params.minInertiaRatio = 0.01;
// Storage for blobs
std::vector<KeyPoint> keypoints;
#if CV_MAJOR_VERSION < 3 // If you are using OpenCV 2
// Set up detector with params
SimpleBlobDetector detector(params);
// Detect blobs
detector.detect(im, keypoints);
#else
// Set up detector with params
Ptr<SimpleBlobDetector> detector = SimpleBlobDetector::create(params);
// Detect blobs
detector->detect(im, keypoints);
#endif
// Draw detected blobs as red circles.
// DrawMatchesFlags::DRAW_RICH_KEYPOINTS flag ensures
// the size of the circle corresponds to the size of blob
Mat im_with_keypoints;
drawKeypoints(im, keypoints, im_with_keypoints, Scalar(0, 0, 255), DrawMatchesFlags::DRAW_RICH_KEYPOINTS);
// Show blobs
imshow("keypoints", im_with_keypoints);
waitKey(0);
}
The answer has been copied from this tutorial I wrote at LearnOpenCV.com explaining various parameters of SimpleBlobDetector. You can find additional details about the parameters in the tutorial.

Answer 2

You may store the parameters for the blob detector in a file, but this is not necessary. Example:
// set up the parameters (check the defaults in opencv's code in blobdetector.cpp)
cv::SimpleBlobDetector::Params params;
params.minDistBetweenBlobs = 50.0f;
params.filterByInertia = false;
params.filterByConvexity = false;
params.filterByColor = false;
params.filterByCircularity = false;
params.filterByArea = true;
params.minArea = 20.0f;
params.maxArea = 500.0f;
// ... any other params you don't want default value
// set up and create the detector using the parameters
cv::SimpleBlobDetector blob_detector(params);
// or cv::Ptr<cv::SimpleBlobDetector> detector = cv::SimpleBlobDetector::create(params)
// detect!
vector<cv::KeyPoint> keypoints;
blob_detector.detect(image, keypoints);
// extract the x y coordinates of the keypoints:
for (int i=0; i<keypoints.size(); i++){
float X = keypoints[i].pt.x;
float Y = keypoints[i].pt.y;
}

Answer 3

Note: all the examples here are using the OpenCV 2.X API.
In OpenCV 3.X, you need to use:
Ptr<SimpleBlobDetector> d = SimpleBlobDetector::create(params);
See also: the transition guide: http://docs.opencv.org/master/db/dfa/tutorial_transition_guide.html#tutorial_transition_hints_headers

Answer 4

// creation
cv::SimpleBlobDetector * blob_detector;
blob_detector = new SimpleBlobDetector();
blob_detector->create("SimpleBlobDetector");
// change params - first move it to public!!
blob_detector->params.filterByArea = true;
blob_detector->params.minArea = 1;
blob_detector->params.maxArea = 32000;
// or read / write them with file
FileStorage fs("test_fs.yml", FileStorage::WRITE);
FileNode fn = fs["features"];
//blob_detector->read(fn);
// detect
vector<KeyPoint> keypoints;
blob_detector->detect(img_text, keypoints);
fs.release();
I do know why, but params are protected. So I moved it in file features2d.hpp to be public:
virtual void read( const FileNode& fn );
virtual void write( FileStorage& fs ) const;
public:
Params params;
protected:
struct CV_EXPORTS Center
{
Point2d loc
If you will not do this, the only way to change params is to create file (FileStorage fs("test_fs.yml", FileStorage::WRITE);), than open it in notepad, and edit. Or maybe there is another way, but I`m not aware of it.