如何使用 OpenCV SimpleBlobDetector

本文介绍了如何使用 OpenCV SimpleBlobDetector的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！

问题描述

我如何使用 cv::SimpleBlobDetector 类及其函数 detectblobs() 而不是任何额外的 blob 检测库?

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

推荐答案

Python: 读取图像 blob.jpg 并使用不同参数执行 blob 检测.

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++: 读取图像 blob.jpg 并使用不同的参数执行 blob 检测.

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);
}

答案已从本教程复制而来我在 LearnOpenCV.com 上写道，解释了 SimpleBlobDetector 的各种参数.您可以在教程中找到有关参数的更多详细信息.

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.

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Detection