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fanfuhan OpenCV 教學047 ~ opencv-047-二值化圖像連通組件狀態統計[八方鍊碼:元件標記/尋找/計算(計數)/統計參數] 資料來源: https://fanfuhan.github.io/ https://fanfuhan.github.io/2019/04/15/opencv-047/ GITHUB:https://github.com/jash-git/fanfuhan_ML_OpenCV C++ #include #include using namespace std; using namespace cv; RNG rng(12345); void componentwithstats_demo(Mat &image); /* * 二值图像连通组件状态统计 */ int main() { Mat src = imread("../images/rice.png"); if (src.empty()) { cout << "could not load image.." << endl; } imshow("input", src); componentwithstats_demo(src); waitKey(0); return 0; } void componentwithstats_demo(Mat &image) { // extract labels Mat gray, binary; GaussianBlur(image, image, Size(3, 3), 0); cvtColor(image, gray, COLOR_BGR2GRAY); threshold(gray, binary, 0, 255, THRESH_BINARY | THRESH_OTSU); Mat labels = Mat::zeros(image.size(), CV_32S); Mat stats, centroids; int num_labels = connectedComponentsWithStats(binary, labels, stats, centroids, 8, 4); cout << "total labels : " << num_labels - 1 << endl; vector colors(num_labels); // 背景颜色 colors[0] = Vec3b(0, 0, 0); // 目标颜色 for (int i = 1; i < num_labels; ++i) { colors[i] = Vec3b(rng.uniform(0, 256), rng.uniform(0, 256), rng.uniform(0, 256)); } // 抽取统计信息 Mat dst = image.clone(); for (int i = 1; i < num_labels; ++i) { // 中心位置 int cx = centroids.at(i, 0); int cy = centroids.at(i, 1); // 统计信息 int x = stats.at(i, CC_STAT_LEFT); int y = stats.at(i, CC_STAT_TOP); int w = stats.at(i, CC_STAT_WIDTH); int h = stats.at(i, CC_STAT_HEIGHT); int area = stats.at(i, CC_STAT_AREA); // 中心位置绘制 circle(dst, Point(cx, cy), 2, Scalar(0, 255, 0), 2); // 外接矩形 Rect rect(x, y, w, h); rectangle(dst, rect, colors[i]); putText(dst, format("num:%d", i), Point(x, y), FONT_HERSHEY_SIMPLEX, .5, Scalar(0, 0, 255), 1); printf("num : %d, rice area : %d\n", i, area); } imshow("result", dst); } Python import cv2 as cv import numpy as np def connected_components_stats_demo(src): src = cv.GaussianBlur(src, (3, 3), 0) gray = cv.cvtColor(src, cv.COLOR_BGR2GRAY) ret, binary = cv.threshold(gray, 0, 255, cv.THRESH_BINARY | cv.THRESH_OTSU) cv.imshow("binary", binary) num_labels, labels, stats, centers = cv.connectedComponentsWithStats(binary, connectivity=8, ltype=cv.CV_32S) colors = [] for i in range(num_labels): b = np.random.randint(0, 256) g = np.random.randint(0, 256) r = np.random.randint(0, 256) colors.append((b, g, r)) colors[0] = (0, 0, 0) image = np.copy(src) for t in range(1, num_labels, 1): x, y, w, h, area = stats[t] cx, cy = centers[t] cv.circle(image, (np.int32(cx), np.int32(cy)), 2, (0, 255, 0), 2, 8, 0) cv.rectangle(image, (x, y), (x+w, y+h), colors[t], 1, 8, 0) cv.putText(image, "num:" + str(t), (x, y), cv.FONT_HERSHEY_SIMPLEX, .5, (0, 0, 255), 1); print("label index %d, area of the label : %d"%(t, area)) cv.imshow("colored labels", image) cv.imwrite("D:/labels.png", image) print("total rice : ", num_labels - 1) input = cv.imread("D:/images/rice.png") connected_components_stats_demo(input) cv.waitKey(0) cv.destroyAllWindows()