您可以尝试使用已实现统计信息的连接组件
cv2.connectedComponentsWithStats来执行组件标记。使用您的二进制图像作为输入，这是伪彩色图像：
每个对象的质心都可以在
centroid参数中找到，其他信息（例如面积）可以在从
status返回的变量中找到
cv2.connectedComponentsWithStats。这是标有每个多边形面积的图像。您可以使用最小阈值区域进行过滤，以仅保留较大的多边形
码
import cv2import numpy as np# Load image, Gaussian blur, grayscale, Otsu's thresholdimage = cv2.imread('2.jpg')blur = cv2.GaussianBlur(image, (3,3), 0)gray = cv2.cvtColor(blur, cv2.COLOR_BGR2GRAY)thresh = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)[1]# Perform connected component labelingn_labels, labels, stats, centroids = cv2.connectedComponentsWithStats(thresh, connectivity=4)# Create false color image and color background blackcolors = np.random.randint(0, 255, size=(n_labels, 3), dtype=np.uint8)colors[0] = [0, 0, 0] # for cosmetic reason we want the background blackfalse_colors = colors[labels]# Label area of each polygonfalse_colors_area = false_colors.copy()for i, centroid in enumerate(centroids[1:], start=1): area = stats[i, 4] cv2.putText(false_colors_area, str(area), (int(centroid[0]), int(centroid[1])), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255,255,255), 1)cv2.imshow('thresh', thresh)cv2.imshow('false_colors', false_colors)cv2.imshow('false_colors_area', false_colors_area)cv2.waitKey()
