我试图计算阈值后的白点数量,但我的代码似乎没有检测到任何东西
输入图像
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#Standard imports
#!/usr/bin/python
# Standard imports
import cv2
import numpy as np;
# Read and threshold image
im = cv2.imread("CopperSEM.tif", cv2.IMREAD_GRAYSCALE)
ret2, LocalTH1 = cv2.threshold(im,0,255,cv2.THRESH_BINARY+cv2.THRESH_OTSU) #Without Filtering
# Set up the detector with default parameters.
parameters = cv2.SimpleBlobDetector_Params()
#change Colors to White
parameters.filterByColor = True
parameters.blobColor = 255
parameters.filterByArea = True
parameters.minArea = 1500
parameters.filterByCircularity = True
parameters.minCircularity = 0.1
parameters.filterByConvexity = True
parameters.minConvexity = 0.87
#reset the detector
detector = cv2.SimpleBlobDetector_create(parameters)
# Detect blobs.
keypoints = detector.detect(LocalTH1)
print(len(keypoints)) #will print out the number of objects that were found since keypoints is a list?
# 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(LocalTH1, keypoints, np.array([]), (0,0,255), cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS)
# Show keypoints
cv2.imshow("Keypoints", im_with_keypoints)
cv2.waitKey(0)
我的输出如下
这里有一个可能更好的方法,而不是使用blob检测器
您可以使用最小阈值区域来过滤白点的数量。通过减小阈值区域,可以包含较小的点。增大面积只会隔离较大的白色斑点。如果轮廓通过此过滤器,则可以将其添加到白点列表中
白点数量
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