OpenCV 从 Blob 检测返回关键点坐标和区域，Python
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OpenCV return keypoints coordinates and area from blob detection, Python
提问by J_yang
I followed a blob detection example (using cv2.SimpleBlobDetector) and successfully detected the blobs in my binary image. But then I don't know how to extract the coordinates and area of the keypoints. Here are the code for the blob detections:
我按照 blob 检测示例（使用cv2.SimpleBlobDetector）并成功检测到我的二进制图像中的 blob。但后来我不知道如何提取关键点的坐标和面积。以下是 blob 检测的代码：
# I skipped the parameter setting part.
blobParams = cv2.SimpleBlobDetector_Params()
blobVer = (cv2.__version__).split('.')
if int(blobVer[0]) < 3:
detector = cv2.SimpleBlobDetector(blobParams)
else:
detector = cv2.SimpleBlobDetector_create(blobParams)
# Detect Blobs
keypoints_black = detector.detect(255-black_blob)
trans_blobs = cv2.drawKeypoints(gray_video_crop, \
keypoints_white, np.array([]), (0,0,255), cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS)
So the variable keypoints_blackcontains the information of the blob(s). When I printed the variable it looked something like this (2 blobs were found):
所以变量keypoints_black包含 blob(s) 的信息。当我打印变量时，它看起来像这样（找到了 2 个 blob）：
KeyPoint 0x10b10b870, KeyPoint 0x10b1301b0
So how to I get the coordinates of the centre of mass of the keypoints and their area so that I can send them as osc messages for interaction.
那么如何获得关键点的质心坐标及其区域，以便我可以将它们作为 osc 消息发送以进行交互。
采纳答案by Jo?o Paulo
The ptproperty:
该pt属性：
keypoints = detector.detect(frame) #list of blobs keypoints
x = keypoints[i].pt[0] #i is the index of the blob you want to get the position
y = keypoints[i].pt[1]
回答by Karthik N G
If you have a list of keypoints. Then you can print as shown below
如果您有关键点列表。然后就可以打印如下图
for keyPoint in keyPoints:
x = keyPoint.pt[0]
y = keyPoint.pt[1]
s = keyPoint.size
Edit: Size determines the diameter of the meaningful keypoint neighborhood. You can use that size and roughly calculate the area of the blob.
编辑：大小决定了有意义的关键点邻域的直径。您可以使用该大小并粗略计算 blob 的面积。
