如何使用遮罩区域找到超像素的质心？

Question

新手来了！我正在使用python加上opencv和skimage包。我已经用超像素分割了一幅图像：

segments = slic(image, n_segments=numSegments, sigma=1, convert2lab=True)

#FOR-LOOP-1
for v in np.unique(segments):
    #create a mask to access one region at the time
    mask = np.ones(image.shape[:2])
    mask[segments == v] = 0

    #my function to calculate mean of A channel in LAB color space
    A = mean_achannel(img, mask) 

现在我想得到与每个超像素的质心相关的坐标，我该怎么做呢？我尝试使用：

from skimage.measure import regionprops

#FOR-LOOP-2
regions = regionprops(segments)
for props in regions:
    cx, cy = props.centroid  # centroid coordinates

但是我不能理解如何将"FOR-LOOP-2“中的每个区域与"FOR-LOOP-1”中的正确区域联系起来。如何计算"FOR-LOOP-1“内部的每个区域质心？

Answer 1

所有需要的值都可以在for-loop-2中使用regionprops找到：

from skimage.measure import regionprops

#FOR-LOOP-2
regions = regionprops(segments,
                      intensity_image=img[..., 1])
for props in regions:
    cx, cy = props.centroid  # centroid coordinates
    v = props.label  # value of label
    mean_a = props.mean_intensity