如何在Python中使用skimage移除图像中不必要的点，只留下所需的簇？

from skimage.feature import peak_local_max
from skimage.segmentation import watershed
from scipy import ndimage as ndi
import numpy as np
import matplotlib.pyplot as plt

image = plt.imread('image.jpg')  # 加载图像
image_gray = rgb2gray(image)  # 转换为灰度图像

distance = ndi.distance_transform_edt(image_gray)  # 计算距离变换
coords = peak_local_max(distance, min_distance=20, labels=image_gray, threshold_abs=0.4)  # 提取峰值点的坐标

markers = np.zeros_like(image_gray)  # 创建标记图像
markers[tuple(coords.T)] = np.arange(coords.shape[0]) + 1  # 标记峰值点
labels = watershed(-distance, markers, mask=image_gray)  # 应用分水岭算法进行图像分割

fig, axes = plt.subplots(1, 2, figsize=(10, 5))
axes[0].imshow(image)
axes[0].set_title('Original Image')
axes[0].axis('off')
axes[1].imshow(labels, cmap='nipy_spectral')
axes[1].set_title('Segmented Image')
axes[1].axis('off')
plt.show()