使用scikit image_标签修改图像来检测图像上的裂缝

import numpy as np
from skimage import data, filters, measure

image = data.imread('image.jpg')  # 替换为实际图像的路径

image_gray = filters.gaussian(image, sigma=1, multichannel=True)  # 将图像转换为灰度图像并进行高斯滤波

thresh = filters.threshold_otsu(image_gray)  # 使用Otsu阈值分割方法获取阈值
image_binary = image_gray > thresh  # 将图像根据阈值进行二值化

labels = measure.label(image_binary)  # 对二值图像进行连通区域标记

image_labeled = np.copy(image)
image_labeled[labels != 0] = [255, 0, 0]  # 将裂缝区域的像素值修改为红色

import matplotlib.pyplot as plt

fig, axes = plt.subplots(1, 2, figsize=(8, 4))
axes[0].imshow(image)
axes[0].set_title('Original Image')
axes[0].axis('off')
axes[1].imshow(image_labeled)
axes[1].set_title('Crack Detection')
axes[1].axis('off')
plt.show()