图像处理中遇到的Python问题及解决方案

import cv2

# 读取图像
image = cv2.imread('image.jpg')

# 显示图像
cv2.imshow('Image', image)
cv2.waiTKEy(0)
cv2.destroyAllwindows()

import cv2

# 读取图像
image = cv2.imread('image.jpg')

# 调整图像大小
resized_image = cv2.resize(image, (800, 600))

# 显示调整大小后的图像
cv2.imshow('Resized Image', resized_image)
cv2.waitKey(0)
cv2.destroyAllWindows()

import cv2

# 读取图像
image = cv2.imread('image.jpg')

# 将图像转换为灰度图
gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

# 对灰度图进行高斯滤波
blurred_image = cv2.GaussianBlur(gray_image, (5, 5), 0)

# 显示滤波后的图像
cv2.imshow('Blurred Image', blurred_image)
cv2.waitKey(0)
cv2.destroyAllWindows()

import cv2

# 读取图像
image = cv2.imread('image.jpg')

# 将图像转换为灰度图
gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

# 对灰度图进行Canny边缘检测
edges = cv2.Canny(gray_image, 100, 200)

# 显示边缘图像
cv2.imshow('Edges', edges)
cv2.waitKey(0)
cv2.destroyAllWindows()

from skimage import segmentation
import matplotlib.pyplot as plt

# 读取图像
image = plt.imread('image.jpg')

# 对图像进行分割
segments = segmentation.slic(image, n_segments=100)

# 显示分割后的图像
plt.imshow(segments)
plt.axis('off')
plt.show()