一、图像缩放
1.API
cv2.resize(src, dsize, fx=0,fy=0,interpolation = cv2.INTER_LINEAR)
参数：
①src ：输入图像
②dsize：绝对尺寸
③fx，fy：相对尺寸
④interpolation：插值方法
2.代码演示
import cv2 as cv
import numpy as np
import matplotlib.pyplot as plt
img = cv.imread('Genshin.jpeg', -1)
cv.imshow('image', img)
[rows, cols] = img.shape[:2]
res_1 = cv.resize(img, (2*cols, 2*rows), interpolation=cv.INTER_CUBIC)
cv.imshow('image', res_1)
cv.waitKey()
res_2 = cv.resize(img, None, fx=0.5, fy=0.5)
cv.imshow('image', res_1)
cv.waitKey()
二、图像平移
1.API
cv2.warpAffine(img, M, dsize)
参数：
①img：输入图像
②M：2×3移动矩阵，为np.float32类型
③dsize：输出图像的大小
2.代码演示
import cv2 as cv
import numpy as np
import matplotlib.pyplot as plt
img = cv.imread('Genshin.jpeg', -1)
cv.imshow('image', img)
[rows, cols] = img.shape[:2]
M = np.float32([[1, 0, 100], [0, 1, 50]])
dst = cv.warpAffine(img, M, (cols, rows))
cv.imshow('image', dst)
cv.waitKey()
三、图像旋转
1.API
cv2.getRotationMatrix2D(center, angle, scale) cv.warpAffine()
参数：
①center：旋转中心
②angle：旋转角度
③scale：缩放比例
返回值：
M：旋转矩阵
2.代码演示
import cv2 as cv
import numpy as np
import matplotlib.pyplot as plt
img = cv.imread('Genshin.jpeg', -1)
cv.imshow('image', img)
[rows, cols] = img.shape[:2]
M = cv.getRotationMatrix2D((cols/2, rows/2), 120, 1)
dst = cv.warpAffine(img, M, (cols, rows))
cv.imshow('image', dst)
cv.waitKey()
四、仿射变换
1.API
cv2.getAffineTransform() cv2.warpAffine()
2.代码演示
import cv2 as cv
import numpy as np
import matplotlib.pyplot as plt
img = cv.imread('Genshin.jpeg', -1)
cv.imshow('image', img)
[rows, cols] = img.shape[:2]
pts1 = np.float32([[50, 50], [200, 50], [50, 200]])
pts2 = np.float32([[100, 100], [200, 50], [100, 250]])
M = cv.getAffineTransform(pts1, pts2)
dst = cv.warpAffine(img, M, (cols, rows))
cv.imshow('image', dst)
cv.waitKey()
五、透射变换
1.API
cv2.getPerspectiveTransform() cv2.warpPerspective()
2.代码演示
import cv2 as cv
import numpy as np
import matplotlib.pyplot as plt
img = cv.imread('Genshin.jpeg', -1)
cv.imshow('image', img)
img = cv.resize(img, None, fx=0.5, fy=0.5)
[rows, cols] = img.shape[:2]
pts1 = np.float32([[56, 65], [368, 52], [28, 138], [389, 390]])
pts2 = np.float32([[100, 145], [300, 100], [80, 290], [310, 300]])
T = cv.getPerspectiveTransform(pts1, pts2)
dst = cv.warpPerspective(img, T, (cols, rows))
cv.imshow('image', dst)
cv.waitKey()
六、图像金字塔
1.API
cv2.pyrUp(img) #对图像进行上采样 cv2.pyrDown(img) #对图像进行下采样
2.代码演示
import cv2 as cv
import numpy as np
import matplotlib.pyplot as plt
img = cv.imread('Genshin.jpeg', -1)
cv.imshow('image', img)
img = cv.pyrDown(img)
img = cv.pyrDown(img)
img = cv.pyrDown(img)
cv.imshow('image', img)
cv.waitKey()
总结
到此这篇关于OpenCV图像的几何变换处理的文章就介绍到这了,更多相关OpenCV图像几何变换内容请搜索服务器之家以前的文章或继续浏览下面的相关文章希望大家以后多多支持服务器之家！
原文链接：https://blog.csdn.net/obstacle19/article/details/136630075
