1. 程式人生 > 實用技巧 >【opencv+python】影象的基本操作:縮放、剪下、位移、旋轉、仿射變換

【opencv+python】影象的基本操作:縮放、剪下、位移、旋轉、仿射變換

1.縮放

程式碼:

# 使用resize函式實現圖片縮放
import cv2
src = cv2.imread("C:/360Downloads/1.jpg", 1)
cv2.imshow("src", src)
srcInfo = src.shape
height = srcInfo[0]
width = srcInfo[1]

dstHeight = int(height * 0.5)
dstWidth = int(width * 0.5)

dst = cv2.resize(src, (dstWidth, dstHeight))
cv2.imshow("dst", dst)
cv2.waitKey(0)

# 使用warpAffine函式實現圖片縮放 import cv2 import numpy as np src = cv2.imread("C:/360Downloads/1.jpg", 1) cv2.imshow("src", src) srcInfo = src.shape height = int(srcInfo[0]/2) width = int(srcInfo[1]/2) # 將圖片縮小為原來的一半: # xNew = x * 0.5 # yNew = y * 0.5 # xNew = x * A1 + y * A2 + B1 # yNew = x * A3 + y * A4 + B2 #
np.float32([[A1, A3, B1], # [A2, A4, B2]]) matScale = np.float32([[0.5, 0, 0], [0, 0.5, 0]]) dst = cv2.warpAffine(src, matScale, (width, height)) cv2.imshow("dst", dst) cv2.waitKey(0)

效果:

2.剪下

程式碼:

# 圖片剪下
import cv2
src = cv2.imread("C:/360Downloads/1.jpg", 1)
cv2.imshow(
"src", src)
# [行,列] dst
= src[100:200, 100:300] cv2.imshow("dst", dst) cv2.waitKey(0)

效果:

3.位移

程式碼:

# 影象位移
import cv2
import numpy as np
src = cv2.imread("C:/360Downloads/1.jpg", 1)
cv2.imshow("src", src)
srcInfo = src.shape
height = srcInfo[0]
width = srcInfo[1]

# 左移100,下移200:
# xNew = x + 100
# yNew = y + 200

# xNew = x * A1 + y * A2 + B1
# yNew = x * A3 + y * A4 + B2

# np.float32([[A1, A3, B1],
#             [A2, A4, B2]])
matShift = np.float32([[1, 0, 100], [0, 1, 200]])
dst = cv2.warpAffine(src, matShift, (width, height))

cv2.imshow("dst", dst)
cv2.waitKey(0)

效果:

4.旋轉

程式碼:

# 旋轉影象
import cv2
src = cv2.imread("C:/360Downloads/1.jpg", 1)
cv2.imshow("src", src)
srcInfo = src.shape
height = srcInfo[0]
width = srcInfo[1]

# getRotationMatrix2D 函式可獲取旋轉的仿射矩陣
# 引數依次為(旋轉中心,旋轉角度,縮放比例)
matRotate = cv2.getRotationMatrix2D((0, 0), 45, 0.5)
dst = cv2.warpAffine(src, matRotate, (width, height))

cv2.imshow("dst", dst)
cv2.waitKey(0)

效果:

5.仿射變換

程式碼:

# 仿射變換
import cv2
import numpy as np
src = cv2.imread("C:/360Downloads/1.jpg", 1)
cv2.imshow("src", src)
srcInfo = src.shape
height = srcInfo[0]
width = srcInfo[1]

# 三點確定一個平面
# getAffineTransform 函式可獲取仿射矩陣
# 引數依次為(源影象的三點座標,目標影象的三點座標)
# 三點分別為(左上角,左下角,右上角)
matSrc = np.float32([[0, 0], [0, height - 1], [width - 1, 0]])
matDst = np.float32([[50, 50], [150, height - 100], [width - 100, 150]])
matAffine = cv2.getAffineTransform(matSrc, matDst)
dst = cv2.warpAffine(src, matAffine, (width, height))

cv2.imshow("dst", dst)
cv2.waitKey(0)

效果: