1.裁剪
# x轴 100 --200
# y轴 100 -- 300
import cv2
img = cv2.imread("图片的位置",0或者1)
imgInfo = img.shape
dst = img[100:200,100:300]
cv2.imshow('image',dst)
cv2.waitKey(0)
2.# 步骤 API 算法原理 源代码
import cv2
img = imread("图片的位置",0或1)
cv2.imshow('src',1)
imgInfo = img.shape
height = imgInfo[0]
width = imgInfo[1]
matShift = np.float([[1,0,100],[0,1,200]]) # 里面是一个2*3的矩阵
dst = cv2.warpAffine(img,matShift,(height,width)) # 参数:1.img原始图片的信息 2.matShift移位矩阵 3. 图片的宽高
cv2.imshow('dst',dst)
cv2.waitKey(0)
算法原理:
# [[1,0,100],[0,1,200]] 2*2 2*1
[[1,0],[0,1]] 2*2 A
[[100],[200]] 2*1 B
[[x],[y]] C
A*C+B = [[1*x+0*y],[0*x+1*y]] + [[100],[200]]
= [[x+100],[y+200]]
import cv2
import numpy as np
img = imread("图片的位置",0或1)
cv2.imshow('src',1)
imgInfo = img.shape
height = imgInfo[0]
width = imgInfo[1]
dst = np.zeros(img.shap,np.uint8)
for i in range(0,height):
for j in range(0,width-100):
dst[i,j+100] = img[i,j]
cv2.imshow('image',dst)
cv2.waitKey(0)
使用opencv裁剪图片和移位
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转载自blog.csdn.net/qq_15256443/article/details/84065016
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