![](https://img-blog.csdnimg.cn/20190614190051565.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L25hdHVyZXM2Ng==,size_16,color_FFFFFF,t_70)
#1 load 2 info 3 resize 4 check
import cv2
img = cv2.imread('bucky.jpg',1)
imgInfo = img.shape
print(imgInfo)
height = imgInfo[0]
width = imgInfo[1]
mode = imgInfo[2]
#1 放大 缩小 2等比例 非
dstHeight = int(height*0.5)
dstWidth = int(width*0.5)
#最近邻域插值 双线性插值 像素重采样 立方插值
dst = cv2.resize(img,(dstWidth,dstHeight))
cv2.imshow('img',dst)
cv2.waitKey(0)
#最近邻域插值 双线性插值 原理
# src 10*20 dst 5*10
# dst<-src
# (1,2)<-(2,4)
# dst x 1 <- src x 2 newX
# newX = x*(src 行/目标 行数) newX = 1*(10/5) = 2
# newY = y*(src 列/目标 列数) newY = 2*(20/10) = 4
# 双线性插值
# A1 = 20% 上 + 80% 下 A2同样
# B1 = 30% 左 + 70% 右 B2同样
# 1 最终点 = A1 30% + A2 70%
# 2 最终点 = B1 20% + B2 80%
# 1 info 2空白模板 3xy
import cv2
import numpy as np
img = cv2.imread('bucky.jpg',1)
imgInfo = img.shape
height = imgInfo[0]
width = imgInfo[1]
dstHeight = int(height*0.5)
dstWidth = int(width*0.5)
dstImage = np.zeros((dstHeight,dstWidth,3),np.uint8)#0-255
for i in range(0,dstHeight):#行
for j in range(0,dstWidth):#列
iNew = int(i*(height*1.0/dstHeight))
jNew = int(j*(width*1.0/dstWidth))
dstImage[i,j] = img[iNew,jNew]
cv2.imshow('image',dstImage)
cv2.waitKey(0)