# [[A1 A2 B1],[A3 A4 B2]] # [[A1 A2],[A3 A4]] [[B1],[B2]] # newX = A1*x + A2*y+B1 # newY = A3*x + A4*y+B2 # x->x*0.5 y->y*0.5 # newX = 0.5*x import cv2 import numpy as np img = cv2.imread('image0.jpg',1) cv2.imshow('src',img) imgInfo = img.shape height = imgInfo[0] width = imgInfo[1] #matScale = np.float32([[A1 A2 B1],[A3 A4 B2]]) # 定义一个2*3的矩阵 matScale = np.float32([[0.5,0,0],[0,0.5,0]]) # 缩放矩阵 dst = cv2.warpAffine(img,matScale,(int(width/2),int(height/2))) #定义一个仿射方法 原始数据 缩放矩阵 最终生成的图片的宽高信息 cv2.imshow('dst',dst) cv2.waitKey(0)
