1、介绍

2、代码

import cv2
import numpy as np
import matplotlib.pyplot as plt![# Affine](https://img-blog.csdnimg.cn/20200525155930993.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2h1eHdfbWFndXM=,size_16,color_FFFFFF,t_70)
def affine(img, dx=30, dy=30):# get shapeH, W, C = img.shape# Affine hyper parametersa = 1.b = dx / Hc = dy / Wd = 1.tx = 0.ty = 0.# prepare temporary_img = np.zeros((H+2, W+2, C), dtype=np.float32)# insert image to center of temporary_img[1:H+1, 1:W+1] = img# prepare affine image temporaryH_new = np.ceil(dy + H).astype(np.int)W_new = np.ceil(dx + W).astype(np.int)out = np.zeros((H_new, W_new, C), dtype=np.float32)# preprare assigned indexx_new = np.tile(np.arange(W_new), (H_new, 1))y_new = np.arange(H_new).repeat(W_new).reshape(H_new, -1)# prepare inverse matrix for affineadbc = a * d - b * cx = np.round((d * x_new  - b * y_new) / adbc).astype(np.int) - tx + 1y = np.round((-c * x_new + a * y_new) / adbc).astype(np.int) - ty + 1x = np.minimum(np.maximum(x, 0), W+1).astype(np.int)y = np.minimum(np.maximum(y, 0), H+1).astype(np.int)# assign value from original to affine imageout[y_new, x_new] = _img[y, x]out = out.astype(np.uint8)return out# Read image
img = cv2.imread("imori.jpg").astype(np.float32)# Affine
out = affine(img, dx=30, dy=30)# Save result
cv2.imshow("result", out)
cv2.waitKey(0)
cv2.imwrite("out.jpg", out)

3、反思

    # Affine hyper parametersa = 1.b = dx / Hc = dy / Wd = 1.tx = 0.ty = 0.