图像仿射变换之图像平移 python实现

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一. 仿射变换介绍：

请参考：图解图像仿射变换：https://www.cnblogs.com/wojianxin/p/12518393.html

二. 仿射变换公式：

仿射变换过程，(x,y)表示原图像中的坐标，(x',y')表示目标图像的坐标 ↑

三. 仿射变换——图像平移算法：

仿射变换—图像平移算法，其中tx为在横轴上移动的距离，ty为在纵轴上移动的距离 ↑

四. python实现仿射变换——图像平移

 1 import cv2
 2 import numpy as np
 3 
 4 # 图像仿射变换->图像平移 
 5 def affine(img, a, b, c, d, tx, ty):
 6     H, W, C = img.shape
 7 
 8     # temporary image
 9     tem = img.copy()
10     img = np.zeros((H+2, W+2, C), dtype=np.float32)
11     img[1:H+1, 1:W+1] = tem
12 
13     # get new image shape
14     H_new = np.round(H * d).astype(np.int)
15     W_new = np.round(W * a).astype(np.int)
16     out = np.zeros((H_new+1, W_new+1, C), dtype=np.float32)
17 
18     # get position of new image
19     x_new = np.tile(np.arange(W_new), (H_new, 1))
20     y_new = np.arange(H_new).repeat(W_new).reshape(H_new, -1)
21 
22     # get position of original image by affine
23     adbc = a * d - b * c
24     x = np.round((d * x_new  - b * y_new) / adbc).astype(np.int) - tx + 1
25     y = np.round((-c * x_new + a * y_new) / adbc).astype(np.int) - ty + 1
26 
27     # 避免目标图像对应的原图像中的坐标溢出
28     x = np.minimum(np.maximum(x, 0), W+1).astype(np.int)
29     y = np.minimum(np.maximum(y, 0), H+1).astype(np.int)
30 
31     # assgin pixcel to new image
32     out[y_new, x_new] = img[y, x]
33 
34     out = out[:H_new, :W_new]
35     out = out.astype(np.uint8)
36 
37     return out
38 
39 
40 # Read image
41 image1 = cv2.imread("../paojie.jpg").astype(np.float32)
42 
43 # Affine : 平移，tx(W向)：向右30；ty(H向)：向上100
44 out = affine(image1, a=1, b=0, c=0, d=1, tx=30, ty=-100)
45 
46 # Save result
47 cv2.imshow("result", out)
48 cv2.imwrite("out.jpg", out)
49 cv2.waitKey(0)
50 cv2.destroyAllWindows()