提示:内容整理自:https://github.com/gzr2017/ImageProcessing100Wen
CV小白从0开始学数字图像处理
30 仿射变换( Afine Transformations )——旋转
- 使用仿射变换,逆时针旋转30度。
- 使用仿射变换,逆时针旋转30度并且能让全部图像显现(也就是说,单纯地做仿射变换会让图片边缘丢失,这一步中要让图像的边缘不丢失,需要耗费一些工夫)。
使用下面的式子进行逆时针方向旋转A度的仿射变换:
x' cosA -sinA tx x
[ y' ] = [ sinA cosA ty ][ y ]
1 0 0 1 1
代码如下:
1.引入库
CV2计算机视觉库
import cv2
import numpy as np
import matplotlib.pyplot as plt
2.读入数据
img = cv2.imread("imori.jpg").astype(np.float)
H, W, C = img.shape
3.旋转
A = 30.
theta = - np.pi * A / 180.
a = np.cos(theta)
b = -np.sin(theta)
c = np.sin(theta)
d = np.cos(theta)
tx = 0
ty = 0
img = np.zeros((H+2, W+2, C), dtype=np.float32)
img[1:H+1, 1:W+1] = _img
H_new = np.round(H).astype(np.int)
W_new = np.round(W).astype(np.int)
out = np.zeros((H_new, W_new, C), dtype=np.float32)
x_new = np.tile(np.arange(W_new), (H_new, 1))
y_new = np.arange(H_new).repeat(W_new).reshape(H_new, -1)
adbc = a * d - b * c
x = np.round((d * x_new - b * y_new) / adbc).astype(np.int) - tx + 1
y = np.round((-c * x_new + a * y_new) / adbc).astype(np.int) - ty + 1
dcx = (x.max() + x.min()) // 2 - W // 2
dcy = (y.max() + y.min()) // 2 - H // 2
x -= dcx
y -= dcy
x = np.minimum(np.maximum(x, 0), W+1).astype(np.int)
y = np.minimum(np.maximum(y, 0), H+1).astype(np.int)
out[y_new, x_new] = img[y, x]
out = out.astype(np.uint8)
4.保存结果
cv2.imshow("result", out)
cv2.waitKey(0)
cv2.imwrite("out.jpg", out)