图片的旋转

2024年5月11日 106次阅读

原理：图片旋转的原理

代码实现：code

keras中的图片旋转：datagen = ImageDataGenerator(rotation_range = 40）#随机旋转40度

opencv中的旋转：

#不改变图片大小
import cv2
import numpy as np
def rotate(image, angle, center=None, scale=1.0):
    # grab the dimensions of the image and then determine the
    (h, w) = image.shape[:2]

    # 若未指定旋转中心，则将图像中心设为旋转中心
    if center is None:
        center = (w / 2, h / 2)

    # 计算二维旋转的仿射变换矩阵
    M = cv2.getRotationMatrix2D(center, angle, scale)

    rotated = cv2.warpAffine(image, M, (w, h))

    # 返回旋转后的图像
    return rotated
src=cv2.imread("lena.png")
print(src.shape)
output_image2=rotate(src, 45)
print(output_image2.shape)
cv2.namedWindow(" image2", cv2.WINDOW_AUTOSIZE)
cv2.imshow(" image2", output_image2)
cv2.waitKey(0)
cv2.destroyAllWindows()
#改变图片大小
import cv2
import numpy as np
def rotate_bound(image, angle):  
    # grab the dimensions of the image and then determine the  
    # center  
    (h, w) = image.shape[:2]  
    (cX, cY) = (w // 2, h // 2)  
  
    # grab the rotation matrix (applying the negative of the  
    # angle to rotate clockwise), then grab the sine and cosine  
    # (i.e., the rotation components of the matrix)  
    M = cv2.getRotationMatrix2D((cX, cY), angle, 1.0)  
    cos = np.abs(M[0, 0])  
    sin = np.abs(M[0, 1])  
  
    # compute the new bounding dimensions of the image  
    nW = int((h * sin) + (w * cos))  
    nH = int((h * cos) + (w * sin))  
  
    # adjust the rotation matrix to take into account translation  
    M[0, 2] += (nW / 2) - cX  
    M[1, 2] += (nH / 2) - cY  
  
    # perform the actual rotation and return the image  
    return cv2.warpAffine(image, M, (nW, nH))
src=cv2.imread("lena.png")
print(src.shape)
output_image1=rotate_bound(src, 45)
print(output_image1.shape)
cv2.namedWindow(" image1", cv2.WINDOW_AUTOSIZE)
cv2.imshow(" image1", output_image1)
cv2.waitKey(0)
cv2.destroyAllWindows()
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