图片旋转是机器学习中常用的数据增广方式，如何优雅地旋转并保证图片内容的完整是一个比较复杂的问题。如果再考虑点，问题又变复杂了。以前我都是自己写点的变换公式，今天get到一个不错的函数，cv2.transform，只要获得旋转矩阵就可以直接求点坐标了，幸福来得太突然，记录下下！

旋转矩阵

link

图旋转

link

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))

点旋转

直接用cv2.transform()，点与图对应，为绝对坐标

M = cv2.getRotationMatrix2D((cX, cY), -angle, 1.0)
pts=cv2.transform(np.asarray(pts,dtype=np.float64).reshape((-1,1,2)),M)