mmcv/image/transforms/geometry.py
def imrotate(img,
             angle,
             center=None,
             scale=1.0,
             border_value=0,
             auto_bound=False):
    """Rotate an image.

    Args:
        img (ndarray): Image to be rotated.
        angle (float): Rotation angle in degrees, positive values mean
            clockwise rotation.
        center (tuple): Center of the rotation in the source image, by default
            it is the center of the image.
        scale (float): Isotropic scale factor.
        border_value (int): Border value.
        auto_bound (bool): Whether to adjust the image size to cover the whole
            rotated image.

    Returns:
        ndarray: The rotated image.
    """
    if center is not None and auto_bound:
        raise ValueError('`auto_bound` conflicts with `center`')
    h, w = img.shape[:2]
    if center is None:
        center = ((w - 1) * 0.5, (h - 1) * 0.5)
    assert isinstance(center, tuple)

    matrix = cv2.getRotationMatrix2D(center, -angle, scale)
    if auto_bound:
        cos = np.abs(matrix[0, 0])
        sin = np.abs(matrix[0, 1])
        new_w = h * sin + w * cos
        new_h = h * cos + w * sin
        matrix[0, 2] += (new_w - w) * 0.5
        matrix[1, 2] += (new_h - h) * 0.5
        w = int(np.round(new_w))
        h = int(np.round(new_h))
    rotated = cv2.warpAffine(img, matrix, (w, h), borderValue=border_value)
    return rotated
def imrotate(img,
             angle,
             center=None,
             scale=1.0,
             border_value=0,
             auto_bound=False):
    """Rotate an image.

    Args:
        img (ndarray): Image to be rotated.
        angle (float): Rotation angle in degrees, positive values mean
            clockwise rotation.
        center (tuple): Center of the rotation in the source image, by default
            it is the center of the image.
        scale (float): Isotropic scale factor.
        border_value (int): Border value.
        auto_bound (bool): Whether to adjust the image size to cover the whole
            rotated image.

    Returns:
        ndarray: The rotated image.
    """
    if center is not None and auto_bound:
        raise ValueError('`auto_bound` conflicts with `center`')
    h, w = img.shape[:2]
    if center is None:
        center = ((w - 1) * 0.5, (h - 1) * 0.5)
    assert isinstance(center, tuple)

    matrix = cv2.getRotationMatrix2D(center, -angle, scale)
    if auto_bound:
        cos = np.abs(matrix[0, 0])
        sin = np.abs(matrix[0, 1])
        new_w = h * sin + w * cos
        new_h = h * cos + w * sin
        matrix[0, 2] += (new_w - w) * 0.5
        matrix[1, 2] += (new_h - h) * 0.5
        w = int(np.round(new_w))
        h = int(np.round(new_h))
    rotated = cv2.warpAffine(img, matrix, (w, h), borderValue=border_value)
    return rotated
Rotate an image.

    Args:
        img (ndarray): Image to be rotated.
        angle (float): Rotation angle in degrees, positive values mean
            clockwise rotation.
        center (tuple): Center of the rotation in the source image, by default
            it is the center of the image.
        scale (float): Isotropic scale factor.
        border_value (int): Border value.
        auto_bound (bool): Whether to adjust the image size to cover the whole
            rotated image.

    Returns:
        ndarray: The rotated image.