def imresize(
        img: np.ndarray,
        size: Tuple[int, int],
        return_scale: bool=False,
        interpolation: str='bilinear',
        out: Optional[np.ndarray]=None,
        backend: Optional[str]=None,
        interp=cv2.INTER_LINEAR, ) -> Union[Tuple[np.ndarray, float, float],
                                            np.ndarray]:
    """Resize image to a given size.

    Args:
        img (ndarray): The input image.
        size (tuple[int]): Target size (w, h).
        return_scale (bool): Whether to return `w_scale` and `h_scale`.
        interpolation (str): Interpolation method, accepted values are
            "nearest", "bilinear", "bicubic", "area", "lanczos" for 'cv2'
            backend, "nearest", "bilinear" for 'pillow' backend.
        out (ndarray): The output destination.
        backend (str | None): The image resize backend type. Options are `cv2`,
            `pillow`, `None`. If backend is None, the global imread_backend
            specified by ``mmcv.use_backend()`` will be used. Default: None.

    Returns:
        tuple | ndarray: (`resized_img`, `w_scale`, `h_scale`) or
        `resized_img`.
    """
    h, w = img.shape[:2]
    if backend is None:
        backend = imread_backend
    if backend not in ['cv2', 'pillow']:
        raise ValueError(f'backend: {backend} is not supported for resize.'
                         f"Supported backends are 'cv2', 'pillow'")

    if backend == 'pillow':
        assert img.dtype == np.uint8, 'Pillow backend only support uint8 type'
        pil_image = Image.fromarray(img)
        pil_image = pil_image.resize(size, pillow_interp_codes[interpolation])
        resized_img = np.array(pil_image)
    else:
        resized_img = cv2.resize(img, size, dst=out, interpolation=interp)
    if not return_scale:
        return resized_img
    else:
        w_scale = size[0] / w
        h_scale = size[1] / h
        return resized_img, w_scale, h_scale
Resize image to a given size.

    Args:
        img (ndarray): The input image.
        size (tuple[int]): Target size (w, h).
        return_scale (bool): Whether to return `w_scale` and `h_scale`.
        interpolation (str): Interpolation method, accepted values are
            "nearest", "bilinear", "bicubic", "area", "lanczos" for 'cv2'
            backend, "nearest", "bilinear" for 'pillow' backend.
        out (ndarray): The output destination.
        backend (str | None): The image resize backend type. Options are `cv2`,
            `pillow`, `None`. If backend is None, the global imread_backend
            specified by ``mmcv.use_backend()`` will be used. Default: None.

    Returns:
        tuple | ndarray: (`resized_img`, `w_scale`, `h_scale`) or
        `resized_img`.
    
ppdet/data/transform/keypoint_operators.py