text: Title: LongestMaxSize does upscale an image in contrast to what notes state(?)
  Body: Regarding the LongestMaxSize transformation the notes state that:
  
  > Note:
  >         - If the longest side of the image is already less than or equal to max_size, the image will not be resized.
  >         - This transform will not crop the image. The resulting image may be smaller than max_size in both dimensions.
  >         - For non-square images, the shorter side will be scaled proportionally to maintain the aspect ratio.
   
  In contrast, images **seem to be upscaled** eventhough their maximum size is smaller than the defined max_size attribute:
  
  ```
  def _func_max_size(img: np.ndarray, max_size: int, interpolation: int, func: Callable[..., Any]) -> np.ndarray:
      image_shape = img.shape[:2]
  
      scale = max_size / float(func(image_shape))
  
      if scale != 1.0:
          new_height, new_width = tuple(round(dim * scale) for dim in image_shape)
          return resize(img, (new_height, new_width), interpolation=interpolation)
      return img
  ```
  
  Is this expected behaviour? Does their exist a transformation that does not upscale the image but resizes (downscales) while maintaining the aspect ratio?