image_processing.py

def filter_rgb_to_hed(np_img, output_type="uint8"):
    """
    Filter RGB channels to HED (Hematoxylin - Eosin - Diaminobenzidine) channels.
    Args:
      np_img: RGB image as a NumPy array.
      output_type: Type of array to return (float or uint8).
    Returns:
      NumPy array (float or uint8) with HED channels.
    """
    #t = Time()
    hed = sk_color.rgb2hed(np_img)
    if output_type == "float":
        hed = sk_exposure.rescale_intensity(hed, out_range=(0.0, 1.0))
    else:
        hed = (sk_exposure.rescale_intensity(
            hed, out_range=(0, 255))).astype("uint8")

    #util.np_info(hed, "RGB to HED", t.elapsed())
    return hed
  
 def filter_hed_to_hematoxylin(np_img, output_type="uint8"):
    """
    Obtain Hematoxylin channel from HED NumPy array and rescale it (for example, to 0 to 255 for uint8) for increased
    contrast.
    Args:
      np_img: HED image as a NumPy array.
      output_type: Type of array to return (float or uint8).
    Returns:
      NumPy array for Hematoxylin channel.
    """
    #t = Time()
    hema = np_img[:, :, 0]
    if output_type == "float":
        hema = sk_exposure.rescale_intensity(hema, out_range=(0.0, 1.0))
    else:
        hema = (sk_exposure.rescale_intensity(
            hema, out_range=(0, 255))).astype("uint8")
    #util.np_info(hema, "HED to Hematoxylin", t.elapsed())
    return hema
  
  def np_to_pil(np_img):
    """
    Convert a NumPy array to a PIL Image.

    Args:
      np_img: The image represented as a NumPy array.

    Returns:
       The NumPy array converted to a PIL Image.
    """
    if np_img.dtype == "bool":
        np_img = np_img.astype("uint8") * 255
    elif np_img.dtype == "float64":
        np_img = (np_img * 255).astype("uint8")
    return Image.fromarray(np_img)