I'm trying to use PIL to display a grayscale image with an associated 
mask.  I want the user to clearly see which pixels are masked, yet still 
be able to see the original data in the masked areas.

The algorithm I've come up with is to average the grayscale image with a 
mask that consists of a tint color. It seems to work (but if there's a 
better algorithm I'd love to hear of it).

However, my code to implement this looks pretty messy. Is there a better 
way?

def addMask(im, mask, maskrgb, intens=75):
    """Add a mask to a grayscale image in such a way that the
    masked areas of the image can still be seen.
    
    Inputs:
    - im is an "F" grayscale image that has been scaled into 0-255 range
    - mask is a mask such that 0 = unmasked, nonzero=masked
    - maskrgb is a tuple of RGB color values 0-255 each
    - intens is the intensity of the displayed mask 0-255

    Returns the masked image in color
    """
    lmask = mask.convert("L")
    rgbmaskset = []
    
    # create color image of mask 
    for colval in maskrgb:
        rgbmaskset.append(lmask.point(lambda i: i * colval))
    rgbmask = Image.merge("RGB", rgbmaskset)
    # create transparency version of mask
    transmask = lmask.point(lambda i: i * intens)
    # merge mask and image
    rgbim = im.convert("RGB")
    rgbim.paste(rgbmask, mask=transmask)
    return rgbim

-- Russell

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