overlay() doesn't return expected result

[hackermd]

Following this tutorial I tried the overlay() function on one of my images (DAPI stain):

import mahotas as mh
import numpy as np
from matplotlib import pyplot as plt  # also tried: import pylab as plt

filename = ''  # some image file
img = mh.imread(filename)

thresh = mh.otsu(img.astype(np.uint))
img_bin = img > thresh

img_over = mh.overlay(img, red=img_bin)

plt.imshow(img_over)
plt.show()

This results in a gray image without any coloring.

(img_over[:,:,0] == img_over[:,:,1]).all()

returns True

I'm using mahotas version 1.4 and matplotlib version 1.4.3 and python 2.7

[luispedro]

Sorry, I cannot reproduce. Do you still have this error if, instead of loading an image from disk (which I cannot use unless you upload it), you use

img = mh.demos.load('nuclear', as_grey=True)

[hackermd]

Thanks for looking into it! Using your demo works! However, the color is not red, but cyan.

When I read my image file as follows

img = mh.imread(filename).astype(np.uint8).astype(np.float64)

to get the same data type and scale as the loaded demo image, I get a colored image, but again the color is cyan instead of red. In addition, the the grayscale image (first input argument) is colorized and not the binary mask (second input argument).

The image file is a 16-bit PNG.

[luispedro]

Ah! OK, I see the cyan now.

This is partially a matplotlib issue: imshow does not support 16 bit images. See:

matplotlib/matplotlib#2499
matplotlib/matplotlib#2632

Maybe overlay() should convert its arguments to np.uint8. But the real issue, IMHO, is matplotlib's obtuseness.