How to display color map of gray image?

Question

I have a 3D image with a size of 128x128x64 that has 64 images, each image has the size of 128x128. The image presents three classes with the label is 0-background, 1-first object,2-second object. I am using matplotlib to show the image.

import matplotlib.pyplot as plt
fig = plt.figure(figsize=(32,32))
ax1 = plt.add_subplot(111)
ax1.imshow(image[:, :, 32])

I want to display it in color map. In which, the background should be black color, the object 1 will be the red color, and the object 2 will be the green color. How should I modify the code? Thanks The expected result likes the bottom left of the figure

Answer 1

Your question is not very clear. You say you want to obtain a result like the bottom left panel of the figure, but this image has shading and various levels of green and red.

From your question, I understood you have a 128x128 array with only 3 possible values: 0. (background), 1. (first object) and 2. (second object). Is that correct? If so, in essence your question boils down to how to create a discret colormap with 3 levels and the colors black, red, green.

Here is what I would do:

# Generate some fake data for testing
img = np.zeros((128,128))  # Background
img[:50,:50] = np.ones((50,50))  # Object 1
img[-50:,-50:] = np.ones((50,50))*2  # Object 2

#>img
#>array([[ 1.,  1.,  1., ...,  0.,  0.,  0.],
#        [ 1.,  1.,  1., ...,  0.,  0.,  0.],
#        [ 1.,  1.,  1., ...,  0.,  0.,  0.],
#        ..., 
#        [ 0.,  0.,  0., ...,  2.,  2.,  2.],
#        [ 0.,  0.,  0., ...,  2.,  2.,  2.],
#        [ 0.,  0.,  0., ...,  2.,  2.,  2.]])





# Create a custom discret colormap
from matplotlib.colors import LinearSegmentedColormap
cmap = LinearSegmentedColormap.from_list("3colors", ['k','r','g'], N=3)



# Plot
# Don't forget to includes the bounds of your data (vmin/vmax)
# to scale the colormap accordingly
fig,ax = plt.subplots()
im = ax.imshow(img, cmap=cmap, vmin=0, vmax=2)
ax.grid(False)
cax = fig.colorbar(im)
cax.set_ticks([0,1,2])