Class for labeled images

[CsatiZoltan]

More and more functions work on labeled images in the codebase. Currently, these are

• show_label_image
• label_image_skeleton
• thicken_skeleton
• label_image_apply_mask
• some methods of the Analysis class could also come here

in the analysis module and

• Segmentation.save_image
• Segmentation.save_array

in the segmentation module.

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It is time to collect them in a class. We will call this class LabeledImage¹ and it should have, at first thought, the following methods:

• __init__(self, label_image)
• find_skeleton
• thicken_skeleton
• apply_mask(self, mask, value)
• change_label(self, old_labels, new_labels)
• show(self, color='random', labels=False) ²
• save_png(self, filename)
• save_numpy(self, filename)
• _validate(label_image)
• __str__(self)

and with the following data members:

• n_label

Once the class has been created, deprecate the old functions and also mention this class creation principal as an example under the "Do not overuse classes" bullet point of the program design.

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¹ MATLAB calls it "label image". However, the word "label" is also a verb and we want to avoid the misunderstanding that we perform labeling as done in computer vision. We also prefer "labeled" to "labelled" as American English is used in the rest of CristalX.
² Other values for the color parameter:

• 'seeded_random', see Random colors for grains, but with a given seed #45
• 'optimal', see Distinguishable colors for nearby labels in a label image #9