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Does anyone have experience working with the Spectral Python module for land classification? The following k-means clustering example takes an iterative approach to classification through pixel clustering. Any thoughts, examples and/or visuals from your own work with SPy would be appreciated.

Source: SPy

>>> (m, c) = kmeans(img, 20, 50)
Using single-pass cluster algorithm to initialize clusters.
Clustering image...done
Starting iterations.
Iteration 1...done
Iteration 2...done
        18743 pixels reassigned.
Iteration 3...done
        3387 pixels reassigned.
Iteration 4...done
        2512 pixels reassigned.
Iteration 5...done
        1960 pixels reassigned.
---// snip //---
Iteration 28...done
        149 pixels reassigned.
Iteration 29...done
        135 pixels reassigned.
Iteration 30...done
        107 pixels reassigned.
^CIteration 31... 15.9%KeyboardInterrupt: Returning clusters from previous iteration
>>>

enter image description here

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closed as not constructive by R.K., whuber Nov 7 '12 at 16:39

As it currently stands, this question is not a good fit for our Q&A format. We expect answers to be supported by facts, references, or expertise, but this question will likely solicit debate, arguments, polling, or extended discussion. If you feel that this question can be improved and possibly reopened, visit the help center for guidance.If this question can be reworded to fit the rules in the help center, please edit the question.

    
Does anyone have experience working with the Spectral Python module for land classification? You might want to be more specific. In its current form, this question isn't really a good fit for the QnA format as it doesn't have a definitive answer. –  R.K. Oct 29 '12 at 12:00
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