Fix and test clustering #74
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This has one breaking change: while the docs advertise that
"All the segmentation algorithms (except Fuzzy C-means) return a
struct SegmentedImage," that's not been true for `kmeans`.
This changes the output so that `kmeans` does return a `SegmentedImage`.
This is a breaking change, because the types are not interchangeable.
This became apparent when trying to add tests for `kmeans`, which
have been lacking.
Before releasing this, we may want to make a second breaking change:
currently, ImageSegmentation provides a new meaning for
`Matrix{Gray{T}}` than Clustering.jl provides for `Matrix{T}`.
This breaks our abstraction that `Gray ≈ Number`.
A way to fix that would be to have `ImageSegmentation.kmeans`
be a different function from `Clustering.kmeans`, and obviously
have the one in ImageSegmentation call the one in Clustering.
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This has one breaking change: while the docs advertise that
"All the segmentation algorithms (except Fuzzy C-means) return a
struct SegmentedImage," that's not been true for
kmeans.This changes the output so that
kmeansdoes return aSegmentedImage.This is a breaking change, because the types are not interchangeable.
This became apparent when trying to add tests for
kmeans, whichhave been lacking.
Before releasing this, we may want to make a second breaking change:
currently, ImageSegmentation provides a new meaning for
Matrix{Gray{T}}than Clustering.jl provides forMatrix{T}.This breaks our abstraction that
Gray ≈ Number.A way to fix that would be to have
ImageSegmentation.kmeansbe a different function from
Clustering.kmeans, and obviouslyhave the one in ImageSegmentation call the one in Clustering.