Added working otsu and mean thresholding #15
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| fn apply_threshold<T>(data: &Array3<T>, threshold: f64) -> Array3<bool> |
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Why have threshold as f64 and not type T?
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In general thresholding algorithms sometimes generate thresholds of a different type to the input (consider for example the mean threshold on ints, which at least from a theory perspective should be a float); if casting back to T is used, then we would need to decide on a strategy (round or floor?), which would likely depend also on whether the threshold value is used for > or >= comparison when being applied to generate the binary result.
Am certainly open to adjusting this to T if we can decide on a consistent strategy that is also in-line with how this is done in other frameworks.
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That all makes sense, I'm happy with keeping it as f64
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Oh another comment, if a thresholding algorithm is only assumed to or designed to work with a single channel image you can always check the number of channels and return a channel dimension mismatch error. I do that in the canny module as canny doesn't make sense with >1 channels |
* Removed commented-out code * Removed debug println * Corrected typo in the comments
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Awesome all looks good to me, if you just update the changelog to mention the thresholding module and algorithms in the unreleased additions I can merge this in 👍 |
The Otsu and Mean threshold implementations mentioned in #13