RFC: a new API that plans algorithm with prior information before binarize

[johnnychen94]

In #30 we changed the usage of AdaptiveThreshold from

w = recommend_window_size(img)
f = AdaptiveThreshold(window_size = w, percentage = 15)
binarize(img, f)

to

f = AdaptiveThreshold(percentage = 15)
binarize(img, f)

By doing this, users no longer need to call recommend_window_size anymore, which is an improvement.

However, this isn't what we really want in the beginning, since we'd like to hold all parameters of AdaptiveThreshold inside of it.

a window_size is something that is intrinsic to an adaptive method since the existence of a window is what often differentiates global thresholding from adaptive local thresholding. A sensible choice of window_size does indeed depend on the size of the image.
-- @zygmuntszpak

As a solution, I’m keeping thinking of introducing another set of API that generate the algorithms with the “best” inferred parameters from prior information, for example, the usage could be:

# option 1
f = AdaptiveThreshold(img)
# option 2
f = algorithm_plan(:AdaptiveThreshold, img)

binarize(img, f)

The idea here is, use img to infer as much information as needed, and leave the others using the default value.

A toy implementation of option 1 could be:

AdaptiveThreshold(img::AbstractArray; kwargs...) = 
    AdaptiveThreshold(;window_size=default_AdaptiveThreshold_window_size(img), kwargs...)

P.S., a practical example of this design is used in my NonlocalMean, where we infer the best r_p (aka. window_size) using img.

[johnnychen94]

closed by #45