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This is a proposed redesign that may be a bit more natural to work
with from the Julia perspective. The principal differences are:
Support eltypes of the form
SVector{T,N}
: this makes this wrapperbehave more like OpenCV itself, which (unlike Python) does not use
an array dimension to encode the number of color channels.
Support
N0f8
andN0f16
, JuliaImages preferred interpretation of8- and 16-bit unsigned intensity data. (See FixedPointNumbers and
https://juliaimages.org/latest/tutorials/arrays_colors/#fixedpoint;
interestingly, OpenCV itself suffers from the exact same problem, see
https://stackoverflow.com/questions/14539498/change-type-of-mat-object-from-cv-32f-to-cv-8u
for an example of a user who got bit by the "divide by 255" rule.)
Work towards support for multidimensional arrays (see
Multidimensional images JuliaImages/OpenCV.jl#4)
Validate arguments more carefully and improve correctness in a few
key places
Improve inferrability (avoid abstract types JuliaImages/OpenCV.jl#1)
This has not been tested (I don't know how, see JuliaImages/OpenCV.jl#3), so don't merge this unquestioningly.