Update to ImageCore 0.9

Author: timholy

Project.toml

@@ -4,7 +4,6 @@ version = "1.5.1"
 
 [deps]
 Clustering = "aaaa29a8-35af-508c-8bc3-b662a17a0fe5"
-ColorVectorSpace = "c3611d14-8923-5661-9e6a-0046d554d3a4"
 DataStructures = "864edb3b-99cc-5e75-8d2d-829cb0a9cfe8"
 Distances = "b4f34e82-e78d-54a5-968a-f98e89d6e8f7"
 ImageCore = "a09fc81d-aa75-5fe9-8630-4744c3626534"
@@ -20,11 +19,10 @@ Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
 
 [compat]
 Clustering = "0.10, 0.11, 0.12, 0.13, 0.14"
-ColorVectorSpace = "0.7, 0.8"
 DataStructures = "0.17.11, 0.18"
 Distances = "0.8, 0.9.2, 0.10"
 Documenter = "0.24, 0.25"
-ImageCore = "0.8.6"
+ImageCore = "0.9"
 ImageFiltering = "0.6"
 ImageMorphology = "0.2.6"
 LightGraphs = "1.1"
@@ -36,8 +34,7 @@ julia = "1"
 
 [extras]
 Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
-Images = "916415d5-f1e6-5110-898d-aaa5f9f070e0"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 
 [targets]
-test = ["Documenter", "Images", "Test"]
+test = ["Documenter", "Test"]

src/ImageSegmentation.jl

@@ -4,6 +4,7 @@ import Base: show
 
 using LinearAlgebra, Statistics
 using DataStructures, StaticArrays, ImageCore, ImageFiltering, ImageMorphology, LightGraphs, SimpleWeightedGraphs, RegionTrees, Distances, StaticArrays, Clustering, MetaGraphs
+using ImageCore.ColorVectorSpace: MathTypes
 import Clustering: kmeans, fuzzy_cmeans
 
 include("compat.jl")
@@ -41,7 +42,7 @@ export
     kmeans,
     fuzzy_cmeans,
     merge_segments,
-    
+
     # types
     SegmentedImage,
     ImageEdge

src/core.jl

@@ -3,6 +3,14 @@ accum_type(::Type{Float32})    = Float32
 accum_type(::Type{T}) where {T<:Real} = Float64
 accum_type(::Type{C}) where {C<:Colorant} = base_colorant_type(C){accum_type(eltype(C))}
 
+accum_type(val) = isa(val, Type) ? throw_accum_type(val) : convert(accum_type(typeof(val)), val)
+throw_accum_type(T) = error("type $T not supported in `accum_type`")
+
+_abs2(c::MathTypes) = c ⋅ c
+_abs2(x) = abs2(x)
+
+default_diff_fn(c1::CT1,c2::CT2) where {CT1<:Union{Colorant,Real}, CT2<:Union{Colorant,Real}} = sqrt(_abs2(c1-accum_type(c2)))
+
 """
 `SegmentedImage` type contains the index-label mapping, assigned labels,
 segment mean intensity and pixel count of each segment.

src/felzenszwalb.jl

@@ -93,11 +93,12 @@ function felzenszwalb(img::AbstractArray{T, 2}, k::Real, min_size::Int = 0) wher
     I1, Iend = first(R), last(R)
     num = 1
     for I in R
+        imgI = img[I]
         for J in CartesianIndices(_colon(max(I1, I-I1), min(Iend, I+I1)))
             if I >= J
                 continue
             end
-            edges[num] = ImageEdge((I[2]-1)*rows+I[1], (J[2]-1)*rows+J[1], sqrt(sum(abs2,(img[I])-meantype(T)(img[J]))))
+            edges[num] = ImageEdge((I[2]-1)*rows+I[1], (J[2]-1)*rows+J[1], sqrt(_abs2(imgI-meantype(T)(img[J]))))
             num += 1
         end
     end

src/region_growing.jl

@@ -1,6 +1,3 @@
-
-default_diff_fn(c1::CT1,c2::CT2) where {CT1<:Union{Colorant,Real}, CT2<:Union{Colorant,Real}} = sqrt(sum(abs2,(c1)-accum_type(CT2)(c2)))
-
 """
     seg_img = seeded_region_growing(img, seeds, [kernel_dim], [diff_fn])
     seg_img = seeded_region_growing(img, seeds, [neighbourhood], [diff_fn])

test/runtests.jl

@@ -1,5 +1,5 @@
-using ImageSegmentation, Images, Test, SimpleWeightedGraphs, LightGraphs, StaticArrays, DataStructures
-using RegionTrees: isleaf, Cell, split! 
+using ImageSegmentation, ImageCore, ImageFiltering, Test, SimpleWeightedGraphs, LightGraphs, StaticArrays, DataStructures
+using RegionTrees: isleaf, Cell, split!
 using MetaGraphs: MetaGraph, clear_props!, get_prop, has_prop, set_prop!, props, vertices
 
 using Documenter

test/watershed.jl

@@ -4,8 +4,7 @@ using ImageFiltering
 
     img = zeros(100, 100)
     img[25:75, 25:75] .= 1
-
-    img, _ = magnitude_phase(img)
+    img[26:74, 26:74] .= 0
 
     markers = zeros(Int, size(img))
     markers[1, 1] = 1
@@ -45,7 +44,7 @@ using ImageFiltering
         # since this is using the compact algorithm with a high value for
         # compactness, the boundary between labels 1 and 2 should occur halfway
         # between the two markers
-        @test sum(labels .== 1) == sum(1:50) - 2
+        @test sum(labels .== 1) == sum(1:50)
     end
 
     @testset "h-minima transform" begin