@@ -14,7 +14,7 @@ function segment_image(
1414 )
1515 seg = unseeded_region_growing (img, threshold)
1616 if prune
17- println (" Pruning segments smaller than $min_size pixels" )
17+ # println("Pruning segments smaller than $min_size pixels")
1818 seg = prune_segments (seg, label -> segment_pixel_count (seg, label) < min_size, (l1, l2) -> colordiff (segment_mean (seg, l1), segment_mean (seg, l2)))
1919 end
2020 return seg
@@ -34,18 +34,18 @@ function stimulus_index(seg::SegmentedImage, colorproj = RGB{Float32}(1, 1, -2))
3434 return i
3535end
3636
37- function contiguous (seg:: SegmentedImage , img:: AbstractMatrix{<:Color} ; min_size:: Int = 50 )
38- L = label_components (labels_map (seg)) # insist on contiguous regions
39- newseg = SegmentedImage (img, L)
40- newseg = prune_segments (newseg, label -> segment_pixel_count (newseg, label) < min_size, (l1, l2) -> colordiff (segment_mean (newseg, l1), segment_mean (newseg, l2)))
41- mapping = Dict (k => Set {Int} () for k in segment_labels (seg))
42- for (i, l) in pairs (seg. image_indexmap)
43- push! (mapping[l], newseg. image_indexmap[i])
44- end
45- return mapping
46- end
47- contiguous (seg:: SegmentedImage , img:: AbstractMatrix{<:Colorant} ; kwargs... ) =
48- contiguous (seg, color .(img); kwargs... )
37+ # function contiguous(seg::SegmentedImage, img::AbstractMatrix{<:Color}; min_size::Int = 50)
38+ # L = label_components(labels_map(seg)) # insist on contiguous regions
39+ # newseg = SegmentedImage(img, L)
40+ # newseg = prune_segments(newseg, label -> segment_pixel_count(newseg, label) < min_size, (l1, l2) -> colordiff(segment_mean(newseg, l1), segment_mean(newseg, l2)))
41+ # mapping = Dict(k => Set{Int}() for k in segment_labels(seg))
42+ # for (i, l) in pairs(seg.image_indexmap)
43+ # push!(mapping[l], newseg.image_indexmap[i])
44+ # end
45+ # return mapping
46+ # end
47+ # contiguous(seg::SegmentedImage, img::AbstractMatrix{<:Colorant}; kwargs...) =
48+ # contiguous(seg, color.(img); kwargs...)
4949
5050struct Spot
5151 npixels:: Int
@@ -75,7 +75,7 @@ function spots(
7575 label = seg. image_indexmap
7676 R = CartesianIndices (label)
7777 Ibegin, Iend = extrema (R)
78- I1 = one (Ibegin)
78+ I1 = oneunit (Ibegin)
7979 centroidsacc = Dict {Int, Tuple{Int, Int, Int}} () # accumulator for centroids
8080 nadj = Dict {Tuple{Int, Int}, Int} () # number of times two segments are adjacent
8181 for idx in R
@@ -140,11 +140,11 @@ function upperleft(spotdict::AbstractDict{Int, Spot}, stimulus, imgsize)
140140 return Dict (k => flip (v) for (k, v) in spotdict), sidx => flip (ss)
141141end
142142
143- function colorize (seg:: SegmentedImage , coloridx:: AbstractDict , colors= distinguishable_colors (length (unique (values (coloridx)))))
144- label = seg. image_indexmap
145- img = similar (label, eltype (colors))
146- for idx in eachindex (label)
147- img[idx] = colors[coloridx[label[idx]]]
148- end
149- return img
150- end
143+ # function colorize(seg::SegmentedImage, coloridx::AbstractDict, colors=distinguishable_colors(length(unique(values(coloridx)))))
144+ # label = seg.image_indexmap
145+ # img = similar(label, eltype(colors))
146+ # for idx in eachindex(label)
147+ # img[idx] = colors[coloridx[label[idx]]]
148+ # end
149+ # return img
150+ # end
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