Get the demo examples working with Images 0.26.

Project.toml

@@ -11,13 +11,6 @@ LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 StaticArrays = "90137ffa-7385-5640-81b9-e52037218182"
 Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
 
-[compat]
-AxisAlgorithms = "0.3, 1"
-CoordinateTransformations = "0.5, 0.6"
-Images = "0.18, 0.19, 0.20, 0.21, 0.22, 0.23"
-Interpolations = "0.10, 0.11, 0.12, 0.13"
-StaticArrays = "0.10, 0.11, 0.12, 1"
-julia = "1"
 
 [extras]
 ImageMagick = "6218d12a-5da1-5696-b52f-db25d2ecc6d1"

demo/demo_farneback.jl

@@ -1,5 +1,4 @@
-using ImageMagick
-using Images, TestImages, StaticArrays, ImageTracking, ImageView, LinearAlgebra, CoordinateTransformations, Gtk.ShortNames
+using Images, ImageTracking, ImageView, LinearAlgebra, CoordinateTransformations
 #=Image Credit:  C. Liu. Beyond Pixels: Exploring New Representations and
 #Applications for Motion Analysis. Doctoral Thesis. Massachusetts Institute of
 #Technology. May 2009. =#

demo/demo_lucas_kanade.jl

@@ -1,9 +1,9 @@
-using Images, TestImages, StaticArrays, ImageTracking, ImageView, LinearAlgebra, CoordinateTransformations, Gtk.ShortNames
+using Images, StaticArrays, ImageTracking, ImageView, LinearAlgebra, CoordinateTransformations
 #=Image Credit:  C. Liu. Beyond Pixels: Exploring New Representations and
 #Applications for Motion Analysis. Doctoral Thesis. Massachusetts Institute of
 #Technology. May 2009. =#
-img1 = load("demo/table1.jpg")
-img2 = load("demo/table2.jpg")
+img1 = load("table1.jpg")
+img2 = load("table2.jpg")
 
 corners = imcorner(img1, method=shi_tomasi)
 I = findall(!iszero, corners)

src/lucas_kanade.jl

@@ -149,6 +149,74 @@
     displacement, status
 end
 
+# TODO: Images.integral_image has been deprecated in favor of IntegralArrays.jl
+# Included here to get this package working with newer versions of Images.jl
+# Should this package use IntegralArrays.jl like the depreciation notes suggest?
+
+accum(::Type{T}) where {T<:Integer} = Int
+accum(::Type{Float32})    = Float32
+accum(::Type{T}) where {T<:Real} = Float64
+accum(::Type{Gray{T}}) where {T} = accum(T)
+
+"""
+```
+integral_img = integral_image(img)
+```
+
+Returns the integral image of an image. The integral image is calculated by assigning
+to each pixel the sum of all pixels above it and to its left, i.e. the rectangle from
+(1, 1) to the pixel. An integral image is a data structure which helps in efficient
+calculation of sum of pixels in a rectangular subset of an image. See `boxdiff` for more
+information.
+"""
+function integral_image(img::AbstractArray)
+    integral_img = Array{accum(eltype(img))}(undef, size(img))
+    sd = coords_spatial(img)
+    cumsum!(integral_img, img, dims=sd[1])
+    for i = 2:length(sd)
+        cumsum!(integral_img, integral_img, dims=sd[i])
+    end
+    integral_img
+end
+
+"""
+```
+sum = boxdiff(integral_image, ytop:ybot, xtop:xbot)
+sum = boxdiff(integral_image, CartesianIndex(tl_y, tl_x), CartesianIndex(br_y, br_x))
+sum = boxdiff(integral_image, tl_y, tl_x, br_y, br_x)
+```
+
+An integral image is a data structure which helps in efficient calculation of sum of pixels in
+a rectangular subset of an image. It stores at each pixel the sum of all pixels above it and to
+its left. The sum of a window in an image can be directly calculated using four array
+references of the integral image, irrespective of the size of the window, given the `yrange` and
+`xrange` of the window. Given an integral image -
+
+        A - - - - - - B -
+        - * * * * * * * -
+        - * * * * * * * -
+        - * * * * * * * -
+        - * * * * * * * -
+        - * * * * * * * -
+        C * * * * * * D -
+        - - - - - - - - -
+
+The sum of pixels in the area denoted by * is given by S = D + A - B - C.
+"""
+boxdiff(int_img::AbstractArray{T, 2}, y::UnitRange, x::UnitRange) where {T} =
+    boxdiff(int_img, y.start, x.start, y.stop, x.stop)
+
+boxdiff(int_img::AbstractArray{T, 2}, tl::CartesianIndex, br::CartesianIndex) where {T} =
+    boxdiff(int_img, tl[1], tl[2], br[1], br[2])
+
+function boxdiff(int_img::AbstractArray{T, 2}, tl_y::Integer, tl_x::Integer, br_y::Integer, br_x::Integer) where T
+    sum = int_img[br_y, br_x]
+    sum -= tl_x > 1 ? int_img[br_y, tl_x - 1] : zero(T)
+    sum -= tl_y > 1 ? int_img[tl_y - 1, br_x] : zero(T)
+    sum += tl_y > 1 && tl_x > 1 ? int_img[tl_y - 1, tl_x - 1] : zero(T)
+    sum
+end
+
 function compute_partial_derivatives(Iy, Ix; σ = 4)
     kernel = KernelFactors.gaussian(σ)
     kernel_factors = kernelfactors((kernel, kernel))