@@ -10,7 +10,7 @@ processing. The core function is `imfilter`, and common kernels
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Let's start with a simple example of linear filtering:
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``` julia
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- julia> using ImagesFiltering , TestImages
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+ julia> using ImageFiltering , TestImages
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julia> img = testimage (" mandrill" );
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@@ -29,7 +29,7 @@ The most commonly used function for filtering is [`imfilter`](@ref).
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``` @meta
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DocTestSetup = quote
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- using Colors, ImagesFiltering , TestImages
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+ using Colors, ImageFiltering , TestImages
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img = testimage("mandrill")
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end
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```
@@ -118,7 +118,7 @@ OffsetArrays.OffsetArray{Float64,1,Array{Float64,1}} with indices -1:1:
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0.333333
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julia> kernf = kernelfactors ((kern1, kern1))
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- (ImagesFiltering . KernelFactors. ReshapedOneD {Float64,2,0,OffsetArrays.OffsetArray{Float64,1,Array{Float64,1}}} ([0.333333 ,0.333333 ,0.333333 ]),ImagesFiltering . KernelFactors. ReshapedOneD {Float64,2,1,OffsetArrays.OffsetArray{Float64,1,Array{Float64,1}}} ([0.333333 ,0.333333 ,0.333333 ]))
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+ (ImageFiltering . KernelFactors. ReshapedOneD {Float64,2,0,OffsetArrays.OffsetArray{Float64,1,Array{Float64,1}}} ([0.333333 ,0.333333 ,0.333333 ]),ImageFiltering . KernelFactors. ReshapedOneD {Float64,2,1,OffsetArrays.OffsetArray{Float64,1,Array{Float64,1}}} ([0.333333 ,0.333333 ,0.333333 ]))
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julia> kernp = broadcast (* , kernf... )
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OffsetArrays. OffsetArray{Float64,2 ,Array{Float64,2 }} with indices - 1 : 1 ×- 1 : 1 :
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