X-Git-Url: http://git.euphorik.ch/?a=blobdiff_plain;f=Parasitemia%2FParasitemia%2FKMeans.fs;fp=Parasitemia%2FParasitemia%2FKMeans.fs;h=0000000000000000000000000000000000000000;hb=4bfa3cbdc6145e6944f02e24829ab2ef3a851ac1;hp=98352fea2ff287236d0654bb4e258ce153e8166b;hpb=48ecdfc43001c444eff6ad442986049384674af2;p=master-thesis.git diff --git a/Parasitemia/Parasitemia/KMeans.fs b/Parasitemia/Parasitemia/KMeans.fs deleted file mode 100644 index 98352fe..0000000 --- a/Parasitemia/Parasitemia/KMeans.fs +++ /dev/null @@ -1,70 +0,0 @@ -module KMeans - -open System.Collections.Generic -open System.Drawing - -open Emgu.CV -open Emgu.CV.Structure - -type Result = { - fg: Image - mean_bg: float32 - mean_fg: float32 - d_fg: Image } // Euclidean distances of the foreground to mean_fg. - -let kmeans (img: Image) : Result = - let nbIteration = 4 - let w = img.Width - let h = img.Height - - let min = ref [| 0.0 |] - let minLocation = ref <| [| Point() |] - let max = ref [| 0.0 |] - let maxLocation = ref <| [| Point() |] - img.MinMax(min, max, minLocation, maxLocation) - - let minf = float32 (!min).[0] - let maxf = float32 (!max).[0] - - let mutable mean_bg = maxf - (maxf - minf) / 4.f - let mutable mean_fg = minf + (maxf - minf) / 4.f - use mutable d_bg : Image = null - let mutable d_fg : Image = null - let fg = new Image(img.Size) - - let imgData = img.Data - let fgData = fg.Data - - for i in 1 .. nbIteration do - match d_bg with - | null -> () - | _ -> - d_bg.Dispose() - d_fg.Dispose() - - // EmGu doesn't import the in-place version of 'AbsDiff' so we have to create two images for each iteration. - d_bg <- img.AbsDiff(Gray(float mean_bg)) - d_fg <- img.AbsDiff(Gray(float mean_fg)) - - CvInvoke.Compare(d_fg, d_bg, fg, CvEnum.CmpType.LessThan) - - let mutable bg_total = 0.f - let mutable bg_nb = 0 - - let mutable fg_total = 0.f - let mutable fg_nb = 0 - - for i in 0 .. h - 1 do - for j in 0 .. w - 1 do - if fgData.[i, j, 0] > 0uy - then - fg_total <- fg_total + imgData.[i, j, 0] - fg_nb <- fg_nb + 1 - else - bg_total <- bg_total + imgData.[i, j, 0] - bg_nb <- bg_nb + 1 - - mean_bg <- bg_total / float32 bg_nb - mean_fg <- fg_total / float32 fg_nb - - { fg = fg; mean_bg = mean_bg; mean_fg = mean_fg; d_fg = d_fg } \ No newline at end of file