X-Git-Url: http://git.euphorik.ch/?p=master-thesis.git;a=blobdiff_plain;f=Parasitemia%2FParasitemiaCore%2FKMeans.fs;h=c0276d90abbd12e422c64f898e49b4954c6ceaa2;hp=86f1e3b5a7102cacbb12c7aa394ccb3683c75cfc;hb=2d712781def419c9acc98368f7102b19b064f16d;hpb=4bfa3cbdc6145e6944f02e24829ab2ef3a851ac1

diff --git a/Parasitemia/ParasitemiaCore/KMeans.fs b/Parasitemia/ParasitemiaCore/KMeans.fs
index 86f1e3b..c0276d9 100644
--- a/Parasitemia/ParasitemiaCore/KMeans.fs
+++ b/Parasitemia/ParasitemiaCore/KMeans.fs
@@ -6,22 +6,24 @@ open System.Drawing
 open Emgu.CV
 open Emgu.CV.Structure
 
-type Result = {
-    fg: Image<Gray, byte>
-    mean_bg: float32
-    mean_fg: float32
-    d_fg: Image<Gray, float32> } // Euclidean distances of the foreground to mean_fg.
-
-let kmeans (img: Image<Gray, float32>) : Result =
+type Result =
+    {
+        fg : Image<Gray, byte>
+        mean_bg : float32
+        mean_fg : float32
+        d_fg : Image<Gray, float32> // Euclidean distances of the foreground to mean_fg.
+    }
+
+let kmeans (img : Image<Gray, float32>) : Result =
     let nbIteration = 4
     let w = img.Width
     let h = img.Height
 
     let min = ref [| 0.0 |]
-    let minLocation = ref <| [| Point() |]
+    let minLocation = ref <| [| Point () |]
     let max = ref [| 0.0 |]
-    let maxLocation = ref <| [| Point() |]
-    img.MinMax(min, max, minLocation, maxLocation)
+    let maxLocation = ref <| [| Point () |]
+    img.MinMax (min, max, minLocation, maxLocation)
 
     let minf = float32 (!min).[0]
     let maxf = float32 (!max).[0]
@@ -30,23 +32,23 @@ let kmeans (img: Image<Gray, float32>) : Result =
     let mutable mean_fg = minf + (maxf - minf) / 4.f
     use mutable d_bg : Image<Gray, float32> = null
     let mutable d_fg : Image<Gray, float32> = null
-    let fg = new Image<Gray, byte>(img.Size)
+    let fg = new Image<Gray, byte> (img.Size)
 
     let imgData = img.Data
     let fgData = fg.Data
 
-    for i in 1 .. nbIteration do
+    for i = 1 to nbIteration do
         match d_bg with
         | null -> ()
         | _ ->
-            d_bg.Dispose()
-            d_fg.Dispose()
+            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))
+        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)
+        CvInvoke.Compare (d_fg, d_bg, fg, CvEnum.CmpType.LessThan)
 
         let mutable bg_total = 0.f
         let mutable bg_nb = 0
@@ -54,10 +56,9 @@ let kmeans (img: Image<Gray, float32>) : Result =
         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
+        for i = 0 to h - 1 do
+            for j = 0 to w - 1 do
+                if fgData.[i, j, 0] > 0uy then
                     fg_total <- fg_total + imgData.[i, j, 0]
                     fg_nb <- fg_nb + 1
                 else